EVALUATING SOYBEAN GERMPLASM FROM USA, CHINA, AND BRAZIL FOR TOLERANCE TO ACIDIC SOILS IN INDONESIA By Agus Hasbianto A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Crop and Soil Sciences—Doctor of Philosophy 2019 ABSTRACT EVALUATING SOYBEAN GERMPLASM FROM USA, CHINA, AND BRAZIL FOR TOLERANCE TO ACIDIC SOILS IN INDONESIA By Agus Hasbianto The soybean production increases more slowly than the demand within the country. The opportunity to increase soybean production exists by planting soybean in the lands available outside the Java island, on acidic Ultisol soils. However, the number of soybean accessions that are tolerant to acidic soils is limited and these accessions do not have desirable traits to meet the market demands. The objective of the first study was to test the adaptability of selected soybean germplasm to acidic soils under greenhouse conditions. A total of 706 soybean accessions originating from the USA, China, and Brazil, were screened to select 20 best performing genotypes through two phases of greenhouse trials. In Phase 1, 60 best performing soybean genotypes were selected in a Peat moss medium at pH 5.0 using plant height and number of days taken for each line to reach V2 stage as the selection criteria. In phase 2, 20 best performing lines out of the previous 60 were selected based on their performance on at least two of three pH regimes; 4.5, 5.0 and 5.5. Of the 60 genotypes, the selected lines from USA and China reached the V2 stage in 12 - 24 days after planting while the selected lines from Brazil took slightly longer to reach the V2 stage with 16 - 30 days after planting. The goal of the second study was to evaluate the 20 selected lines from the previous study for tolerance to aluminum toxicity, a major concern in Indonesian low pH soils. We used the same medium but added aluminum hydroxide to the medium since Peat moss does not contain aluminum (Al). We conducted a greenhouse study where the previously selected 20 soybean lines were subjected to two levels of Al; 0.0% and 5% Al (by weight). Root length, number of root nodules, and plant height were taken as the dependent variables 35 days after planting as criteria for selection. All data were analyzed using ANOVA and LSD. The measured variables were significantly different at P < 0.0001. Plant height and root length of the 20 lines were higher in the medium with 5% Al compared to the control with 0.0% aluminum. The results indicated that the 20 selected lines would be tolerant to soils with low pH and Al3+ levels up to 5% by weight and could perform well under Indonesian acidic soils. The third study was intended to evaluate the 20 selected lines for tolerance to acidic soils in Indonesia and select promising lines for use that can be grown by farmers and/or used as parents in a soybean breeding program in Indonesia. We designed a field research for two seasons in 2017 and 2018, in two locations. To select the best performing out of the 20 lines under current farmer practices, a split-split plot design with three factors was used with lime as the main plot, organic fertilizer as the subplot, and soybean genotypes as the sub-subplot. Two farmer preferred varieties, ANJASMORO and DERING, were used as check varieties. Plant height, root length, number of root nodules, number of pods, and yield were used to evaluate the performance of the 20 lines. All data were analyzed using ANOVA and LSD. In 2017 season, the best four genotypes of the 20 lines tested with the highest yields were PI675661 with 3.08 tons/ha (for farmers who applied only lime), PI628880 with 2.46 tons/ha and PI628929 with 2.41 tons/ha (both: for farmers who applied only organic fertilizer), and PI628871 with 2.32 tons/ha (for farmers who applied a combination of both lime and organic fertilizer). In the 2018 season, the yield reported was the highest in PI628925 with 2.38 tons/ha (for farmers who applied a combination of lime and organic fertilizer), and PI675661 with 2.17 tons/ha and PI628929 with 2.03 tons/ha (both: for farmers who did not apply lime, but applied only organic fertilizer). PI675661 and PI628929 can be considered as the promising lines with superior traits: number of pods, yield, and larger seed size. I dedicate this dissertation to my beloved parents, my wife and all my family, and my teachers. iv ACKNOWLEDGEMENTS I am greatly thankful to ALLAH Subhanahu wa Ta’ala, the almighty God for His protection and compassion, and I truly thank my parents and my wife for their support, prayer, and encouragement that have never stopped. I would like to thank IAARD for providing scholarship through the Sustainable Management of Agricultural Research and Technology Dissemination (SMARTD) program and giving me a precious opportunity to join Michigan State University. I would like to express my deepest appreciation and sincere gratitude to my mentor and committee chair Dr. Cholani K. Weebadde, for her unlimited support, patience, and encouragement. She continues to strengthen my enthusiasm for research and course work. Her guidance and persistent support have made this dissertation being real. She has become one of the influential figures who inspire my scientific life. I would like to thank Dr. Russell Freed, Dr. Dechun Wang, Dr. Karim Maredia, and Dr. Brian Teppen for their support, advice, and willingness to serve on the committee. I would also like to thank Dr. Suneth Sooriyapathirana for his time and effort in helping me improve this dissertation. I would like to thank Randall L. Nelson and Todd Bedford from the National Soybean Research Center of USDA (USDA-NSRC) in Illinois for providing the seeds for our greenhouse and field studies. I thank Dr. Karen Cichy for providing spaces in the greenhouse and John Dahl for assisting in soil analysis. I thank Dr. Siddharth Chandra and the Asian Study Center of Michigan State University to fund our second field research in Indonesia. I would like to thank Dr. Muhammad Yasin, Director of the South Kalimantan Assessment Institute for Agricultural Technology (AIAT), Ir. Taufik Rahman (sub-division administration), Dr. Akhmad Hamdan (Banjarbaru Research Station), Dr. Aidi Noor, Mr. v Masdar, Mr. Agung Sutanto, and Mrs. Jumarni (Pelaihari Research Station). I would also like to thank Dr. Nurul Hidayatun, the Gene Bank Manager of ICABIOGRD Bogor, for her willingness and support towards keeping the seed of the soybean accessions. vi TABLE OF CONTENTS LIST OF TABLES ............................................................................................................. ix LIST OF FIGURES ........................................................................................................... xi KEY TO ABBREVIATIONS ........................................................................................... xii CHAPTER 1. GENERAL INTRODUCTION ................................................................ Background .......................................................................................................................... Soybean Production in Indonesia ......................................................................................... Challenges in Soybean Production ...................................................................................... Soybean Breeding Efforts in Indonesia ............................................................................... Importance of the Present Study .......................................................................................... Organization of the Dissertation and Objectives ................................................................. REFERENCES .................................................................................................................... CHAPTER 2. SCREENING SOYBEAN LINES FOR TOLERANCE TO ACIDIC SOIL .................................................................................................................................... Abstract ................................................................................................................................ Introduction .......................................................................................................................... Materials and Methods ......................................................................................................... Plant materials ............................................................................................................. Greenhouse screening experiments for determining tolerance to acidic soils ............ Selecting 20 best performing soybean genotypes each from the three regions USA, China and Brazil at pH 5.0 .......................................................................................... Selecting a total of 20 best performing soybean genotypes using three low pH regimes ......................................................................................................................... Results and Discussion ........................................................................................................ Selecting 20 best performing soybean genotypes each from the three regions USA, China and Brazil at pH 5.0 .......................................................................................... USA accessions ........................................................................................................... Chinese accessions ...................................................................................................... Brazilian accessions .................................................................................................... Selecting a total of 20 best performing soybean genotypes using three low pH regimes ......................................................................................................................... APPENDIX .......................................................................................................................... REFERENCES .................................................................................................................... CHAPTER 3. EVALUATION OF A SELECTED SET OF SOYBEAN LINES FOR TOLERANCE TO ALUMINUM TOXICITY ................................................................ Abstract ................................................................................................................................ Introduction .......................................................................................................................... vii 1 1 2 3 5 6 8 9 14 14 15 19 19 19 19 22 23 24 25 26 27 28 31 67 71 71 72 Materials and Methods ......................................................................................................... Plant material .............................................................................................................. Potting media .............................................................................................................. Planting ....................................................................................................................... Variables and data analysis ......................................................................................... Results and Discussion ........................................................................................................ APPENDIX .......................................................................................................................... REFERENCES .................................................................................................................... 75 76 76 77 78 78 82 92 CHAPTER 4. EVALUATION OF TWENTY SOYBEAN LINES FROM USA, CHINA, AND BRAZIL FOR TOLERANCE TO ACIDIC SOILS IN INDONESIA ................ Abstract ................................................................................................................................ Introduction .......................................................................................................................... Materials and Methods ......................................................................................................... Location and experimental design ............................................................................. Treatments ................................................................................................................. Soil test ...................................................................................................................... Maintenance .............................................................................................................. Observations and data analysis .................................................................................. Participatory selections with local farmers ............................................................... Results and Discussion ........................................................................................................ Line performance in the 2017 planting season .......................................................... Line performance in the 2018 planting season .......................................................... APPENDIX .......................................................................................................................... REFERENCES .................................................................................................................... 98 98 99 102 102 103 104 104 104 105 105 106 109 113 126 CHAPTER 5. CONCLUSIONS AND FUTURE DIRECTIONS .................................. Conclusions .......................................................................................................................... Future Directions ................................................................................................................. APPENDIX .......................................................................................................................... 130 130 131 133 viii LIST OF TABLES Table 2.1. Summary of the seed characteristics including seed weight, maturity group, and percent yellow seed coat of 706 lines from USA, China, and Brazil ................................... Table 2.2. Seed coat color, seed weight, and days taken by 20 selected USA lines to reach V2 stage ............................................................................................................................... 32 33 Table 2.3. Seed coat color, seed weight, and days taken by 20 selected Chinese lines to reach V2 stage ............................................................................................................................... 34 Table 2.4. Seed coat color, seed weight, and days taken by 20 selected Brazilian lines to reach V2 stage .............................................................................................................................. 35 Table 2.5. List of 91 soybean lines of the USA accessions .................................................. 36 Table 2.6. List of 407 lines of the Chinese accessions ........................................................ 39 Table 2.7. List of 208 soybean lines of the Brazilian accessions ......................................... 49 Table 2.8. Analysis of variance for plant height for the 706 lines using PROC ANOVA procedure (SAS 9.4) .............................................................................................................. 54 Table 2.9. Analysis of variance for plant height for 60 soybean lines tested on three different pH regimes using PROC MIXED procedure (SAS 9.4) ....................................................... 54 Table 2.10. Comparison of means for plant height for 55 surviving lines within the USA accessions used to select the best 20 out of 91 lines ............................................................. 55 Table 2.11. Comparison of means for plant height for 131 surviving lines within the Chinese accessions used to select the best 20 out of 407 lines ........................................................... 56 Table 2.12. Comparison of means for plant height for 155 surviving lines within the Brazilian accessions used to select the best 20 out of 208 lines ........................................................... 57 Table 2.13. Comparison of means for plant height for 60 lines grown on three pH regimes 58 Table 2.14. Comparison of means for root length for 60 lines grown on three pH regimes . 59 Table 3.1. Analysis of variance for plant height ................................................................... 83 ix Table 3.2. LSD means separation for root length ................................................................. 83 Table 3.3. LSD means separation for plant height ................................................................ 84 Table 3.4. LSD means separation for number of root nodules ............................................. 85 Table 3.5. pH of the medium pre- and post- study ............................................................... 85 Table 4.1. Soil test results from two locations in 2017 and 2018 growing seasons ............. 114 Table 4.2. Monthly rainfall during the field research in 2017 and 2018 growing seasons ... 115 Table 4.3. PI number, seed weight, and maturity group of soybean lines and local varieties used in 2017 and 2018 growing seasons ............................................................................... 115 Table 4.4. Analysis of variance for yield in the 2017 growing season ................................. 116 Table 4.5. Comparison of means for yield in the 2017 growing season ............................... 116 Table 4.6. Comparison of means for plant height in the 2017 growing season .................... 117 Table 4.7. Comparison of means for pod number in the 2017 growing season ................... 118 Table 4.8. Analysis of variance for yield in the 2018 growing season ................................. 119 Table 4.9. Comparison of means for yield in the 2018 growing season ............................... 119 Table 4.10. Comparison of means for pod number in the 2018 growing season ................. 120 Table 4.11. Comparison of means for root length in the 2018 growing season ................... 121 Table 4.12. Comparison of means for plant height in the 2018 growing season .................. 122 Table 5.1. The best performing soybean lines in both 2017 and 2018 growing seasons ...... 134 x LIST OF FIGURES Figure 2.1. Means of plant height in 55 surviving lines (60.4% of a total 91 lines) within the USA accessions at 35 days after planting ............................................................................. 60 Figure 2.2. Means of plant height in 131 surviving lines (32.2% of total 407 lines) within Chinese accessions at 35 days after planting ........................................................................ Figure 2.3. Means of plant height in 155 surviving lines (74.5% of total 208 lines) within Brazilian accessions at 35 days after planting ...................................................................... Figure 2.4. Means of plant height in 39 surviving lines (65% of total 60 lines) grown on pH 4.5 at 35 days after planting (the second selection phase) .............................................. Figure 2.5. Means of plant height in 22 surviving lines (37% of total 60 lines) grown on pH 5.0 at 35 days after planting (the second selection phase) .............................................. Figure 2.6. Means of plant height in 22 surviving lines (37% of total 60 lines) grown on pH 5.5 at 35 days after planting (the second selection phase) .............................................. Figure 2.7. Means of root length in 44 surviving lines at pH 4.5, 5.0, and 5.5 (the second selection phase) ..................................................................................................................... Figure 3.1. Means of plant height in 20 soybean lines from day 7 to day 35 after planting (A0: 0% aluminum, A5: 5% aluminum treatments) .............................................................. 61 62 63 64 65 66 86 Figure 3.2. Means of root length in 20 soybean lines (at 35 days after planting) ................. 89 Figure 3.3. Means of plant height in 20 soybean lines (at 35 days after planting) ............... 90 Figure 3.4. Means of number of root nodules in 20 soybean lines (at 35 days after planting) 91 Figure 4.1. Layout of main plots, sub plots, and sub-sub plots in the field research ............. 123 Figure 4.2. Means of yield in the 20 selected lines and 2 local varieties for both 2017 and 2018 growing seasons ........................................................................................................... Figure 5.1. Future directions of the present study ................................................................ 124 135 xi KEY TO ABBREVIATIONS AIAT Assessment Institute for Agricultural Technology ANOVA One-way analysis of variance Al(OH)3 Aluminum hydroxide BSN ha Badan Standarisasi Nasional (National Standardization Agency) Hectare IAARD Indonesian Agency for Agricultural Research and Development ICABIOGRD Indonesian Center for Agricultural Biotechnology and Genetic Resource Research and Development ILETRI Indonesian Legume and Tuber Research Institute ISARI Indonesian Swampland Agriculture Research Institute kg LSD MSU MoA MG Kilogram Least Significant Difference Michigan State University Ministry of Agriculture Republic of Indonesia Maturity group NaOH Sodium hydroxide USDA-NSRC National Soybean Research Center of the U.S. Department of Agriculture SOM Soil organic matter VE V2 Emergence stage Second trifoliate stage xii CHAPTER 1. GENERAL INTRODUCTION Background Soybean has long been a part of the traditional cuisine of Indonesian people since the 12th century (Sidharta, 2008). It is the main ingredient used for a number of processed food items that represent a part of the basic diet in Indonesia. Two types of processed foods, tempeh and tofu, are consumed as side dishes and as vegetables on a daily basis. Soybean is widely accepted by all levels of the society as a high protein food (Astuti et al., 2000; Sumarno and Adie, 2010). Therefore, soybean is a valuable grain crop in Indonesia mainly as a source of protein and a cash crop. The protein content of Indonesian soybean varieties varies from 36.9 to 45.6% (Ginting and Tastra, 2007; Widowati, 2013), while some soybean varieties in the world contain up to 50% protein and more than 20% oil (Friedman and Brandon, 2001). Soybeans have become the preferred source of vegetable protein, because it costs much less than animal protein (Yun et al., 2005). The high protein content and the comparatively lower prices of soybean than other protein sources are the main factors that influence the demand for soybean. These factors also provide a strong basis for the government to choose soybean as the main affordable option to meet the protein needs of the society. The processed food industries are not only generating high protein food items but also providing employment for the community. Soybean-based food industries are operated by small scale households in both rural and urban areas and become beneficial as a source of household income for lower to middle economic class levels. The number of soy-based food businesses are estimated to be more than eight thousand units which employ hundreds of thousands of workers 1 (Astuti et al., 2000; BSN, 2012). Therefore, soybean is not only important for improving nutrition but also for improving the economy of the society. As an important source of protein for food and feed, soybean demand is always high and exceeds the national production capacity (Schilling, 2000). High demand for soybean is not only in the form of dry grain, but also soybean meal as a result of the rise in livestock populations. The soybean meal is one of the essential ingredients added in animal feed as the main protein source when mixed in with other items (Sudaryanto and Swastika, 2007). The Ministry of Agriculture of the Republic of Indonesia (MoA) (2015) reported that the national soybean demand in 2014 reached 2.235 million tons of dry grain, 5.67% higher than that of 2013. However, the total soybean production in the country was only 954,997 tons (Statistic Indonesia, 2014). Therefore, the deficit production of around 1.3 million tons requires imports to ensure food security. Given that production does not meet high demand for consumption, Indonesia has become one of the net soybean importers in the world and this has negatively affected the national economy. Saliem and Nuryanti (2011) noted that from 1990-2009, the expenditure of foreign exchange to import soybean reached $298 million per year with the highest expenditure of $698 million in 2008. This routine expense has been judged as a burden for Indonesia’s financial stability. The government is facing the issue of not being able to reduce import costs without affecting soybean availability. Soybean Production in Indonesia Considering the importance of soybean as a protein source for the majority of the Indonesian people, the government has taken steps to increase soybean production along with 2 rice and corn to ensure the national food security (MoA, 2015). Since 1980s, increasing soybean production has been met through two main strategies: increasing productivity and planting area. In 1970, a decade before these programs were carried out, soybean was planted on 0.69 million hectares with an average yield of 0.72 tons/ha. In 1990, a decade after running the programs, the planting area for soybean reached 1.33 million hectares with an average yield of 1.11 tons/ha (Sudaryanto and Swastika, 2007; Sumarno and Adie, 2010). Soybean production reached the highest level in 1992 with 1.7 million hectares of planting area and generated 1.9 million tons of soybean grain. Since then, soybean planting area continued to decrease due to the implementation of a monumental effort on achieving self- sufficiency in rice and corn and imbalanced competition with non-agriculture related developmental activities in the country (Sudaryanto and Swastika, 2007; Mulyani et al., 2009). Decline in soybean production is highly influenced by reduction of planting area in Java since the Java island became the central production area for soybean and other staple crops in Indonesia for decades (Sudaryanto and Swastika, 2007; Mulyani et al., 2009; Arnawa et al., 2015). Moreover, soybean is a secondary crop that is commonly planted after rice in rice- rice - soybean or rice -soybean-soybean rotation within a year (Suhartina et al., 2014). The fact that Java is the center for many staple crops makes it difficult for government to increase soybean production on this land. Therefore, expanding planting areas to outside of the Java island would be a necessity to enhance soybean production in Indonesia (Sumarno and Adie, 2010). Challenges in Soybean Production Efforts at increasing soybean production by the government has to face three primary challenges; low fertility of the available land, lack of market driven quality traits in existing 3 soybean varieties, and the unfavorable price paid for locally produced soybean. Shifting the soybean planting to areas outside of the Java island was conducted since the 1980s. The available soil for crop production including soybean is more than 40 million ha outside of the Java island but are dominated by Ultisols. This type of soil is found in Sumatra, Java, Bali, Kalimantan, Sulawesi, and Papua islands (Rachman et al. 2007; Mulyani et al., 2009; Rochayati and Dariah, 2012). Ultisols have potential to be developed as cropland, but it has several constraints such as acidity, low content of organic matter, and low Phosphorus (P) availability (Trakoonyingcharoen et al., 2005; Rochayati and Dariah, 2012). The low fertility issue of Ultisols can be addressed through fertilization, liming, and addition of organic matter (Mulyani et al., 2009). In some areas of Indonesia, application of 6.0 tons/ha of lime to acidic soils could raise soil pH to a higher- level ranging from 0.3 - 1.0 (Subandi and Wijanarko, 2013). Besides liming, adding organic matter has also shown to be substantial to increase soil organic matter (SOM) and to help plant growth and development. Furthermore, applying organic fertilizer to the soil has a positive effect to correct the soil pH (Whalen et al., 2000). Another benefit of organic fertilizer is that it helps enhance soil quality by increasing the activity of soil microorganisms (Subowo, 2010). However, the two soybean improvement programs implemented included the increasing of planting areas and liming, were not enough to increase soybean production without having high-yielding varieties that perform well on acidic soils. Seeds of the currently available soybean varieties in Indonesia such as WILIS and TANGGAMUS, are small to medium sized (Arsyad et al., 2007; Kristanto et al., 2013; IAARD, 2017), and does not meet the market demand (Schilling, 2000; Krisnawati and Adie, 2015). With these varieties, increasing soybean production is almost impossible because without a guaranteed market, farmers would not choose 4 soybean as a crop to grow. Therefore, providing soybean varieties that could meet market demand is critical and can be met by improving existing germplasm through a breeding program. In Indonesia, the soybean breeding program began in 1900s. By 2015, the program had released more than 80 soybean varieties with broad adaptations including some varieties with good tolerance to a low pH of 5.5 but with small and medium-sized seeds (Arsyad et al., 2007). If Indonesia is to benefit from producing soybean in the land that is currently available with Ultisols, the breeding efforts should focus on developing large seeded varieties with tolerance to acidic soils to encourage production. Soybean price is one of the significant factors influencing soybean production. In Indonesia, soybean production is managed manually making production less efficient. In the Indonesian market, the price of imported soybean is always lower than the locally produced soybean. The minimum price that is profitable for farmers is around Rp 9,000/kg or US$ 0.6/kg (US$ 1 = Rp 14,000). By selling soybean grain at this level, farmers are able to cover their expenses with some profit (Aldillah, 2015). However, the price of imported soybean is around Rp 6,000 to Rp 7,500/kg (Aldillah, 2015; Brata and Yasa, 2015). Therefore, the current situation of production for soybeans in not profitable for the economy. Perhaps planting better adapted, better yielding and market preferred varieties would help improve the profitability of current production systems. Soybean Breeding Efforts in Indonesia Improving soybean characteristics through plant breeding efforts in Indonesia started in 1918 with the sole focus of developing high yielding varieties with broad adaptability (Arsyad et al., 2007; IAARD, 2017). For developing better yielding soybean varieties, breeders used a 5 single source of germplasm with 13 varieties obtained from Taiwan (Mejaya, 2010; IAARD, 2017). Given that high yielding lines with broad adaptability were not necessarily useful to increase production in less favorable soil conditions, in the 1990s, there was a shift in the breeding programs to focus on developing specific characteristics such as adaptability of soybean lines for specific soil types. As a result, the Indonesian Agency for Agricultural Research and Development (IAARD) was able to release some varieties with superior traits. However, due to the limited germplasm accessions available in the country, the rate of improving soybean varieties with superior traits is rather limited. For example, the soybean breeding program at IAARD was only able to release nine improved soybean lines from 1918 – 1980 (IAARD, 2017). Some efforts were previously made to obtain soybean germplasm resources from Thailand, the Philippines, Columbia, Nigeria, Taiwan, and USA (Mejaya, 2010). As a result, the number of lines used in the soybean breeding program increased dramatically from 1981 through 2016. In 2010, there were 900 soybean lines in the IAARD germplasm collection (Chaerani et al., 2011). This allowed the release of 85 new superior soybean varieties by 2016 (IAARD, 2017). As the result, soybean yield increased compared to what it was at the beginning of the breeding program. In 2012, the average of soybean yield was 1.40 tons/ha which was 0.3 tons/ha higher than it was in 1992 (Nainggolan and Rachmat, 2014). Importance of the Present Study Although there was an increase in productivity, the area of soybean plantations continued to decline. Moreover, the newly released varieties had small and medium sized seeds which do not have a high demand in the market. Therefore, the breeding program needed a new direction for accelerating varietal improvement oriented towards developing varieties with consumer 6 preferred larger seed size, and adapted to acidic Ultisols, the land available to increase production. Evaluation of the land that can be used to expand soybean production in Indonesia revealed that much of this land contained acidic soils (Abdurrahman et al., 2007). In 1995, efforts focused on improving soybean varieties that are tolerant to acidic dry land generated some varieties such as SINDORO, SINGGALANG, SLAMET, TANGGAMUS, and DEMAS, that performed well on soils with a pH of 5.5 (Arsyad et al., 2007; IAARD, 2017). Of these, both TANGGAMUS and DEMAS released by IAARD, have good tolerance to acidic soils. However, the seed size of both these varieties does not meet with market standards that require larger seed sizes of over 13 g/100 seeds. Thus, developing large seeded soybean varieties that perform well in acidic soils is essential for Indonesia. However, there is only a total of 900 soybean germplasm accessions collected by IAARD; and of these only 12 lines are recorded as having some tolerance to acidic soils (Chaerani et al., 2011). Given that germplasm that can be used as parents is a primary constraint in the breeding program, it is critical that Indonesia accesses soybean germplasm resources as the first step towards improving the breeding program (Arsyad et al., 2007; Agrawal et al., 2013). The success of any breeding program depends on having access to a diverse pool of germplasm. Therefore, it is essential to obtain access to soybean germplasm from other parts of the world to improve the soybean breeding program in Indonesia - especially the large-seeded germplasm that show tolerance to acidic soils. Considering that the USA, China and Brazil successfully grow large-seeded soybean varieties on acidic soils; it is worthwhile to reach out to these countries and request access to the improved germplasm accessions in the hope of integrating these favorable traits into the local Indonesian varieties through breeding. 7 Organization of the Dissertation and Objectives This dissertation is organized into five chapters. The Chapter 1 is to provide a general introduction and objectives. The objectives of Chapter 2 are to 1. select 20 best performing soybean genotypes at pH 5.0 from each of the three regions the USA, China and Brazil and 2. select a total of 20 best performing soybean genotypes using three low pH regimes. The objective of Chapter 3 is to 1. evaluate the 20 selected lines from the previous study for tolerance to aluminum toxicity. The objectives of Chapter 4 are to 1. evaluate the 20 selected lines for tolerance to acidic soils in Indonesia and 2. select promising lines that can be grown by farmers and/or can be used as parents in a soybean breeding program in Indonesia. The Chapter 5 presents the overall conclusions and the future directions. 8 REFERENCES 9 REFERENCES Abdurrahman, Mulyani A., Irawan. 2007. Land resources for soybeans in Indonesia in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 168-184. In Bahasa Indonesia Agarwal D.K., Billore S.D., Sharma A.N., Dupare B.U., Srivastava S.K. 2013. Soybean: Introduction, Improvement, and Utilization in India—Problems and Prospects. Agric Res (December 2013) 2(4):293–300. DOI 10.1007/s40003-013-0088-0 Aldillah R., 2015. Projections for Indonesian soybean production and consumption. Journal of Applicable Quantitative Economic. Vol. 8 No. 1, February 2015. ISSN: 2301-8968. In Bahasa Indonesia Arnawa K., Tamba I.M., Anindita R. 2015. The impact of market power on soybean price in Indonesia. Asia Pacific Journal of Sustainable Agriculture Food and Energy (APJSAFE). ISSN: 2338-1345 –Vol. 3 (1) 1-6. Arsyad D.M., Adie M.M. and Kuswantoro H. 2007. Soybean varieties breeding on specific of agroecology in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 205-228. In Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/03/dele_9.darman-1.pdf Astuti M., Meliala A., Dalais F.S., Wahlqvistet M.L. 2000. Tempe, a nutritious and healthy food from Indonesia. Asia Pacific J Clin Nutr (2000) 9(4): 322–325. Brata I.G.C.S. and Yasa I.G.W.M. 2015. Degree of import disclosure and degree of soybean commodities in Indonesia. Journal of Economic Development. The University of Udayana, Bali. Vol. 4 No. 8. Pages: 873-897. ISSN: 2303-0178 Badan Stardarisasi Indonesia [BSN]. 2012. Tempeh: Indonesian gift to the world. Jakarta. In Bahasa Indonesia. Link: http://www.bsn.go.id/uploads/download/Booklet_tempe- printed21.pdf Chaerani, Hidayatun N., Utami D.W. 2011. Genetic Diversity of 50 Soybean Accessions Based on Ten Microsatellite Markers. AgroBiogen Journal 7(2):96-105. In Bahasa Indonesia. Link: http://ejurnal.litbang.pertanian.go.id/index.php/ja/article/viewFile/3775/3124 Friedman M. and Brandon D.L. 2001. Nutritional and Health Benefits of Soy Proteins. J. Agric. Food Chem., 2001, 49 (3), pp 1069–1086. DOI: 10.1021/jf0009246 10 Ginting and Tastra. 2007. The quality standard of soybeans seeds in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 444- 463. In Bahasa Indonesia IAARD. 2017. Description of soybean varieties released in 1918-2016. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/09/kedelai.pdf Krisnawati A. and Adie M.M. 2015. Selection of soybean genotypes by seed size and its prospects for industrial raw material in Indonesia. Procedia Food Science 3 (2015) 355 – 363. DOI: 10.1016/j.profoo.2015.01.039 Kristanto H., Arsyad D.M., Purwantoro. 2013. Acidic-dry land soybean characteristic. Cash crop Journal. Indonesian Agency for Agricultural Research and Development. No. 25- 2013: 1–10. In Bahasa Indonesia Mejaya M.J. 2010. Support of germplasm in the establishment of superior soybean varieties. Secondary Food Bulletin. The Indonesian Legume and Tuber Crops Research Institute. Vol. 19. Page:14-18. In Bahasa Indonesia. DOI: http://dx.doi.org/10.21082/bul%20palawija.v0n19.2010.p13-18 Ministry of Agriculture Republic of Indonesia-MoA. 2015. Strategic plan on the 2015-2019 period. In Bahasa Indonesia. Link: http://www1.pertanian.go.id/file/RENSTRA_2015- 2019.pdf Mulyani A., Rachman A., Dairah A., 2009. The spread of acidic-soil: potential and availability for agricultural development in Rock-phosphate: utilization of rock-phosphate as phosphate nutrient source. Pgs: 25-46. In Bahasa Indonesia Mulyani A., Sukarman, Hidayat A. 2009. Prospect of soybean extensification in Indonesia. Journal of Land Resources Vol. 3 No. 1. ISSN 1907-0799. In Bahasa Indonesia Nainggolan K. and Rachmat M. 2014. Self-sufficiency prospect of soybean in Indonesia. Journal PANGAN Vol. 23 No. 1. Pages: 83-92. In Bahasa Indonesia Rachman A, Subiksa IGM, Wahyunto. 2007. Soybean planting area development to sub-optimal land in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg.185-203. In Bahasa Indonesia Rochayati and Dariah. 2012. Acidic dry-land development: opportunities and challenges in Dry- land agriculture prospect in supporting food security. Indonesian Agency for Agricultural Research and Development (IAARD). Jakarta. pg. 187-206. In Bahasa Indonesia 11 Saliem H.P. and Nuryanti S. 2011. The global economic perspective of soybean and cassava to support food self-sufficient. National seminar on the result of a variety of beans and tubers. Malang. Indonesia. in Bahasa Indonesia Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2012/09/01_SET_Handewi- 1.pdf Schilling R. 2000. The soybean commodity and seed multiplication system in Indonesia. Mission report and proposals. The Center for International Cooperation in Agronomic Research for Development (CIRAD, France). Link: https://agritrop.cirad.fr/475487/1/ID475487.pdf Sidharta M. 2008. Soyfoods in Indonesia in The world of soy. University of Illinois Press. Urbana and Chicago. pg. 195-207. ISBN: 9780252033414 Statistic Indonesia [BPS]. 2014. Production of soybean by province. Link: www.bps.go.id/linkTableDinamis/view/id/871 Subandi and Wijanarko A,. 2013. The influence of liming technique on soybean growth and the yield on acidic dry-land. Journal of Penelitian pertanian tanaman pangan. Vol. 32 No. 3: 171-178. In Bahasa Indonesia Subowo G. 2010. Strategy to use organic matter efficiently to enhance soil fertility and productivity. Journal of land resource. Vol. 4 No. 1: 13-25. In Bahasa Indonesia Sudaryanto and Swastika. 2007. The Economic of soybean in Indonesia in in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 1-27. In Bahasa Indonesia Suhartina, Purwantoro, Novita Nugrahaeni, Abdullah Taufiq. 2014. Yield stability of drought tolerance soybean genotypes. Journal of crop farming research. IAARD. Vol. 33 No. 1: 54-60. In Bahasa Indonesia Sumarno and Adie M.M. 2010. The development strategies of soybean production towards sustainable food self-sufficiency. Journal of Iptek Tanaman Pangan. Vol. 5 no. 1: 49-63. In Bahasa Indonesia Trakoonyingcharoen P., Kheoruenromne I., Suddhiprakarn A., Gilkes R.J., 2005. Phosphate sorption by Thai red oxisols and red Ultisols. Soil science. Vol 170 No. 9: 716-725 Whalen J.K., Chang C., Clayton G.W., Carefoot J.P., 2000. Cattle manure amendments can increase the pH of acid soils. Soil Sci. Soc. Am. J. 64:962–966 12 Widowati S. 2013. Soybeans processing technique in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 491-521. In Bahasa Indonesia Yun J.H., Kwon I.K., Lohakare J.D., Choi J. Y., Yong J. S., Zheng J., Cho W. T., Chae B. J. 2005. Comparative efficacy of plant and animal protein sources on the growth performance, nutrient digestibility, morphology and caecal microbiology of early-weaned Pigs. Asian-Aust. J. Anim. Sci. 2005. Vol 18, No. 9: 1285-1293 13 CHAPTER 2. SCREENING SOYBEAN LINES FOR TOLERANCE TO ACIDIC SOIL Abstract Soybean is the third major crop in Indonesia after rice and corn. The soybean production increases more slowly than the demand within the country. The opportunity to increase soybean production exists by planting soybean in the land available outside of the Java island, on acidic Ultisol soils. However, the number of soybean accessions that are tolerant to acidic soils is limited and these accessions do not have desirable seed traits to meet the market demands. The objective of the present study was to test the adaptability of selected soybean germplasm to acidic soils under greenhouse conditions. A total of 706 soybean accessions originating from the USA, China, and Brazil, were screened to select 20 best performing genotypes from each country through two phases of greenhouse trials. In Phase 1, the 20 best performing soybean genotypes from each of the three countries were selected at pH 5.0 using plant height and number of days taken for each line to reach the V2 stage as the selection criteria. In phase 2, these 60 soybean genotypes were subjected to three low pH regimes; 4.5, 5.0 and 5,5 to select the best performing 20 genotypes in acidic soils using plants height and root length 55 days after planting as the selection criteria. Of the 60 genotypes, the 20 selected lines from USA and the 20 selected lines from China reached the V2 stage in 12 - 24 days after planting while the 20 selected lines from Brazil took slightly longer to reach V2 stage with 16 - 30 days after planting. In the second screening, 20 best performing lines out of the previous 60 were selected based on their performance on acidic soils with a pH of 4.5. Aluminum (Al) toxicity could hinder plant growth in low pH soils. Given that Al toxicity is a major concern in Indonesian low pH soils, further studies are needed to evaluate the performance under aluminum (Al) toxicity. 14 Introduction Soybean is the third strategic commodity after rice and maize in Indonesia. Soybean has been listed by the Indonesian government as one of the top national priority-crops in the food self-sufficiency programs for decades (Ministry of Agriculture Republic of Indonesia, MoA, 2015). The demand for soybean and two other commodities is increasing every year due to the importance of rice as the primary carbohydrate source, corn being the main component for the food and feed industry, and soybean as the most valuable protein source for humans and livestock. While both rice and corn have shown success in increasing yield due to plant breeding efforts, soybean production increases more slowly compared to the demand (Sudaryanto and Swastika, 2007; Supadi, 2010). The limited availability of fertile land and superior varieties has been identified as reasons for low production of soybean in Indonesia. For decades, the main area for crop production in the country was the Java Island contributing to more than 60% of the total food production of - mainly rice and soybean (Widiatmaka et al., 2016; Syuaib, 2016). However, in order to succeed in rice self-sufficiency, land allocation in Java was prioritized for rice. Therefore, increasing soybean production areas in the Java Island was no longer possible and the government needs to consider increasing soybean production in non-Java areas, which are particularly acidic dry-land areas. The total acidic dry-land area in Indonesia, as explained by Mulyani et al. (2009), is more than 102 million ha or a total of 69.46% of dry-land spread throughout the eight larger islands. Ultisols dominate the acidic dry-land (40.77%) that is available for soybean development programs in Indonesia. While the Ultisols soil have the potential to serve as cropland, it has several problems such as acidity, low content of soil organic matter, and low Phosphorus (P) availability 15 (Trakoonyingcharoen et al., 2005). In Indonesia, Ultisols soil have a pH ranging between 4.27 - 5.30, available, Al between 0.94 - 6.95 me/100 g, and available soil P (Bray) between 3.80 - 36.70 ppm (Rochayati and Dariah, 2012). According to Lyamuremye et al. (1996), the soil fertility problems associated with low soil pH, can be overcome by applying lime to the soil. The value of liming to correct soil acidity to enhance agricultural productivity is well documented. The importance of liming, according to Pagani (2011), is to increase soil pH regardless of their initial pH, with the range of increasing up to 2.50 units of pH for the first four years after application. The significant role of liming in fixing low pH problem is also well- known by the Indonesian government; and therefore, it has been applied to expand soybean planting areas from 1983 – 1987. The results were seen years later with an increase in soybean yield reaching over 1.5 tons/ha (Sumarno and Adie, 2010). Indonesian agriculture is dominated by small-holder resource-poor farmers most of whom do not have the capabilities to lime the soil to fix soil fertility constraints, despite understanding its importance. Farmers will not be able to afford and apply the lime due to limitations in capital. In this situation, providing farmers with superior varieties that can withstand acidic soils will be an excellent and long-term strategy for improving soybean production on acidic-soil. Plant breeding is a sustainable and long-term solution to help farmers and the government increase soybean production. Providing superior varieties adapted to acidic soils is more affordable for farmers than recommendations on liming and other types of conditioning the land (Adie and Krisnawati, 2016). Therefore, since 1995, Indonesia has changed the goals of the soybean breeding program from developing high yielding varieties with broad adaptability to improving soybean varieties that are tolerant to acidic dry-lands (Arsyad et al., 2013; IAARD, 16 2017). Varieties resulting from this program reported to have good tolerance to acidic soils but did not meet market preference of large seed sizes. For many years, the soybean breeding program in Indonesia depended on a limited number of accessions that are tolerant to acidic soils for use as parents. The Indonesian Center for Agricultural Biotechnology and Genetic Resource Research and Development (ICABIOGRD) has only 12 accessions out of more than 900 accessions that were reported to have tolerance to acidic soils (Chaerani et al., 2011). One of the most effective ways of enhancing a breeding program is to access new germplasm resources through plant introductions from other sources (Arsyad et al., 2013; Ibrahim et al., 2017). Considering the interest in increasing soybean production by growing the crop in acidic soils, improving the soybean breeding program in Indonesia could consider the following steps in the plant breeding process. These steps include determining objectives (1), accessing genetic variation (2), developing and selecting progeny (3) and disseminating varieties (4) (Bernardo, 2010). In the current study, our goal was to access germplasm from countries that successfully produce soybean in Ultisols under low pH conditions and conduct an initial evaluation of this germplasm under the conditions found in Indonesia, hence meeting the second step in the plant breeding process. Being the country of origin for soybean, China has the most significant collection of soybean germplasm with > 40,000 accessions, followed by the USA with > 18,000 accessions, and Brazil with > 10,000 accessions (Carter et al., 2003). These three countries also have soybeans production regions that have Ultisols with acidic conditions similar to Indonesia. Furthermore, the USA and Brazil are the largest soybean producers in the world and is home to excellent soybean breeding programs. As such, Indonesia can benefit from obtaining soybean germplasm from these countries to develop an adapted germplasm. Therefore, as the first step in 17 the current study, we obtained soybean germplasm from the above three countries that were available in the National Soybean Research Center of the U.S. Department of Agriculture (USDA). Prior to requesting the germplasm, we superimposed the world soil map along with the world pH map to identify the regions in these countries that successfully produce soybeans in acidic Ultisols. We then subjected the 706 germplasm accessions obtained from the USDA soybean germplasm repository to greenhouse testing to select a subset of germplasm accessions for further testing. The first screening test was designed to select a subset of 60 soybean accessions of the 706 obtained from USDA-NSRC depending on their performance on acidic soil during its vegetative stages. This selection phase was not only intended to narrow down the number of lines for further experimentation as we strived to identify the best performing soybean germplasm on acidic soils, but also to have an understanding of which of the lines would be useful for enhancing the diversity of soybean germplasm available in Indonesia. As pointed out by Rao and Hodgkin (2002), ecological and geographical factors play a role in the extent and distribution of genetic diversity of plant species. Therefore, an understanding of the available diversity within the soybean lines grown in acidic soils would assist us in determining which of the lines would be the most useful for breeding purposes. Therefore, the goal of this experiment was to select 20 best performing lines from each of the three countries of origin during the vegetative stages. 18 Materials and Methods Plant materials The plant material used in this study consisted of 706 soybean accessions obtained from the National Soybean Research Center of the United States Department of Agriculture (USDA- NSRC) in Urbana, Illinois. Among the lines were 91 originating from the USA, 407 lines from China, and 208 lines from Brazil, the three countries with the most significant number of soybean collections and planting area on acidic soils (Carter et al., 2003). A list of the soybean accessions with information on their origin is given in Tables 2.5 (USA), 2.6 (China) and 2.7 (Brazil). Greenhouse screening experiments for determining tolerance to acidic soils Selecting 20 best performing soybean genotypes each from the three regions USA, China and Brazil at pH 5.0 In order to obtain 20 best performing lines from each of the three regions, all of the 706 lines were planted on a screening medium with a pH of 5.0 as this represents the average pH level of Indonesian acidic soils. We conducted the experiment in the greenhouse given that naturally acidic soils that are comparable with that of Indonesia are not available in Michigan. We used Peat moss as the standard planting medium for greenhouse experiments at Michigan State University (MSU) as it is a pure acidic soil. However, this soil has a very low pH level around 3.5 and had to be raised to 5.0 using Sodium hydroxide (NaOH) as a strong base to bring the pH levels comparable to that of Indonesian acidic soils. To determine the amount of NaOH needed to achieve a pH of 5.0, we used a titration method (Whitney, 1998) which 19 consists of four steps: adding distilled water to peat moss sample, measuring the initial pH level of sample, making a 0.1 M NaOH solution, and titrating droplets of NaOH solution to peat moss sample until reaching the desired pH level. Adding distilled water to the peat moss sample is intended to dissolve soluble contents in the soil sample in order to measure the initial pH of the soil and to prepare the sample for the next titration steps. For this step, we added 28 ml of distilled water to approximately seven grams of dry peat moss in a small cup and stirred gently until soluble content of the soils dissolved in the water. The mixture was covered and left for 2 hours to allow time for all contents to dissolve before the actual pH of the peat moss solution was measured using a pH meter. The method was replicated three times to prepare three samples. For the next step, we prepared a 0.1 M NaOH solution by dissolving 4 grams of solid NaOH in 1,000 ml distilled water using Erlenmeyer or volumetric flask. In the titration step, 0.1M NaOH was added to the peat moss sample one drop at a time with a burette, until its pH was brought to 5.0 using a pH meter. The number of drops of NaOH needed to make the pH of the peat moss solution to 5.0 was used to calculate the volume of NaOH needed to prepare the soil medium for the greenhouse experiment. We used the titration results as a basis to raise the pH level of the peat moss to 5.0 in sufficient quantities being used for the screening test. Given that we required 706 pots filled with 22 grams of dry peat moss for the experiment, we needed 15,510 grams of peat moss. To prepare the medium, we mixed 55,224 ml of distilled water with the peat moss (considering 78 ml distilled water is added to each pot), and let the mixture stand in a closed box for about 5 - 6 hours to allow the material to be mixed. Next, 28,804 ml of 0.1 M NaOH solution was added to the prepared peat moss and the mixture was left to stand for about 12-24 hours. As a final step, 20 the pH of the prepared medium was measured to ensure that the pH level is 5.0 before filling the media into the pots. We planted three soybean seeds in each pot at 2.5 cm below the surface and allowed seeds to germinate and grow until V2, the vegetative phase previously identified. No chemical treatments were given to the soil since we were interested in observing the plant’s adaptation to specific pH conditions. However, we watered every pot daily using the same amount of distilled water. The distilled water was used in place of tap water to maintain soil pH level around 5.0. Daily observations were made to evaluate plant growth during the vegetative (V) phases. The variables observed in this experiment were plant height and the number of days taken for each plant to reach vegetative stages from emergence (VE) to the stage where we could observe at least two unrolled trifoliate leaves (V2). Plant height was measured at 35 days after planting as well as at the V2 stage. Plant height is an important variable to be measured in understanding the effect of H+ toxicity which begins to show in five days after planting (Kidd and Proctor, 2001; Adie and Krisnawati, 2016). The growth stage V2 is an important stage in plant growth that provides information regarding the plant’s response to acidic planting medium. In this stage, soybean roots have been well developed to support the development of root nodules and absorption of nutrients for plant growth (Lersten and Carlson, 2004; Pedersen and Licht, 2014). Given that nodular formation and active nitrogen fixation begins at the V2 stage in soybean, we considered V2 as critical for the plants to establish itself in acidic soils. Guidelines for soybean vegetative phases is based on Pedersen and Licht (2014). The data collected on plant height was tabulated using Microsoft Excel. We then sorted the data from the highest to lowest for each variable to simplify the genotypic selection. SAS 9.4 was used to analyze the data and generate an analysis of variance (ANOVA) table followed by 21 multiple comparisons if the result showed a significant difference at P≤ 0.05. In this experiment, we selected as many as 60 genotypes to represent the three countries of origin for the soybean accessions and will be used for future experimentation. Selecting a total of 20 best performing soybean genotypes using three low pH regimes The second screening test was used to select 20 soybean lines out of the previous 60 selected (20 from each of the countries USA, China and Brazil) that perform better on varying low pH levels. Thus, we used two factors for this study; the selected soybean genotypes (from the first screening), and the varying pH levels. The 60 selected soybean genotypes from the preliminary trial were treated with a commercial inoculant of Rhizobium bacteria prior to planting to assist nodule formation on soybean roots. The dose of inoculant was 0.4 gram per 100 grams of soybean seeds (USDA, 2015). Eighteen seeds of each of the genotypes were mixed with the inoculant in a small cup and planted directly on to the appropriate soil medium 5 to 10 minutes after mixing. For the second factor, the variation of soil pH level, we considered three pH levels: 4.5, 5.0 and 5.5. As in the first screening experiment, peat moss with an initial pH of 3.5 was selected as the preferred growing medium. Therefore, as described in the first screening experiment, the soil was treated with NaOH to achieve the desired pH level. The amount of NaOH needed to adjust the desired pH level was calculated using the same titration procedure (Whitney, 1998) and the process for mixing the distilled water and NaOH to prepare the medium for the greenhouse experiment remained unchanged. A total of 36,000 grams of peat moss and 69,000 ml of 0.1 M NaOH solution were needed to make as much as 360 pots of growth medium. We planted three seeds in each pot at 2.5 cm below the surface and allowed seeds to germinate and grow until V2, the vegetative phase previously identified. No chemical treatments 22 were provided to the seedlings except the seed inoculant with Rhizobium bacteria as we were particularly interested in evaluating the ability of each genotype to form nodules under naturally acidic field soil conditions. Plants were watered once or twice a day using tap water provided in the greenhouse depending on the condition of the soil surface moisture as a means of keeping the plants alive. Plant growth was monitored every three days to evaluate their performance in terms of plant height, and the vegetative stage reached. Observation of vegetative phases was determined in reference to Pedersen and Licht (2014). We also counted the number of root nodules on each genotype at the end of the research about 55 days after planting. Data were subjected to analysis of variance using SAS 9.4, and a test of means was used as a comparison tool to decide on the 20 best performing genotypes if the ANOVA test results showed a significant F-value (P≤ 0.05). Results and Discussion More than 90% of the selected lines had yellow color seed-coat (Table 2.1) which is a trait in high demand in the Indonesian market as the raw material for processed food and feed. Moreover, the selected lines also showed a wide range of maturity groups (MGs) and seed sizes. Therefore, the initial results shed promise for using the selected lines for potential release in Indonesia if they perform well in future field trials or for use as parents for improving current soybean varieties in the country. 23 Selecting 20 best performing soybean genotypes each from the three regions USA, China and Brazil at pH 5.0 When requesting the germplasm from USDA-NSRC, one of our criteria was that the germplasm be developed in or grown in regions that represent acidic Ultisols in the three countries Brazil, China and USA. The list of soybean accessions from the three regions shown in Table 2.5, 2.6, and 2.7. We assumed that such selection criteria would provide germplasm that could best perform under the land currently available to expand soybean cultivation in Indonesia. However, of the 706 plants, 36 accessions from USA, 276 accessions from China and 53 accessions from Brazil failed to survive to a stage where we could obtain measurements for plant height and/or did not reach V2 stage when planted in the acidic peat moss medium. As such, these accessions were excluded from any further experimentation. Significant differences of plant height were found among the 706 lines at P < 0.0001 (Table 2.8). The significant result from the analysis of variances justified selection of 60 lines through comparison of means, which was conducted for each group of lines so that the 20 best lines from each country of origin could be selected. Plant height could be determined by genetic factors and environmental factors including the plant’s adaptability to a low pH medium. Several investigations have reported the effect of low pH in reducing the plant growth rate (Board, 1991; Caires et al., 2008; Joris et al., 2013). Given our interest in selecting soybean genotypes that favorably respond to acidic soils, we considered plant height to be one of the indicators. Plant height is also used as one of the main indicators in evaluating soybean adaptability on acidic soil in Indonesia (Adie and Krisnawati, 2016). 24 USA accessions The results obtained from comparing the average plant height for the accessions from the USA is shown in Table 2.10 and Figure 2.1. As many as 55 lines (60%) grew successfully until 35 days after planting, while the rest of the lines did not survive. The ability of these lines to grow showed an initial tolerance to low pH soil. The 55 lines were of three seed-size categories, when compared to the seed-size standards used in Indonesia (Ginting and Tastra, 2013); small seeded (≤ 10.0 grams per 100 seeds), medium seeded (10.1 - ≤13.0 grams per 100 seeds), and large seeded (> 13.0 grams per 100 seeds). The maturity groups (MGs) of the accessions also showed a wide range between MG-I to MG-VIII. Among the 55 surviving lines, line number PI556727 had the highest plant height and was significantly different from 38 other lines from USA (Table 2.10). One hundred seeds of these accessions weighed 15.61 grams, hence were binned in the large-seeded category. Moreover, these accessions along with another eight accessions were grouped into MG-VIII, which is the most suitable category for the Indonesian climate. Number of plant stands that reached a V2 stage speaks to the ability of the selected lines to survive on an acidic growing medium. The number of the days taken by the 20 selected accessions from the USA to reach V2 is shown in Table 2.2. Ten of the accessions including PI556727 reached 100% plant stand in 17 to 24 days after planting meaning these lines showed tolerance to acidic soil conditions. This variable also allowed us to select accessions that are fast maturing. For example, accession PI594922 exhibits the shortest life span followed by PI556564. Early maturing accessions are of particular interest to Indonesian climate and planting season where soybean is generally planted at the end of the rainy season after rice or corn (Handayani et al., 2018). 25 Based on the comparison of means of plant height and the days for the plants to reach V2 stage 35 days after planting, the 20 selected lines from USA that show a higher value and plant stand are PI556727, PI556744, PI556537, PI556612, PI615694, PI556536, PI576154, PI590932, PI583367, PI548987, PI603953, PI556515, PI553047, PI584506, PI615695, PI556564, PI548986, PI556481, PI556584, PI594922. Chinese accessions The comparison of means for the 407 lines obtained from China and tested in the low pH medium is shown in Table 2.11 and Figure 2.2. Of these only 131 lines (32%) survived until 35 days after planting. Accession number PI567652 reached the highest value of plant height and significantly differed from the other 17 lines from China. This line together with another 130 lines showed some tolerance to low pH soil by surviving for 35 days after planting. The seed weight of the 131 surviving lines varied from 6.64 grams to 32.09 grams per 100 seeds which provides us with opportunities to select large seeded accessions of interest to Indonesia as 59 of the lines (45%) had a seed weight of ≥ 15.0 grams per 100 seeds and dominated by yellow seed-coat. The maturity groups for all surviving lines ranged from MG-IV to MG-VII. The number of days it took for the accessions from China to reach the V2 stage is shown in Table 2.4. Only six lines reached 100% plant stand at V2 stage, while other lines were less than 70%. According to this result, the accessions obtained from the USA had a higher plant stand than the Chinese accessions. However, all of these six lines reached the V2 stage at the same time of 20 days after planting which can be considered as promising lines due to the short season available for soybean in Indonesia (Arsyad et al., 2013), especially those lines with the 26 larger seeds. The other lines reached the V2 stage between 15 to 24 days with a maximum plant stand of 66.6%. Based on the comparison of means for plant height and the days taken for plants to reach the V2 stage at 35 days after planting, the 20 selected lines that show a highest values are PI567620B, PI594568B, PI567643, PI567652, PI587714A, PI603637A, PI567379A, PI567410C, PI567413, PI567611, PI567614C, PI567646A, PI567684B, PI567779A, PI587572B, PI587614, PI587692B, PI587768, PI594643, and PI603706B. Brazilian accessions For the 208 accessions obtained from Brazil the comparison of means are shown in Table 2.12 and Figure 2.3. With 155 accessions surviving (74.5%), Brazil provided the highest number of accessions performing under acidic soil conditions. Accession PI 675656 was the tallest among the 208 lines and was significantly different from 61 of the surviving lines obtained from Brazil. This line along with the other 154 lines showed some tolerance to low pH by surviving in acidic medium for 35 days after planting. The seed weight of all the 155 lines that survived, varied from 7.88 grams to 23.58 grams per 100 seeds. Of these, 76 lines (49%) had a seed weight ≥ 15.0 gram per 100 seeds. Of the germplasm obtained from USDA-NSRC, the number of large-seeded accessions was highest in those obtained from Brazil. Moreover, the yellow seeds also dominated the surviving lines obtained from Brazil increasing the opportunity to obtain lines with large seeds and yellow coat for improving the soybean breeding program in Indonesia. The maturity groups for all surviving lines ranged from MG-VI to MG-X. However, only a portion of the lines that survived could reach the V2 stage. 27 Table 2.4 shows the number of the days it took for the 20 accessions selected from the group obtained from Brazil to reach the V2 stage. Of these 20 lines, only seven lines reached 100% of plant stand and reached the V2 stage at 18 – 30 days after planting. These seven lines along with the rest of the 13 lines selected needed more days to reach the V2 stage, compared to the accessions obtained from USA and China. However, the accessions obtained from Brazil had the highest number of lines with large seeds size, and given that Brazil’s location is comparable to Indonesia, we hope these lines would be better adapted to Indonesian climate. Based on the comparison of means for plant height and the days needed to reach the V2 stage, the 20 selected lines from Brazil are PI628842, PI628929, PI628885, PI628962, PI675671, PI628873, PI628835, PI628848C, PI628894, PI628828, PI628812, PI628965, PI628925, PI675661, PI628809, PI675669, PI628869, PI628871, PI628952, and PI628880. Selecting a total of 20 best performing soybean genotypes using three low pH regimes We used all of the 60 lines selected in the previous experiment for this study. This study was specifically designed to determine the 20 best performing lines in three different pH levels. There were significant differences among the main effect of lines and pH levels to plant height (Table 2.9). Such differences would indicate the tolerance of each accession at different acidity levels of the growing media. Results showed significant differences between lines for the three pH levels, as well as for the interaction between lines and pH levels. Therefore, a multiple comparison was needed to select 20 lines from the 60 considered in the study. We intended to find 20 best performing accessions out of the 706 obtained from the USDA-NSRC based on their performance on various low pH levels. In order to narrow down the number of accessions from 60 to 20, we wanted to select accessions that were able to perform better in two of the three pH levels used in the second study. The results from the means 28 comparison of plant height variable are shown in Table 2.13. Of the 60 accessions, 44 lines survived in the medium with pH 4.5. Of these 44 lines, accession PI628871 showed the highest value for plant height and was significantly different from the other 40 lines that survived at pH 4.5 (Figure 2.4). The accession PI567611 showed the highest value for plant height among the lines that were tested at pH 5.0 (Figure 2.5), and line number PI628925 showed the highest value for plant height at pH 5.5 (Figure 2.6). However, different results were found for the root length variable (Table 2.14). The highest value for root length at each pH level were seen in PI556727, PI628871, and PI556537 for pH 4.5, 5.0, and 5.5 respectively. Means of root length of 44 survived accessions are shown in Table 2.14 and Figure 2.7. Root length of 44 survived plants at pH 4.5 were longer than surviving lines at both pH 5.0 and 5.5. Among all lines that survived at pH 4.5, PI556727 had better root growth and had the longest root length. In the medium with pH 5.0, among the 22 lines that survived, PI628871 was the accession with the highest root length. According to the data, several accessions were able to survive at all three pH levels including the lines PI556727, PI628871, and PI567611. In this study, we noted that the lines planted on growing medium with pH 4.5 performed better than lines planted on medium with slightly higher pH levels of 5.0 and 5.5. We believe this observation supports the explanation provided by Peterson (1982), Robson (1989) and Havlin et al. (2014) where a positive correlation between lower pH and the availability of manganese (Mn2+) was observed especially at pH < 5.0. The availability of Mn2+ for uptake by plants would increase the rate of photosynthesis and hence, plant growth. Based on the results of mean comparisons, the 20 lines selected are PI628871, PI628962, PI567611, PI556744, PI556727, PI615695, PI628925, PI567779A, PI556537, PI628842, PI594922, PI556515, PI590932, PI628929, PI628880, PI567410C, PI567643, PI556612, 29 PI675661, and PI556564. These lines performed better on either all the three pH levels or two of the three pH levels tested. 30 APPENDIX 31 Table 2.1. Summary of the seed characteristics including seed weight, maturity group, and percent yellow seed coat of 706 lines from USA, China, and Brazil Country of origin Number of lines % lines with yellow seed Maturity Range of 100 seed weight group (range) (g) coat 100 94 98 I – VIII 5.83 – 20.89 IV – VII 6.06 – 32.09 V - X 7.88 – 41.33 USA China Brazil 91 407 208 32 Table 2.2. Seed coat color, seed weight, and days taken by 20 selected USA lines to reach V2 stage No PI MG Seed coat Weight of color 100 seeds (gr) Days to reach V2 stage 33.3% 66.6% 100.0% 12 13 14 12 13 13 13 13 14 15 15 13 14 13 13 13 15 15 17 20 15 15 17 15 17 17 17 17 17 20 20 17 17 17 17 20 20 20 24 24 17 20 20 20 20 20 20 20 24 24 - - - - - - - - - - 1 PI594922 2 PI548987 3 PI548986 4 PI556564 V V VI VI yellow yellow yellow yellow 5 PI556727 VIII yellow 6 PI584506 7 PI615694 * 8 PI615695 9 PI556536 10 PI556584 11 PI556481 12 PI556515 13 PI556537 14 PI556744 15 PI576154 16 PI590932 17 PI556612 VII VII VII VII VII VII VIII VIII V VI IV VI 18 PI603953 * VIII 19 PI553047 20 PI583367 VII VII yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow 15.56 14.53 12.98 13.83 15.61 12.10 14.15 7.38 16.96 12.32 10.68 14.89 14.12 17.58 11.36 17.31 12.90 11.38 8.94 8.62 33 Table 2.3. Seed coat color, seed weight, and days taken by 20 selected Chinese lines to reach V2 stage Seed coat Weight of 100 Days to reach V2 stage seeds (gr) 33.3% 66.6% 100.0% 12 13 14 14 14 14 13 12 20 14 13 13 17 15 17 15 12 14 17 15 15 17 17 17 17 17 17 15 24 20 20 20 20 20 23 20 15 20 20 20 20 20 20 20 20 20 - - - - - - - - - - - - - - 10.53 15.00 16.72 9.42 11.72 12.66 16.35 13.91 6.64 10.60 11.72 16.22 10.34 16.33 15.42 13.44 21.38 13.38 8.64 13.29 34 No PI MG 1 PI567611 2 PI594568B 3 PI567643 4 PI567652 5 PI587714A 6 PI603637A 7 PI567379A IV V IV IV V V V color yellow yellow yellow yellow yellow yellow yellow 8 PI567410C VII yellow 9 PI567413 10 PI567620B 11 PI567614C 12 PI567646A 13 PI567684B 14 PI567779A 15 PI587572B 16 PI587614 V IV IV IV IV IV VI VI yellow yellow yellow yellow yellow yellow yellow yellow 17 PI587692B VII yellow 18 PI587768 19 PI594643 20 PI603706B VI V IV yellow yellow yellow Table 2.4. Seed coat color, seed weight, and days taken by 20 selected Brazilian lines to reach V2 stage No PI MG Seed coat Weight of 100 color seeds (g) Days to reach V2 stage 33.3% 66.6% 100.0% - - 18 - - 18 18 18 18 18 20 20 20 20 20 22 24 24 - - 16 18 20 20 20 24 25 24 27 27 24 24 24 24 27 27 27 30 24 27 18 24 24 24 30 30 30 - - - - - - - - - - - - - 1 PI628842 VIII yellow 2 PI628929 3 PI625695 4 PI628962 IX VII VII yellow yellow yellow 5 PI675671 VIII yellow 6 PI628873 7 PI628835 8 PI628848C VI VII VII yellow yellow yellow 9 PI628894 VIII yellow 10 PI628828 11 PI628812 12 PI628965 13 PI628925 14 PI675661 15 PI628809 16 PI675669 17 PI628869 18 PI628871 19 PI628952 20 PI628880 VI VI VII VIII X VI X VI VI VI V yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow yellow 14.75 18.92 13.46 14.07 23.17 13.28 14.47 14.08 13.01 15.05 13.45 13.52 14.51 15.24 16.20 14.72 15.71 14.21 12.72 13.91 35 Table 2.5. List of 91 soybean lines of the USA accessions No. PI Number Cultivar MG State Sub-collection Year Seed Weight (grams/100 seeds) PI561211 3172 PI561212 3202 PI556741 COKER 393 PI559379 3311 PI515961 Pennyrile PI576440 Calhoun PI590931 CF492 PI590932 CF461 PI611112 7499 PI548987 Dare PI572239 Holladay PI594922 Graham PI596414 Clifford PI556506 McNair 500 PI556697 TERRA-VIG 505 PI556742 COKER 355 PI556743 COKER 485 PI556744 COKER 425 PI596540 Camp-lx2 PI508266 Young PI511813 Twiggs PI542712 Bryan PI548835 3615 PI548985 Kershaw PI548986 Brim PI548988 Pickett PI556480 McNair 600 PI556504 LANCER PI556514 COKER 136 PI556564 COKER 156 PI556612 TERRA-VIG 606 PI556716 GK-67 PI556827 COKER 686 PI576154 Doles PI592756 Dillon PI597389 Prolina PI599333 Musen PI602597 Boggs PI614702 Soyola PI617045 NC-Roy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 I II III III IV IV IV IV IV V V V V V V V V V V VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI N. Carolina Private N. Carolina Private S. Carolina Private N. Carolina Private Kentucky Kentucky Kentucky Kentucky Kentucky Modern Modern Modern Modern Modern N. Carolina Modern N. Carolina Modern N. Carolina Modern N. Carolina Modern N. Carolina Private S. Carolina S. Carolina S. Carolina S. Carolina Private Private Private Private Kentucky Modern N. Carolina Modern Georgia Georgia Modern Modern N. Carolina Private S. Carolina Modern N. Carolina Modern N. Carolina Modern N. Carolina Private S. Carolina Private S. Carolina Private S. Carolina Private S. Carolina Private Georgia S. Carolina Georgia Private Private Modern S. Carolina Modern N. Carolina Modern S. Carolina Modern Georgia Modern N. Carolina Modern N. Carolina Modern 36 1994 1994 1984 1991 1987 1993 1995 1995 2000 1965 1993 1996 1997 1976 1983 1984 1984 1984 1996 1984 1987 1990 1991 1982 1990 1965 1974 1976 1973 1980 1981 1983 1987 1993 1994 1997 1997 1998 2000 2001 18.53 16.81 17.13 12.40 20.89 16.89 14.99 17.31 15.03 14.53 13.93 15.56 16.28 15.23 13.36 14.62 18.32 17.58 10.43 12.63 14.35 12.00 15.07 12.87 12.98 13.33 12.52 16.36 17.41 13.83 12.90 15.94 13.45 11.36 16.75 11.80 10.77 10.29 11.94 12.91 Table 2.5. Cont’d No. PI Number Cultivar MG State Subcollection Year Seed Weight (grams/100 seeds) 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 PI619615 N6201 VI N. Carolina Modern PI642732 Nitrasoy VI N. Carolina Modern PI522236 Thomas PI531068 Stonewall PI536009 Colquitt PI548657 Jackson PI548989 Ransom PI553041 Duocrop PI553042 Wright PI553046 Gasoy 17 PI553047 Gordon PI555453 Hagood VII Georgia VII Alabama VII Georgia Modern Modern Modern VII N. Carolina Modern VII N. Carolina Modern VII Georgia VII Georgia VII Georgia VII Georgia Modern Modern Modern Modern VII S. Carolina Modern PI556481 McNair 800 VII N. Carolina Private PI556516 TERRA-VIG 708 PI556536 COKER 237 PI556545 Brooks VII VII S. Carolina S. Carolina VII Georgia Private Private Private PI556583 McNair 710 VII N. Carolina Private PI556584 McNair 770 VII N. Carolina Private PI556623 COKER 317 PI556825 COKER 627 PI556847 6727 VII VII VII S. Carolina S. Carolina S. Carolina Private Private Private PI572238 Haskell VII Georgia Modern PI583367 Pearl PI584506 Carver PI595645 Benning PI615694 N7001 PI615695 N7103 PI617041 Santee PI619616 N7101 PI619617 N7102 VII N. Carolina Modern VII Alabama VII Georgia Modern Modern VII N. Carolina Modern VII N. Carolina Modern VII S. Carolina Modern VII N. Carolina Modern VII N. Carolina Modern PI641156 NC-Raleigh VII N. Carolina Modern PI647085 N7002 VII N. Carolina Modern PI661157 N7003CN VII N. Carolina Modern PI508267 Johnston VIII N. Carolina Modern VIII S. Carolina Modern VIII S. Carolina VIII S. Carolina VIII Georgia Private Private Modern Private Private PI536637 Perrin PI548697 Majos PI548698 Yelnanda PI553045 Cook PI556467 Coker Hampton 266A VIII S. Carolina PI556515 COKER 338 VIII S. Carolina 37 2002 2006 1988 1988 1989 1953 1970 1981 1979 1977 1984 1990 1974 1977 1978 1978 1980 1980 1982 1986 1987 1993 1994 1994 1996 2001 2001 2001 2002 2002 2005 2007 2011 1983 1988 1990 1990 1991 1971 1976 19.71 12.37 14.15 13.96 12.94 14.11 16.02 9.70 10.21 8.36 8.94 10.79 10.68 14.81 16.96 13.00 15.69 12.32 11.17 13.44 12.13 15.08 6.82 12.10 12.91 14.15 7.38 14.67 7.22 8.31 13.64 12.87 17.59 14.27 19.68 13.40 15.45 18.47 13.95 14.89 Table 2.5. Cont’d No. PI Number Cultivar MG State Subcollection Year Seed Weight (grams/100 seeds) 1978 1983 1984 1987 1992 1998 1999 2000 1962 2007 2008 14.12 11.30 15.61 13.07 14.53 11.38 12.43 10.22 16.03 19.66 5.83 81 82 83 84 85 86 87 88 89 90 91 PI556537 COKER 488 VIII S. Carolina PI556696 COKER 368 VIII S. Carolina PI556727 COLLIER VIII Georgia Private Private Private Private PI556848 6738 PI568236 Maxcy PI603953 Motte PI608033 Kuell PI612157 Prichard VIII S. Carolina VIII S. Carolina Modern VIII S. Carolina Modern VIII Alabama VIII Georgia Modern Modern PI614156 Hampton VIII S. Carolina Modern PI647086 N8001 PI654355 N8101 VIII N. Carolina Modern VIII N. Carolina Modern 38 Table 2.6. List of 407 lines of the Chinese accessions No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV Henan Jiangsu Jiangsu Hubei Anhui Jiangsu Shaanxi Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan Henan 10.37 15.89 18.72 16.11 15.73 13.20 12.42 10.60 11.46 11.72 12.69 16.47 10.53 14.48 14.98 8.40 13.86 13.99 22.14 14.25 16.72 16.22 20.73 12.46 14.02 9.24 8.05 14.75 21.65 12.01 13.64 11.49 16.22 22.21 13.93 9.81 8.83 18.20 12.74 10.80 1 PI103080 2 PI071444 3 PI071463 4 PI072227 5 PI446893 White Soybean Siu wong tau Wan No. 100-1 6 PI532455B Dan yang bai hua dou 7 PI567381A Bai ke huang 8 PI567611 9 PI567612 Ba yue zha Bo ai er zi bai dou 10 PI567614C Chang yuan xiao tian e dan 11 PI567614D Chang yuan xiao tian e dan 12 PI567615 Chen liu niu mao huang 13 PI567620B Guang shan tian e dan 14 PI567623 Ji yuan shui bai dou 15 PI567626 Jian ding da bai dou 16 PI567627B Kai feng xiao zi tie jiao huang 17 PI567630B Luan chuan ba yue zha bai dou 18 PI567631 19 PI567638 20 PI567639 21 PI567643 Luan chuan bai neng dou Min quan wan dou yuan Min quan yuan dan li Nei huang niu mao huang 22 PI567646A Pu yang tie jiao huang 23 PI567646B Pu yang tie jiao huang 24 PI567650A Ru nan huang mao dou 25 PI567650C Ru nan huang mao dou 26 PI567652 Shang cai qi yue ban 27 PI567654 28 PI567655 29 PI567658 Shang qiu bai hua cao Shang qiu tie jiao huang Tang yin bai hua cao huang dou 30 PI567660A Tong xu xiao zi huang 31 PI567660B Tong xu xiao zi huang 32 PI567661A Wei shi hong mao huang dou 33 PI567667A Xia yi zi hua jiao 34 PI567667B Xia yi zi hua jiao 35 PI567669 Xin an huang dou 36 PI567673B Yu cheng da zi tie jiao huang 37 PI567674 Yu cheng xiao tie jiao huang 38 PI567676A Yu xian da zi huang 39 PI567677 Yu xian huang dou 40 PI567684A Zheng zhou zao shu xiao zi huang 39 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) 41 PI567684B Zheng zhou zao shu xiao zi huang 42 PI567687 43 PI567698B 44 PI567701 45 PI567704 46 PI567707 47 PI567713B 48 PI567713D 49 PI567713E 50 PI567726 Fu yang 4 Fu yang 17 Fu yang 20 Fu yang 23 Fu yang 26 Fu yang 36 Fu yang 36 Fu yang 36 Fu yang 50 51 PI567739A Feng xian sun lou mei guo qing 52 PI567739B Feng xian sun lou mei guo qing 53 PI567743 54 PI567745 55 PI567747 56 PI567750 Gan yu zhe wang da hong mao chun dou Pei xian cheng guan tian e dan Pei xian da bai pi jia Pei xian da ping ding huang 57 PI567751A Pei xian hong mao you 58 PI567751B Pei xian hong mao you 59 PI567753C Pei xian liu yue xian 60 PI567755B Pei xian ping ding huang yi 61 PI567757 Pei xian tie jiao huang 62 PI567758 Pei xian tu shan da ping ding huang 63 PI567760 Pei xian xiao bai pi 64 PI567762A Pei xian xiao huang ke 65 PI567765D Sui ning da si li yi 66 PI567767B Tong shan da bai pi 67 PI567771C Tong shan da wu bai jian ke 68 PI567771D Tong shan da wu bai jian ke 69 PI567772 Tong shan hong mao you 70 PI567775B Tong shan niu mao huang 71 PI567777 Tong shan wan dou yuan 72 PI567779A Tong shan xiao hong mao 73 PI567780B Tong shan zheng ji dou 74 PI578490 He nan zao feng No. 1 75 PI587620B Wu jiang ba yue niu mao huang 76 PI592949 Yu dou No. 8 77 PI594393 78 PI603498A 79 PI594398B 80 PI594399C Shui niu pi Lao shu pi 87-32 85-23-9 IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV Henan Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Henan Jiangsu Henan Anhui Shaanxi Anhui Anhui 10.34 9.31 17.54 14.95 10.08 12.35 19.21 19.78 22.27 7.97 15.28 13.59 16.02 12.18 13.69 22.86 17.64 18.37 17.91 15.63 14.45 14.94 21.05 14.40 14.64 19.24 16.75 12.97 10.72 14.47 11.73 16.33 10.32 10.24 12.57 17.58 14.68 17.75 16.69 16.03 40 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV V V V V V V V V V V V V V V V Anhui Anhui Anhui Anhui Hunan Guizhou Guizhou Guizhou Guizhou Jiangsu Jiangsu Henan Anhui Shaanxi Shaanxi Shaanxi Shaanxi Shaanxi Shaanxi Shaanxi Hubei Jiangsu Jiangsu Jiangsu Jiangxi Henan Henan Hubei Jiangsu Jiangsu Shaanxi Shaanxi Shaanxi Shaanxi Shaanxi Henan Henan Henan Henan Jiangsu 22.14 15.61 21.02 18.57 14.10 12.29 8.68 14.93 11.87 19.84 14.48 13.83 12.27 15.09 14.05 7.12 12.98 14.71 5.93 13.13 - 18.22 10.88 15.09 13.29 8.82 12.45 20.64 16.15 22.77 16.35 20.17 14.31 17.86 6.64 14.00 13.23 14.76 14.05 19.82 81 PI594406 25-1 82 PI594409A 86-8-39 83 PI594410 84 PI594413 Liu yue zha Ba yue bai 85 PI594586A Bao jing niu mao huang jia 86 PI594647A Wu zui zao dou No. 3 87 PI594647B Wu zui zao dou No. 3 88 PI594664 E shui zao No. 2 89 PI594682B Liu yue ba 90 PI602500A Tong shan tian er dan 91 PI602501 92 PI602992 Tong shan tian er dan Qin yang shui dou 93 PI594398A 87-32 94 PI603498B 95 PI603502C Lao shu pi Da hei dou 96 PI603505 Da dou 97 PI603511A Wan dou huang 98 PI603511B Wan dou huang 99 PI603527A Hei liao dou 100 PI603531A Zao jiao hu mian dou zi 101 PI603636 Chi huang dou No. 2 102 PI603673G Dong hai bai ta me jia cao 103 PI603678B Feng xian xiao huang dou 104 PI603691 Su qian hong mao zi 105 PI603706B 106 PI103079 Huang dou Shang tsai 107 PI171430 108 PI179825 Paoting 109 PI464933 Su xie No. 1 110 PI561378 Guanyun da hei dun 111 PI567379A Bai gun dou 112 PI567383 Da ke huang dou 113 PI567396C 114 PI567396D 115 PI567413 Lao shu pi Lao shu pi Yi wo feng 116 PI567629B Lu yi xiao zi huang 117 PI567634 Mi yang niu mao huang 118 PI567650D Ru nan huang mao dou 119 PI567657 Tang he huang dou 120 PI567736 Dong hai bai ta me jia cao 41 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight grams/100 seeds V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Henan Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Anhui Anhui Hubei Hubei Hubei 18.26 27.65 25.49 17.67 20.85 29.91 14.59 13.13 13.66 17.84 19.50 10.62 21.28 16.37 16.42 17.92 14.85 10.91 17.70 17.63 12.78 16.98 18.73 19.61 21.78 21.90 24.99 27.32 22.81 22.53 22.00 21.04 20.66 23.87 21.37 20.19 13.76 13.92 15.13 11.72 121 PI567755C Pei xian ping ding huang yi 122 PI567764 Sui ning da qing dou yi 123 PI567766 Sui ning jian ding chun da qing dou 124 PI567779C Tong shan xiao hong mao 125 PI578488A Feng xian sui dao huang 126 PI578491A Hua xian da lu dou 127 PI587577A Wu jiang wu yue niu mao huang 128 PI587577B Wu jiang wu yue niu mao huang 129 PI587577C Wu jiang wu yue niu mao huang 130 PI587577D Wu jiang wu yue niu mao huang 131 PI587577E Wu jiang wu yue niu mao huang 132 PI587577F Wu jiang wu yue niu mao huang 133 PI587577G Wu jiang wu yue niu mao huang 134 PI587585A Kan jiang qiu dao huang jia 135 PI587585C Kan jiang qiu dao huang jia 136 PI587585D Kan jiang qiu dao huang jia 137 PI587588B Tai xing niu mao huang yi 138 PI587589 Tai xing guo yi No. 1 139 PI587598A Ru gao xiao mang dou er 140 PI587600C Ru gao xiao huang dou 141 PI587606B Nan tong huang you guo zi 142 PI587612A Ru dong ba yue bai jia 143 PI587608B Hai men jie jie si 144 PI587619 Yi xing zao huang dou 145 PI587639 Dan tu he dou 146 PI587642A Ru dong zao jia hong 147 PI587643A Nan tong hong pi xiang zi dou 148 PI587643B Nan tong hong pi xiang zi dou 149 PI587645 Nan tong jiang you dou 150 PI587646 Nan tong zong se dou 151 PI587647B Nan tong zhuang yang dou 152 PI587648 Nan tong niu kou hong 153 PI587649 Hai men po pi feng jia 154 PI587650 Hai men hong huang dou jia 155 PI587651 Hai men hong huang dou yi 156 PI587667 Dau huang dou 157 PI587696 Mi feng qiu 158 PI587712A E dou No. 1 159 PI587713 You 70-23 160 PI587714A Jing 802 42 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Jiangsu Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Jiangxi Jiangxi Hunan Hunan Hunan Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou 9.54 17.83 12.32 10.78 12.96 16.39 14.27 6.06 17.15 6.93 15.92 17.84 17.89 11.60 15.15 17.72 26.39 18.90 11.39 19.81 17.83 12.48 12.47 20.64 22.83 12.95 12.47 14.91 16.94 15.00 14.97 19.22 19.08 14.26 18.12 10.60 8.64 10.38 8.31 6.91 161 PI587714B Jing 802 162 PI587716C Tain men da zi huang 163 PI587722 Gu cheng yi shu hou 164 PI587728 Ji mu dou dan zhu 165 PI587734 Song zi yang huang dou 166 PI587752 Xian ning dong huang dou jia 167 PI587753B Xian ning dong huang dou yi 168 PI587773 Tian men xiao gan dou 169 PI587788A Nan zhang hei huang dou 170 PI587805 Tong shan san ji huang pi dou 171 PI587814A 172 PI587814B Ba yue dou Ba yue dou 173 PI587820A En shi ji dan huang 174 PI587820B En shi ji dan huang 175 PI587836 Tong shan qi yue huang 176 PI587846A An lu hong huang dou No. 2 177 PI587848 Wu chang hei dong dou 178 PI592914 1138-2 179 PI594392 Wu he qi tou huang 180 PI594397B 181 PI594400 87-74 87-10 182 PI594418A Ye xi xiao li huang 183 PI594418C Ye xi xiao li huang 184 PI594421 Da du huang dou 185 PI594428 Bai hua qing 186 PI594430D Guang qian qing dou 187 PI594431 Chang pu qing dou 188 PI594432 Zheng nong wan qing dou 189 PI594568A Ba yue huang 190 PI594568B Ba yue huang 191 PI594579 Zhong he tian cheng dou 192 PI594595 Ba yue da huang dou jia 193 PI594602 Bao jing cha huang dou 194 PI594605B 195 PI594623 Qi yue dou Da hei dou 196 PI594627A Xia kou bai shui dou No. 1 197 PI594643 Ba yue huang No. 4 198 PI594653 Mi dou No. 2 199 PI594656 Liu yue dou No. 2 200 PI594657 Liu yue dou No. 3 43 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V V Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guizhou Guangxi Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Jiangsu Hubei Yunnan Yunnan Shaanxi Shaanxi Shaanxi Hubei Hubei Hubei 11.54 9.73 10.40 9.50 13.73 11.46 12.55 10.51 9.91 14.04 8.80 9.23 6.48 9.94 12.22 12.63 12.93 10.97 10.84 13.02 12.07 10.87 8.67 23.44 20.31 18.79 17.23 9.17 10.94 24.12 13.84 12.07 21.44 15.94 17.72 8.00 25.29 9.28 14.86 13.39 201 PI594659A Liu yue ba No. 1 202 PI594660C Liu yue dou No. 1 203 PI594660D Liu yue dou No. 1 204 PI594665 Liu yue mang No. 3 205 PI594667 Jiang kou huang dou No. 4 206 PI594671 Liu yue mang No. 2 207 PI594675 Huang dou No. 1 208 PI594677 Huang dou No. 7 209 PI594678 Huang dou No. 1 210 PI594679 Huang dou No. 3 211 PI594680 Huang dou No. 2 212 PI594681 Huang dou 213 PI594683A Liu yue ba No. 10 214 PI594683B Liu yue ba No. 10 215 PI594698 Huang dou 13 216 PI594700A Qing huang za dou No. 7 217 PI594702 Liu yue bao No. 6 218 PI594704 Qing pi dou No. 2 219 PI594705 Qing pi dou No. 3 220 PI594706 Qing pi dou 221 PI594711A Qing huang za dou No. 3 222 PI594711B Qing huang za dou No. 3 223 PI594719 224 PI594776 Bai zhi dou Bai ri dou 225 PI594792B Xiao lu dou 226 PI594806 Gao jiao huang dou 227 PI594829 Lu dou 228 PI594858A Huang pi dou zi 229 PI594858B Huang pi dou zi 230 PI594864 Yang yan dou 231 PI597470 Nan nong 73-935 232 PI597473 82-24 233 PI599508 234 PI603178 235 PI603507 Bai dou 236 PI603508 237 PI603530C Bai hei dou An hui dou 238 PI603609 Pu qi huang se dou 239 PI603616 69-4 240 PI603624 Liu yue bao 44 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) V V V V V V V VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI Hubei Hubei Hubei Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu 16.15 12.66 16.67 29.39 32.09 23.32 22.31 19.25 13.42 16.59 19.27 12.26 18.54 19.22 10.07 20.64 18.32 21.93 14.34 15.42 14.79 22.51 18.17 16.78 20.85 16.91 18.75 10.76 17.77 19.53 13.92 14.47 16.76 12.09 9.35 19.19 14.36 13.44 15.72 20.36 241 PI603635 Zao niu mao huang 242 PI603637A Qing pi cao huang dou 243 PI603638 Lu pi dou 244 PI603677A Sui ning huang xu da dou 245 PI603677B Sui ning huang xu da dou 246 PI603681A Pei xian xiao bai pi 247 PI603681B Pei xian xiao bai pi 248 PI561379B Sudoi No. 1 249 PI587550B Nan jing da dai dou yi 250 PI587550C Nan jing da dai dou yi 251 PI587557B Li shui zhong zi huang do yi 252 PI587558A Ju rong ziao zi huang 253 PI587563B Dan yang huang xiang dou yi 254 PI587564A Dan yang san san er 255 PI587564B Dan yang san san er 256 PI587570A Li yang dan yang zao No. 1 257 PI587570B Li yang dan yang zao No. 1 258 PI587571 Li yang zao shi ri 259 PI587572A Yi xing zhong ji huang dou yi 260 PI587572B Yi xing zhong ji huang dou yi 261 PI587577I Wu jiang wu yue niu mao huang 262 PI587581 Tai cang huang mao dou jia 263 PI587583B Jiang pu huang da dou yi 264 PI587584 Yi zheng da li huang dou 265 PI587595B Bao ying deng xi feng ding 266 PI587595C Bao ying deng xi feng ding 267 PI587596A Hai an wu zui dou jia No. 2 268 PI587597B Hai an ci yu dou No. 1 269 PI587601A Ru gao ba yue bai jia 270 PI587601B Ru gao ba yue bai jia 271 PI587601C Ru gao ba yue bai jia 272 PI587603A Nan tong ai jiao huang 273 PI587603C Nan tong ai jiao huang 274 PI587603D Nan tong ai jiao huang 275 PI587606C Nan tong huang you guo zi 276 PI587608C Hai men jie jie si 277 PI587612D Ru dong ba yue bai jia 278 PI587614 Ru dong xiao huang ke 279 PI587618A Li yang ba yue huang yi 280 PI587627A Hai men guan qing dou 45 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI Jiangsu Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei 23.08 19.05 19.73 16.32 11.52 18.83 17.63 16.54 12.21 15.71 18.02 15.51 19.00 17.55 16.71 20.26 20.32 15.63 24.53 20.57 10.36 18.59 22.40 14.38 7.77 8.84 10.27 10.61 9.05 12.25 10.96 13.89 11.32 9.96 10.17 12.46 13.89 12.96 15.48 18.96 281 PI587638 Ru dong hei wan huang dou 282 PI587659A 283 PI587659B 284 PI587664A 285 PI587664B 286 PI587666 Qing dou zi Qing dou zi Shan zi bai Shan zi bai Er dao zao 287 PI587668B Hui mei dou 288 PI587669 Zan zi bai 289 PI587670A Liu yue bao 290 PI587673 Ke ban jin 291 PI587676 Qing ke dou 292 PI587679 Da li dou 293 PI587683 Hua mi yan 294 PI587684A Ai jiao huang 295 PI587684B Ai jiao huang 296 PI587686A Xi li huang No. 1 297 PI587686B Xi li huang No. 1 298 PI587689 Xiao li huang 299 PI587693 300 PI587697 Yu shan dou Da qing dou 301 PI587698A Qing pi 302 PI587702 303 PI587704 304 PI587705B Qing pi dou Qing pi dou Qing pi dou 305 PI587719C Xi shui xiao dou 306 PI587721A Gu cheng huang dou 307 PI587721B Gu cheng huang dou 308 PI587721C Gu cheng huang dou 309 PI587723A Gu cheng mian yang wei 310 PI587727 Song zi ci yi zi 311 PI587732 Ying shan ji mu wo 312 PI587733 Da wu ai jiao huang 313 PI587736A Jing zhou dong huang dou 314 PI587736B Jing zhou dong huang dou 315 PI587737 Da wu huang se dou 316 PI587738 Jing huang 22 317 PI587740 Jing huang No. 7 318 PI587742A An lu hong huang dou 319 PI587742C An lu hong huang dou 320 PI587743 An lu niu pi huang dou 46 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) 321 PI587742B An lu hong huang dou 322 PI587749 Jing shan niu mao huang 323 PI587755 Yi chang ba yue huang 324 PI587757B Han chuan wu lu bai 325 PI587761 Ying shan tian e dan 326 PI587764 Han chuan wu lu bai 327 PI587766 Jing 398 328 PI587768 Tong shan da huang dou 329 PI587769 Wu chang zhu po dou 330 PI587774 Xiao gan dou 331 PI587788B Nan zhang hei huang dou 332 PI587797 Yang xin hei da dou 333 PI587800 Ying shan da li huang 334 PI587806B Wu ming 24 yi 335 PI587813 336 PI587814C 337 PI587814G 338 PI587814F Yi duo yun Ba yue dou Ba yue dou Ba yue dou 339 PI587815B Hong mao za dou 340 PI587817 Wu lu bai 341 PI587823 Jing shan qing da dou 342 PI587825B E huang 13 343 PI587826 Da wu qing pi dou No. 2 344 PI587835 Huang dou 345 PI587839A Han chuan fen qing huang dou 346 PI587839B Han chuan fen qing huang dou 347 PI587839C Han chuan fen qing huang dou 348 PI587841A 349 PI587841B Shan zi bai Shan zi bai 350 PI587844A Tong cheng hei se dou 351 PI587844B Tong cheng hei se dou 352 PI587846B An lu hong huang dou No. 2 353 PI587847 Tong shan niu gan dou 354 PI594418E Ye xi xiao li huang 355 PI603517A Lao shu pi 356 PI603522 Gao gan qing 357 PI603539A 358 PI603539B 359 PI603539C Huang dou Huang dou Huang dou 360 PI603611B Wu feng shai lu qing 361 PI603617 65-391 362 PI603618 Tian e dan No. 2 363 PI603702A 364 PI603702B 73-2 73-2 47 VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Anhui Shaanxi Shaanxi Shaanxi Shaanxi Shaanxi Hubei Hubei Hubei Jiangsu Jiangsu 8.86 13.39 17.83 14.83 17.20 13.83 16.64 13.38 12.78 14.77 12.42 8.89 17.94 18.52 16.32 19.92 14.63 15.57 17.84 16.02 18.38 11.76 15.95 11.95 17.08 15.95 15.55 7.17 11.21 18.68 17.32 16.18 15.24 10.72 16.58 19.54 11.82 12.81 14.96 18.44 11.40 10.92 15.31 13.49 Table 2.6. Cont’d No. PI Number Cultivar MG State Seed Weight (grams/100 seeds) 365 PI071564 366 PI171446 - - 367 PI518722 Nan nong 493-1 368 PI567391 Jiang se huang dou 369 PI567410B (Yang huang dou) 370 PI567410C (Yang huang dou) 371 PI587557A Li shui zhong zi huang do yi 372 PI587563A Dan yang huang xiang dou yi 373 PI587563C (Dan yang huang xiang dou yi) 374 PI587565A Dan yang da zi xi dou jia 375 PI587567B (Li yang su huang dou yi) 376 PI587573A Yi xing zhong zi dou yi 377 PI587573B (Yi xing zhong zi dou yi) 378 PI587574A Wu jin bai hua dou 379 PI587583D (Jiang pu huang da dou yi) 380 PI587603B (Nan tong ai jiao huang) 381 PI587622B (Liu he lu dou No. 2) 382 PI587654 Tai xing ma que dou 383 PI587662B (Mi feng qiu) 384 PI587680 Gao jiao huang 385 PI587682B (Da li huang No. 1) 386 PI587687E (Xiao li dou No. 1) 387 PI587691 Hou zi mao 388 PI587692B (Pi wai qing) 389 PI587695 Dong huang dou 390 PI587699 391 PI587701 Qing dou Qing dou 392 PI587731 Yun meng hua ye dou 393 PI587759 Song zi ba yue cha 394 PI587760 Dang yang xiao li dou 395 PI587762 Wu ming 22 396 PI587763 Jing huang 36 397 PI587767A Yun meng bai mao huang dou 398 PI587790B (Mian yang huang feng wo) 399 PI587791 Mian yang ya dong bai 400 PI587815A Hong mao za dou 401 PI587829 E huang No. 9 402 PI587831 Yun an qing huang dou 403 PI587833 Jing men shu hou zi 404 PI587834 Yun an qing pi dou 405 PI587838 Mian yang ji mu dun 406 PI587843 407 PI587844C (Tong cheng hei se dou) 48 VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII Jiangsu Jiangsu Jiangsu Shaanxi Shaanxi Shaanxi Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Jiangsu Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Anhui Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei Hubei 13.52 13.22 15.08 21.83 13.91 15.53 12.80 16.04 19.04 16.75 28.92 13.74 15.63 20.80 18.49 13.61 17.35 19.83 13.60 16.75 18.31 16.49 16.94 21.38 25.16 18.73 21.19 13.97 17.04 19.36 15.58 15.03 14.97 17.21 18.47 17.10 8.93 7.65 13.97 7.47 17.21 19.70 18.08 Table 2.7. List of 208 soybean lines of the Brazilian accessions No. PI Number Cultivar MG Sub-collection Seed Weight (grams/100 seeds) V V V V V V V V VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI 12S-2118 12S-2119 12S-2120 12S-2121 12S-2122 12S-2123 12S-2124 12S-2125 09S-3838 12S-2262 12S-2263 12S-2264 12S-2265 12S-2266 12S-2267 12S-2268 12S-2269 12S-2270 12S-2271 12S-2272 12S-2273 12S-2274 12S-2275 12S-2276 12S-2277 12S-2278 12S-2279 12S-2280 12S-2281 12S-2281 12S-2283 12S-2284 12S-2285 12S-2286 12S-2287 12S-2288 12S-2289 12S-2290 12S-2291 12S-2292 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 PI 628799 BR-2 (Vagem clara) PI 628821 FT-Cometa PI 628854 IAS-2 PI 628878 Pampeira PI 628879 Parana PI 628880 Paranagoiana PI 628910 BR-23 PI 628964 Tropical OT PI 417503 Pioneira PI 628801 PI 628802 PI 628803 BR-4 BR-5 BR-7 PI 628804 BR-8 (Pelotas) PI 628807 BR-13 (Maravilha) PI 628809 BR-16 PI 628812 MG/BR-46 (Conquista) PI 628814 Campos Gerais PI 628816 CEP 12 (Cambara) PI 628817 CEP 16 (Timbo) PI 628819 Coker 136 PI 628820 Decada PI 628828 FT-9 (Inae) PI 628831 FT-13 (Alianca) PI 628837 FT-20 (Jao) PI 628839 FT-Eureka PI 628840 FT-Guaira PI 628841 FT-Manaca PI 628846 IAC-11 PI 628852 Ipagro-21 PI 628856 PI 628858 IAS-5 Invicta PI 628860 Ivora PI 628862 Lancer PI 628867 Ocepar-3 (Primavera) PI 628868 Ocepar-4 (Iguacu) PI 628869 Ocepar-5 (Piquiri) PI 628871 Ocepar-8 PI 628872 Ocepar-9=SS1 PI 628873 Ocepar-10 PI 628874 Ocepar-11 49 10.32 13.59 16.39 15.28 15.12 13.91 17.44 13.81 15.27 17.41 15.66 14.27 13.12 16.05 16.20 13.45 14.13 14.32 15.20 15.28 13.55 15.05 14.74 15.33 11.30 17.88 16.24 11.13 17.41 13.86 15.17 14.65 16.13 18.82 16.87 15.71 14.21 14.59 13.28 14.95 Table. 2.7. Cont’d No. PI Number Cultivar MG Sub-collection Seed Weight (grams/100 seeds) VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VI VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII 12S-2293 12S-2294 12S-2295 12S-2296 12S-2297 12S-2298 12S-2299 12S-2300 12S-2301 12S-2302 12S-2303 12S-2304 12S-2305 12S-2308 12S-2309 12S-2310 12S-2311 12S-2312 12S-2313 12S-2314 12S-2315 04S-1544 04S-1545 04S-1673 12S-2419 12S-2420 12S-2421 12S-2422 12S-2423 12S-2424 12S-2425 12S-2426 12S-2427 12S-2428 12S-2429 12S-2430 12S-2431 12S-2432 04S-144 12S-2434 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 PI 628876 Ocepar-14 PI 628877 Ocepar-18 PI 628881 Paranaiba PI 628882 Perola PI 628883 Planalto PI 628884 Prata PI 628892 Sertaneja PI 628900 IPB-90-77 PI 628901 IPB 204-77 PI 628909 MG BR-22 (Garimpo) PI 628911 BR-24 PI 628912 BR-29 (Londrina) PI 628917 BR-37 PI 628920 CEP-20 (Guajuvira) PI 628923 Embrapa-1 (IAS-5 RC) PI 628924 Embrapa-4 (BR-4 RC) PI 628926 Emgopa-302 PI 628931 FT-1 PI 628949 Ipagro-20 PI 628952 Ocepar-17 PI 628953 Ocepar-20 PI 417496 PI 417497 3802 3837 PI 518756 Centenaria PI 628806 BR-12 PI 628815 CEP 10 PI 628829 FT-10 (Princesa) PI 628830 FT-12 (Nissei) PI 628835 FT-17 (Bandeirantes) PI 628836 FT-18 (Xavante) PI 628838 FT-Abyara PI 628844 IAC-5 PI 628845 PI 628847 IAC-10 IAC-12 PI 628848 A IAC-13 PI 628848 B (IAC-13) PI 628848 C (IAC-13) PI 628849 IAC-14 PI 628850 IAC-100 PI 628851 IAC-Foscarin 31 50 11.57 15.11 14.81 14.30 16.66 12.38 16.63 15.47 13.95 13.77 16.98 14.57 12.56 12.67 15.57 20.64 14.39 12.17 14.52 12.72 17.08 13.24 14.21 8.39 17.13 15.25 13.87 12.42 14.47 17.49 13.52 12.79 11.66 10.50 15.33 11.98 14.08 13.88 8.56 14.64 Table 2.7. Cont’d No. PI Number Cultivar MG Sub-collection Seed Weight (grams/100 seeds) PI 628853 PI 628855 IAS-1 IAS-4 PI 628865 Missoes PI 628866 Ocepar-2 (lapo) PI 628870 Ocepar-6 PI 628875 Ocepar-13 PI 628885 RS-5 (Esmeralda) PI 628886 RS-6 (Guassupi) PI 628887 RS-7 (Jacui) PI 628888 Sant' Ana PI 628890 Sao Carlos PI 628893 PI 628898 Sulina Uniao PI 628908 MS BR-21 (Buriti) PI 628913 BR-30 PI 628914 BA BR-13 PI 628915 MS BR-34 (Empaer 10) PI 628916 PI 628918 BR-36 BR-38 PI 628928 Emgopa-304 (Campeira) PI 628932 FT-2 PI 628936 FT-Estrela PI 628938 FT-Canarana PI 628945 IAC-7 PI 628948 IAC-17 PI 628962 Vila Rica PI 628963 La Suprema PI 628965 UFVITM-1 PI 663948 Embrapa-48* PI 203398 Abura PI 417500 Escura A PI 417501 Kedelle Stb 26 PI 417502 L356 PI 417504 S44/55 PI 628800 BR-3 PI 628805 BR-9 (Savana) PI 628808 BR-14 (Modelo) PI 628810 BR-27 (Cariri) PI 628811 MT/BR-45 (Paiaguas) PI 628813 MG/BR-48 (Garimpo RCH) PI 628822 FT-3 PI 628824 FT-5 (Formosa) PI 628825 FT-6 (Veneza) 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 51 VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII 12S-2435 12S-2438 10S-2052 12S-2440 12S-2441 12S-2442 12S-2443 12S-2444 12S-2445 12S-2446 12S-2447 12S-2448 12S-2449 12S-2450 12S-2451 08S-1316 10S-6586 08S-1317 12S-2455 12S-2456 12S-2457 12S-2458 12S-2459 09S-5358 12S-2461 12S-2462 08S-1319 12S-2464 12S-3023 14S-1742 04S-1906 04S-1907 07S-2477 04S-1908 12S-2581 12S-2582 12S-2583 08S-1359 12S-2585 12S-2586 12S-2587 12S-2588 12S-2589 16.24 13.51 15.64 15.07 14.43 13.76 13.46 15.96 19.90 17.21 15.12 18.46 14.77 13.79 13.87 8.88 9.12 12.86 13.53 13.32 13.71 12.81 9.81 11.91 14.97 14.07 8.55 13.52 13.24 13.58 14.78 7.88 14.67 11.01 17.79 11.24 14.82 14.34 12.96 15.04 14.12 15.15 15.22 Table 2.7. Cont’d PI Number Cultivar MG Sub-collection Seed Weight (grams/100 seeds) PI 628826 FT-7 (Taroba) PI 628834 PI 628842 PI 628843 FT-16 IAC-1 IAC-4 PI 628857 Industrial PI 628859 Ivai PI 628864 Mineira PI 628891 Sao-Luiz PI 628894 PI 628895 PI 628897 PI 628899 Tiaraju UFV-2 UFV-4 Vicoja PI 628902 BR-1 PI 628906 MS BR-19 (Pequi) PI 628919 MT/BR-50 (Parecis) PI 628922 Dourados PI 628925 Embrapa-20 (Doko RC) PI 628927 Emgopa-303 PI 628930 FT-Cristalina PI 628935 FT-Seriema PI 628937 FT-Jatoba PI 628939 FT-Bahia PI 628940 FT-Cristal PI 628941 FT-Iracema PI 628944 PI 628947 IAC-6 IAC-9 PI 628950 IAS-2 (Delta) PI 628951 Numbaira PI 628954 Timbira PI 628958 UFV-7 (Juparana) PI 628960 UFV-9 (Sucupira) PI 628961 UFV-Araguira PI 628966 BR-6 (Nova Bragg) PI 644103 BRS Tiana PI 675650 BRS 283 PI 675651 BRS 284 PI 675665 BRSMG 752S PI 675671 BRSMG 753 C PI 183485 Abura PI 341252 Amerelo Giganti PI 417498 Alianca Preta PI 417499 PI 417505 Aratiba S67/62 VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII VIII IX IX IX IX IX 12S-2590 12S-2591 12S-2592 12S-2593 12S-2594 12S-2595 12S-2596 12S-2597 12S-2598 09S-5356 12S-2600 12S-2601 12S-2602 12S-2603 12S-2604 14S-564 12S-2605 12S-2606 12S-2607 12S-2608 12S-2609 12S-2610 12S-2611 12S-2612 13S-1210 09S-5360 12S-2617 12S-2618 12S-2619 09S-5362 12S-2621 12S-2622 12S-2623 10S-2096 16CR-2 16CR-3 16CR-17 16CR-23 06CR-1015 14CR-1029 06CR-1300 06CR-1302 06CR-1304 52 16.01 13.60 14.75 15.01 15.45 14.71 14.08 14.79 13.01 12.05 13.67 13.07 9.19 15.05 17.09 12.96 14.51 13.06 11.33 11.13 15.07 11.33 12.31 11.65 12.59 11.40 11.32 14.52 10.98 12.10 11.52 13.44 15.13 12.45 17.76 15.56 18.31 23.17 18.68 23.34 41.33 13.13 13.63 No. 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 Table 2.7. Cont’d Cultivar MG Sub-collection Seed Weight (grams/100 seeds) IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX IX X X X X X X X X X X X X X X X 11CR-2222 03CR-339 05CR-367 16CR-439 05CR-606 11CR-2444 11CR-2446 11CR-2448 11CR-2451 06S-3131 06CR-1718 14CR-1216 06CR-1720 05CR-612 14CR-1219 14CE-1220 07CR-227 14CR-1222 08CR-2072 06CR-1660 12S-2613 06CR-1626 14CR-1226 06CR-1630 05CR-620 16CR-19 16CR-20 16CR-4 16CR-5 16CR-6 16CR-7 16CR-8 16CR-11 16CR-12 16CR-13 16CR-14 16CR-15 16CR-16 16CR-18 16CR-21 16CR-22 13.41 20.58 22.25 18.12 21.38 25.48 23.69 22.95 23.58 13.17 21.42 17.45 19.39 18.22 18.30 21.82 16.81 18.92 21.55 19.16 14.93 21.81 16.46 22.06 22.92 16.26 18.30 11.50 18.66 15.75 17.95 19.37 - 20.75 14.40 15.24 21.36 - 16.97 17.84 14.72 18.44 No. 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 PI Number PI 430901 PI 483251 Cristalina PI 483252 Doko PI 483253 Tropical PI 628797 Andrews PI 628823 FT-4 PI 628827 FT-8 (Araucaria) PI 628832 FT-14 (Piracema) PI 628833 PI 628861 FT-15 J-200 PI 628863 LC 72-749 PI 628889 Santa Rosa PI 628896 UFV-3 PI 628903 BR-15 (Mato Grosso) PI 628904 MS BR-17 (Sao Gabriel) PI 628905 MS BR-18 (Guavira) PI 628907 MS BR-20 (Ipe) PI 628929 Emgopa-305 (Caraiba) PI 628933 FT-11 (Alvorada) PI 628934 FT-19 (Macacha) PI 628942 FT-Maracaju PI 628943 PI 628946 IAC-2 IAC-8 PI 628957 UFV-5 PI 628959 UFV-8 (Monte Rico) PI 675667 BRS 7980 PI 675668 BRS 326 PI 675652 BRS Barreiras PI 675653 BRS Camauba PI 675654 BRSGO Chapadoes PI 675655 BRS Corisco PI 675656 BRS Jiripoca PI 675657 BRSGO Luziana PI 675659 BRSMT Pintado PI 675660 BRS Sambaiba PI 675661 BRS Tracaja PI 675662 BRSMG 68 (Vencedora) PI 675663 BRSGO 8360 PI 675664 BRS 313 PI 675666 BRS 361 PI 675669 BRS Perola PI 675670 BRSGO 8660 53 Table 2.8. Analysis of variance for plant height for the 706 lines using PROC ANOVA procedure (SAS 9.4) Sum of Squares Mean Square F Value Pr > F 55007.92 78.03 12.42 <.0001 4433.59 6.28 Source Lines Error DF 705 706 Corrected Total 1411 59441.51 Table 2.9. Analysis of variance for plant height for 60 soybean lines tested on three different pH regimes using PROC MIXED procedure (SAS 9.4) Source Lines pH Lines*pH Error Corrected Total DF Sum of square Mean square F value Pr>F 9066.91 153.68 62.07 <0.0001 2301.43 1150.71 464.80 <0.0001 4821.41 40.86 16.50 <0.0001 445.63 445.63 16635.37 16635.37 59 2 118 180 359 54 Table 2.10. Comparison of means for plant height for 55 surviving lines within the USA accessions used to select the best 20 out of 91 lines Lines 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 PI556727 PI556744 PI556537 PI556612 PI615694 PI556536 PI576154 PI590932 PI583367 PI548987 PI603953 PI556515 PI553047 PI584506 PI615695 PI556564 PI548986 PI556481 PI556584 PI594922 PI617041 PI561211 PI559379 PI647085 PI556825 PI556847 PI597389 PI548835 PI548985 PI642732 PI596540 PI556848 PI654355 PI614702 PI596414 PI619615 PI548698 PI556480 PI556506 PI508267 PI590931 PI556742 PI553041 PI555453 PI576440 PI536009 PI556545 PI572239 PI508266 PI511813 PI556741 PI548988 PI553042 PI531068 PI641156 I 25.90 23.00 22.10 22.00 19.70 19.00 18.60 18.40 15.20 17.50 15.80 17.00 16.30 21.20 17.20 17.90 16.00 19.50 22.70 22.70 16.10 17.60 13.60 20.70 20.00 9.65 19.60 15.30 10.40 10.60 13.60 18.40 18.30 17.80 17.20 16.90 10.50 16.70 16.20 11.90 10.70 15.00 14.60 14.70 14.60 12.20 12.70 12.40 4.30 12.20 12.00 11.70 4.00 8.30 6.50 Plant Height (cm) II 24.20 25.00 25.00 24.50 19.30 18.00 18.20 18.00 20.60 18.20 19.40 18.00 18.60 13.50 17.40 16.50 18.30 14.80 11.40 11.30 17.80 14.40 18.20 10.40 10.20 19.30 9.70 13.60 18.10 17.90 14.30 9.10 9.20 9.00 8.70 8.40 14.50 8.30 8.10 12.10 12.70 7.60 7.40 7.30 7.20 7.50 6.30 6.40 14.30 6.10 6.00 5.80 10.50 4.20 3.20 Mean 25.05 24.00 23.55 23.25 19.50 18.50 18.40 18.20 17.90 17.85 17.60 17.50 17.45 17.35 17.30 17.20 17.15 17.15 17.05 17.00 16.95 16.00 15.90 15.55 15.10 14.48 14.65 14.45 14.25 14.25 13.95 13.75 13.75 13.40 12.95 12.65 12.50 12.50 12.15 12.00 11.70 11.30 11.00 11.00 10.90 9.85 9.50 9.40 9.30 9.15 9.00 8.75 7.25 6.25 4.85 a ** ab abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc bc c ** Means within columns followed by the same letter are not significantly different (LSD, P<0.05) 55 Table 2.11. Comparison of means for plant height for 131 surviving lines within the Chinese accessions used to select the best 20 out of 407 lines Lines Plant Height (cm) Mean Lines Plant Height (cm) II Mean Plant Height (cm) II 26.5 29.8 27.5 19.3 28.6 16.3 21.8 19.5 19.0 20.2 19.5 18.0 18.1 21.0 20.8 17.3 11.2 20.6 17.2 17.4 10.6 10.2 15.6 17.2 16.8 16.7 18.0 18.4 17.1 17.0 6.3 15.0 9.4 14.2 14.6 14.5 9.2 14.2 9.1 9.1 9.1 9.0 8.8 15.3 14.3 8.7 8.7 17.0 10.5 8.6 17.0 15.6 13.2 I 30.4 20.7 18.8 21.8 11.3 23.1 17.0 19.2 18.1 16.5 16.4 17.8 17.5 14.5 14.6 17.8 22.4 12.0 15.3 15.7 21.3 20.4 15.0 13.1 13.4 13.1 11.5 10.7 12.0 12.0 22.5 13.3 18.8 14.0 13.5 13.6 18.4 13.3 18.2 18.2 18.2 18.0 17.7 11.2 12.2 17.5 17.5 9.0 15.3 17.2 8.7 10.1 12.5 II PI567652 9.5 PI567684B 9.7 PI567611 5.8 PI587572B 5.6 PI567413 8.6 PI587614 5.6 PI594568B 8.7 PI567620B 5.6 PI603637A 5.4 PI587692B 9.4 PI587714A 4.9 PI567614C 4.8 PI567379A 4.5 PI587768 4.3 PI567410C 7.20 PI567643 4.10 PI603706B 4.00 PI567646A 3.60 PI567779A 3.60 PI594643 3.55 PI587701 3.70 PI567627B 3.00 PI567684A 2.85 PI594667 0.00 PI587684B 0.00 PI567745 PI072227 PI587728 PI603681B PI567660B PI567650C PI446893 PI567614D PI594653 PI594432 PI603681A PI603673G PI567743 PI567615 PI587689 PI594681 PI103079 PI587713 PI567396C PI594680 PI567777 PI594430D PI567755B PI567677 PI567753C PI561378 PI587714B PI594678 ** Means within columns followed by the same letter are not significantly different (LSD, P<0.05) 11.6 12.80 18.2 12.60 17.0 12.50 8.3 12.45 8.2 12.38 8.2 12.38 12.4 12.20 15.1 12.15 13.3 12.15 14.0 12.15 13.8 12.10 14.0 12.05 12.1 12.05 8.0 12.00 13.3 11.75 7.8 11.70 12.1 11.65 7.7 11.63 7.7 11.55 7.7 11.55 12.5 11.55 11.5 11.50 7.6 11.48 15.4 11.40 13.6 11.40 11.9 11.30 13.5 11.05 7.2 10.88 7.2 10.88 7.3 10.80 12.5 10.50 6.7 10.13 9.0 10.05 6.7 10.05 6.4 9.68 6.4 9.60 6.3 9.45 9.5 9.35 9.4 9.30 6.2 9.23 9.2 9.20 6.1 9.15 6.1 9.08 6.0 9.08 9.8 9.05 6.0 9.00 12.6 9.00 6.0 9.00 6.0 8.85 10.4 8.85 9.8 8.80 9.0 8.75 5.8 8.70 PI567650D PI567623 PI567638 PI587761 PI587577A PI587693 PI587712A PI587800 PI594864 PI603677B PI594660C PI594627A PI594665 PI567650A PI567396D PI567757 PI594679 PI171430 PI567698B PI594431 PI594671 PI567612 PI179825 PI587571 PI587603D PI594657 PI587696 PI594623 PI603702A PI587760 PI587619 PI587684A PI567772 PI603638 PI587659B PI567410B PI567391 PI587757B PI587774 PI587573A PI587813 PI567381A PI587608B PI603677A PI587767A PI587577B PI594660D PI594647A PI532455B PI587695 PI587734 PI594656 PI587603C 28.45 25.25 23.15 20.55 19.95 19.70 19.40 19.35 18.55 18.35 17.95 17.90 17.80 17.75 17.70 17.55 16.80 16.30 16.25 16.55 15.98 15.30 15.30 15.15 15.10 14.90 14.75 14.55 14.55 14.50 14.40 14.15 14.10 14.10 14.05 14.05 13.80 13.75 13.65 13.65 13.65 13.50 13.28 13.25 13.25 13.13 13.13 13.00 12.90 12.90 12.85 12.85 12.85 Lines PI594602 PI594659A PI587683 PI603691 PI587606B PI587743 PI587769 PI594595 PI587763 PI587764 PI594647B PI567780B PI594806 PI594682B PI587766 PI567676A PI587622B PI587620B PI603678B PI587606C PI567736 PI567630B PI567750 PI587618A PI587666 I 7.9 7.6 11.5 11.3 8.2 11.2 8.0 11.1 10.8 6.5 9.8 9.5 8.9 8.6 5.50 8.20 8.00 7.20 7.20 7.10 7.40 6.00 5.70 6.00 6.00 I 14.0 7.0 8.0 16.6 16.5 16.5 12.0 9.2 11.0 10.3 10.4 10.1 12.0 16.0 10.2 15.6 11.2 15.5 15.4 15.4 10.6 11.5 15.3 7.4 9.2 10.7 8.6 14.5 14.5 14.4 8.5 13.5 11.1 13.4 12.9 12.8 12.6 9.2 9.2 12.3 9.2 12.2 12.1 12.1 8.3 12.0 5.4 12.0 11.8 7.3 7.8 8.5 11.6 a** ab abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc Mean 8.70 8.65 8.63 8.48 8.40 8.40 8.35 8.33 8.10 7.95 7.35 7.13 6.68 6.45 6.35 6.15 6.00 5.40 5.40 5.33 5.55 4.50 4.28 3.00 3.00 abc abc abc abc abc abc abc abc bc bc bc bc bc bc bc bc bc bc bc bc bc c c c c 56 Table 2.12. Comparison of means for plant height for 155 surviving lines within the Brazilian accessions used to select the best 20 out of 208 lines Lines Plant Height (cm) I II Mean Plant Height (cm) I II Mean Plant Height (cm) I Mean 7.05 6.95 6.90 6.90 6.90 6.83 6.80 6.75 6.75 6.75 6.68 6.50 6.45 6.45 6.38 6.30 6.30 6.20 6.20 6.15 6.10 6.00 5.78 5.63 5.50 5.50 5.48 5.48 5.40 5.40 5.33 5.25 5.25 5.03 4.95 4.80 4.80 4.73 4.58 4.50 4.50 4.28 3.53 3.30 3.23 3.23 3.23 2.50 2.40 abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc bc bc bc bc bc bc c c 17.00 16.10 14.20 14.10 14.50 13.80 17.60 13.80 13.50 13.50 15.50 13.10 13.30 12.80 15.00 15.20 13.30 13.10 12.70 12.80 13.50 13.10 12.50 12.10 14.50 13.50 12.40 14.50 14.50 12.30 11.90 15.60 12.60 13.30 13.00 12.70 13.30 13.20 13.00 13.50 11.70 13.10 10.70 12.00 12.10 12.20 13.80 11.00 14.10 10.10 10.20 12.30 13.20 PI 675656 PI 675669 PI 628828 PI 628873 PI 628842 PI 675671 PI 675659 PI 628869 PI 628965 PI 628962 PI 675667 PI 628929 PI 628880 PI 628870 PI 675654 PI 628871 PI 628910 PI 628894 PI 628860 PI 675661 PI 628812 PI 628839 PI 628809 PI 628862 PI 628872 PI 341252 PI 628960 PI 628811 PI 628831 PI 628885 PI 675662 PI 628876 PI 628895 PI 628905 PI 628947 PI 628944 PI 628892 PI 628946 PI 628852 PI 628918 PI 628868 PI 628803 PI 628933 PI 628897 PI 628925 PI 675663 PI 628866 PI 663948 PI 628846 PI 628854 PI 417502 PI 675666 PI 628819 ** Means within columns followed by the same letter are not significantly different (LSD, P<0.05) 6.60 9.90 6.60 9.90 7.10 9.80 9.50 9.80 9.10 9.80 9.00 9.75 7.00 9.75 6.40 9.75 9.00 9.70 6.80 9.70 9.00 9.70 7.10 9.65 8.20 9.60 6.50 9.50 9.20 9.45 9.10 9.30 8.50 9.25 6.15 9.23 8.20 9.20 9.10 9.10 8.50 9.05 8.60 9.05 6.00 9.00 8.50 8.95 8.10 8.95 5.90 8.85 8.30 8.75 7.20 8.60 6.00 8.55 7.40 8.50 6.50 8.45 7.50 8.45 7.30 8.40 7.00 8.40 7.20 8.35 7.10 8.15 7.10 8.15 5.10 8.15 5.30 8.10 5.40 8.10 7.50 8.05 7.00 8.00 5.30 7.95 7.10 7.90 6.40 7.90 4.10 7.75 5.15 7.73 7.60 7.70 7.60 7.60 4.80 7.20 7.40 7.70 5.90 7.25 7.00 7.10 II 7.10 7.00 7.60 6.30 9.20 4.60 7.80 6.00 7.70 6.10 9.10 4.55 8.00 5.60 9.20 4.30 9.00 4.50 7.50 6.00 8.90 4.45 8.50 4.50 8.60 4.30 11.6 1.30 8.50 4.25 8.40 4.20 6.40 6.20 7.00 5.40 8.40 4.00 8.20 4.10 7.50 4.70 8.00 4.00 7.70 3.85 7.50 3.75 6.30 4.70 5.50 5.50 7.30 3.65 7.30 3.65 7.20 3.60 7.20 3.60 7.10 3.55 7.00 3.50 7.00 3.50 6.70 3.35 5.80 4.10 6.40 3.20 6.40 3.20 6.30 3.15 6.10 3.05 4.70 4.30 6.00 3.00 5.70 2.85 4.70 2.35 3.50 3.10 4.30 2.15 4.30 2.15 4.30 2.15 5.00 0.00 3.20 1.60 Lines PI 628841 PI 628927 PI 628817 PI 628858 PI 628808 PI 628874 PI 628922 PI 417499 PI 628877 PI 628826 PI 675650 PI 628863 PI 628824 PI 628901 PI 628957 PI 628825 PI 675668 PI 628932 PI 628915 PI 628834 PI 628890 PI 628942 PI 628883 PI 628887 PI 628916 PI 675664 PI 628816 PI 628837 PI 628909 PI 628937 PI 628867 PI 628936 PI 628864 PI 628951 PI 628859 PI 628886 PI 628966 PI 483253 PI 628939 PI 483251 PI 628807 PI 628940 PI 675655 PI 628879 PI 628913 PI 628822 PI 628814 PI 628893 PI 628875 PI 628802 PI 628857 PI 675665 PI 628899 16.20 14.55 14.10 13.90 13.75 13.70 13.55 13.50 13.30 13.05 12.95 12.85 12.80 12.80 12.80 12.75 12.70 12.70 12.65 12.65 12.60 12.60 12.35 12.10 12.05 12.00 11.85 11.80 11.75 11.50 11.45 11.40 11.35 11.35 11.30 11.20 11.20 11.15 11.05 10.90 10.75 10.55 10.55 10.50 10.50 10.40 10.35 10.35 10.20 10.00 9.95 9.95 9.90 Lines PI 628865 PI 628930 PI 628914 PI 628963 PI 628954 PI 628928 PI 628904 PI 628855 PI 628813 PI 628843 PI 628934 PI 628964 PI 628961 PI 628943 PI 628878 PI 203398 PI 628941 PI 628945 PI 628950 PI 628840 PI 628906 PI 675660 PI 628908 PI 644103 PI 628884 PI 628889 PI 628820 PI 628902 PI 628799 PI 628800 PI 628900 PI 628948 PI 417505 PI 628907 PI 628935 PI 628856 PI 628832 PI 675653 PI 628896 PI 675652 PI 483252 PI 628833 PI 417504 PI 628881 PI 628882 PI 417501 PI 675651 PI 628853 PI 628797 13.20 13.20 12.50 10.10 10.50 10.50 12.50 13.10 10.40 12.60 10.40 12.20 11.00 12.50 9.70 9.50 10.00 12.30 10.20 9.10 9.60 9.50 12.00 9.40 9.80 11.80 9.20 10.00 11.10 9.60 10.40 9.40 9.50 9.80 9.50 9.20 9.20 11.20 10.90 10.80 8.60 9.00 10.60 8.70 9.40 11.40 10.30 7.80 7.60 9.60 8.00 8.60 7.20 15.40 13.00 14.00 13.70 13.00 13.60 9.50 13.20 13.10 12.60 10.40 12.60 12.30 12.80 10.60 10.30 12.10 12.30 12.60 12.50 11.70 12.10 12.20 12.10 9.60 10.50 11.30 9.10 9.00 10.70 11.00 7.20 10.10 9.40 9.60 9.70 9.10 9.10 9.10 8.30 9.80 8.00 10.40 9.00 8.90 8.60 6.90 9.70 6.30 9.90 9.70 7.60 6.60 a** ab ab abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc abc 57 Table 2.13. Comparison of means for plant height for 60 lines grown on three pH regimes Lines PI628871 PI628962 PI567611 PI556744 PI556727 PI615695 PI628925 PI567779A PI556537 PI628842 PI594922 PI556515 PI590932 PI628929 PI628880 PI567410C PI567643 PI556612 PI675661 PI556564 PI628828 PI628848C PI628894 PI628812 PI628809 PI628880 PI587768 PI576154 PI567614C PI587614 PI556536 PI628885 PI556481 PI594643 PI584506 PI628952 PI567413 PI675669 PI587714A PI567652 PI583367 PI567620B PI615694 * PI556584 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 48 44 45 pH 4.5 22.10 a ** 21.40 a 20.60 ab 20.30 ab 20.10 ab 18.20 b 18.00 b 16.90 c 16.60 c 15.00 cd 14.60 cd 13.30 def 12.20 efg 12.00 efg 11.90 efg fghi 11.10 10.80 fghi 9.70 ghij 7.90 0.00 jk 21.60 a 21.10 ab 20.90 ab 20.70 ab 20.60 ab 20.10 ab 15.90 cd 12.40 efg fgh 11.30 11.10 fghi 9.50 ghij 9.00 ijk 8.80 hij 8.30 ijk ijk 8.20 ijk 8.10 jkl 7.90 7.10 jkl 6.60 jkl 5.50 kl 4.90 0.00 0.00 0.00 l Plant Height (cm) pH 5.0 12.80 bc 13.50 b 19.50 a 0.00 9.40 de 11.70 bc 9.70 de 9.90 cde 9.10 de 10.80 bcd 9.40 de 9.10 de 10.10 cde 8.90 de 11.20 bcd 10.90 bcd 8.30 de 7.10 e 13.20 b 10.10 cde 0.00 0.00 0.00 0.00 0.00 7.50 e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9.40 de 0.00 0.00 9.30 de 0.00 0.00 pH 5.5 10.60 a 12.80 a 12.50 a 0.00 9.40 bc 11.90 a 13.60 a 10.10 b 12.50 a 9.90 b 12.90 a 9.10 bc 11.90 a 8.70 bc 10.10 b 9.40 bc 10.20 b 8.50 bc 11.00 a 10.60 a 0.00 0.00 0.00 0.00 0.00 7.60 bc 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.80 c 10.00 b ** Means within columns followed by the same letter are not significantly different (LSD, P<0.05) 58 Table 2.14. Comparison of means for root length for 60 lines grown on three pH regimes Lines PI556727 PI567611 PI615695 PI556744 PI628962 PI567779A PI628925 PI628929 PI567410C PI594922 PI556537 PI628842 PI556515 PI628871 PI567643 PI590932 PI628880 PI556612 PI675661 PI556564 PI628828 PI628848C PI628809 PI628812 PI628894 PI567614C PI628880 PI567413 PI675669 PI628885 PI628952 PI583367 PI584506 PI576154 PI556481 PI587768 PI556536 PI587714A PI587614 PI594643 PI567652 PI567620B PI615694 * PI556584 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 pH 4.5 8.05 a ** 7.43 ab 6.90 abc 6.30 bc 5.88 d 5.50 de 5.18 defg 4.58 d-i 4.43 e-k 4.38 e-k 4.35 e-l 4.25 e-l 4.18 f-l 4.10 f-l 3.63 g-m 3.60 h-m 3.30 i-m 3.15 k-n 1.70 N 0.00 6.80 abc 5.90 cd 5.35 def 4.85 d-h 4.53 e-j 4.35 e-l 4.00 g-l i-m 3.43 3.23 j-m 3.18 k-n lmn 2.80 2.75 lmn 2.60 mn 2.53 mn 2.43 mn 2.40 mn 2.38 mn 2.35 mn 2.33 mn 2.33 mn 2.05 n 0.00 0.00 0.00 Root Length (cm) pH 5.0 2.15 c 3.33 b 2.10 c 0.00 2.68 bc 2.40 bc 2.33 bc 2.10 c 2.10 c 2.00 c 1.80 c 2.33 bc 2.08 c 3.80 a 2.48 bc 2.00 c 2.30 bc 1.85 c 2.65 bc 2.85 bc 0.00 0.00 0.00 0.00 0.00 0.00 1.88 c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.93 c 0.00 0.00 0.00 1.85 c 0.00 0.00 pH 5.5 2.05 ab 0.00 1.98 ab 2.50 ab 2.35 ab 2.30 ab 2.65 a 2.00 ab 2.05 ab 1.98 ab 2.80 a 1.98 ab 2.23 ab 1.98 ab 2.20 ab 1.70 ab 2.00 ab 2.30 ab 1.98 ab 2.65 a 0.00 0.00 0.00 0.00 0.00 0.00 1.70 ab 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.28 b 1.73 ab ** Means within columns followed by the same letter are not significantly different (LSD, P<0.05) 59 20 selected lines Figure 2.1. Means of plant height in 55 surviving lines (60.4% of a total 91 lines) within the USA accessions at 35 days after planting 60 20 selected lines Figure 2.2. Means of plant height in 131 surviving lines (32.2% of total 407 lines) within Chinese accessions at 35 days after planting 61 20 selected lines Figure 2.3. Means of plant height in 155 surviving lines (74.5% of total 208 lines) within Brazilian accessions at 35 days after planting 62 Figure 2.4. Means of plant height in 39 surviving lines (65% of total 60 lines) grown on pH 4.5 at 35 days after planting (the second selection phase) 63 Figure 2.5. Means of plant height in 22 surviving lines (37% of total 60 lines) grown on pH 5.0 at 35 days after planting (the second selection phase) 64 Figure 2.6. Means of plant height in 22 surviving lines (37% of total 60 lines) grown on pH 5.5 at 35 days after planting (the second selection phase) 65 Figure 2.7. Means of root length in 44 surviving lines at pH 4.5, 5.0, and 5.5 (the second selection phase) 66 REFERENCES 67 REFERENCES Adie M.M. and Krisnawati A. 2016. Identification of soybean genotypes adaptive and productive to acid soil agro-ecosystem. Biodiversitas: Vol. 17, No. 2. Pages: 565-570. ISSN: 1412- 033X. DOI: 10.13057/biodiv/d17022 Arsyad D.M., Adie M.M., Kuswantoro H. 2013. Soybean varieties breeding on specific of agroecology in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 205-228. In Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/03/dele_9.darman-1.pdf Bernardo R. 2010. Essentials of Plant Breeding. ISBN 978-0-9720724-1-0 Published July 2010 Board, J E. 1991. Response of determinate soybean cultivars to low pH soils. Louisiana State University Agricultural Experiment Station Reports. 349. Link: http://digitalcommons.lsu.edu/agexp/349 Caires E.F., Garbuio F.J., Churka S., Barth G., Correa J.C.L. 2008. Effects of soil acidity amelioration by surface liming on no-till corn, soybean, and wheat root growth and yield. Europ. J. Agronomy 28 (2008) 57–64. doi:10.1016/j.eja.2007.05.002 Carter, T.E., Nelson, R.L., Sneller, C.H., Cui, Z. 2003. Genetic diversity in soybean in Soybeans: improvement, production, and uses. Third edition. American Society of Agronomy, inc., Crop Science Society of America, inc., Soil Science Society of America, inc. 2004. ISBN: 978-0-89118-154-5 Chaerani, Hidayatun N., Utami D.W. 2011. Genetic Diversity of 50 Soybean Accessions Based on Ten Microsatellite Markers. AgroBiogen Journal 7(2):96-105. Link: http://ejurnal.litbang.pertanian.go.id/index.php/ja/article/viewFile/3775/3124 Ginting and Tastra. 2013. Quality standard of soybeans seed in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 444-463. Link: http://balitkabi.litbang.pertanian.go.id/publikasi/monograf/kedelai-teknik-produksi- dan-pengembangan/[in Bahasa Indonesia] Handayani L., Rauf A., Rahmawaty, Supriana T. 2018. The strategy of sustainable soybean development to increase soybean needs in North Sumatera. International Conference on Agriculture, Environment, and Food Security. IOP Conf. Series: Earth and Environmental Science 122 (2018) 012018. doi :10.1088/1755-1315/122/1/012018 68 Havlin J.L., Tisdale S.L., Nelson W.L., Beaton J.D. 2014. Soil fertility and fertilizers: an ntroduction to nutrient management. Eight editions. Pearson education Inc. Upper Saddle River, N.J: Prentice Hall. 503 p. ISBN: 978-81-203-4868-4 IAARD. 2017. Description of soybean varieties released in 1918-2016. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/09/kedelai.pdf Ibrahim S.E., Han W.Y., Baek I.Y., Cho G.R. 2017. Evaluating soybean germplasm for agronomic performance under irrigated cropping environment in Sudan. The Jpurnal of Korean Sicoety of International Agriculture. Vil. 29(4). Pages: 415~420. ISSN 2287-8165. https://doi.org/10.12719/KSIA.2017.29.4.415 Joris H.A.W., Caires E.F., Bini A.R., Scharr D.A., Haliski A. 2013. Effects of soil acidity and water stress on corn and soybean performance under a no-till system. Plant Soil (2013) 365:409–424. DOI 10.1007/s11104-012-1413-2 Kidd P.S. and Proctor J. 2001. Why plants grow poorly on very acid soils: are ecologists missing the obvious? Journal of Experimental Botany. Vol. 52. No. 357. Page: 791-799. Lersten N.R. and Carlson J.B. 2004. Vegetative morphology in Soybeans: improvement, production, and uses. Agronomy Np. 16. Third Edition. Page 15-57. ISBN: 0-89118-154-7 Lyamuremye, F., Dick, R. P., Baham, J. 1996. Organic amendments and phosphorus dynamics in phosphorus chemistry and sorption. Soil Science 161(7):426-435. Ministry of Agriculture Republic of Indonesia. 2015. Strategic plan on 2015-2019 period. Link: http://www1.pertanian.go.id/file/RENSTRA_2015-2019.pdf Mulyani A., Rachman A., Dairah A. 2009. The spread of acidic-soil: potential and availability for agricultural development in Rock-phosphate: utilization of rock-phosphate as phosphate nutrient source. Pgs: 25-46. Pagani A. 2011. Soil pH and lime management for corn and soybean. Dissertation. Iowa State University. Ames, Iowa Pedersen P., and Licht M. 2014. Soybean growth and development. Extension and outreach of Iowa State University. PM 1945. Reviewed July 2014.28 p. Link: www.extension.iastate.edu Peterson J.C. 1982. Effects of pH upon nutrient availability in a commercial soilless root medium utilized for floral crop production. Ornamental Plants- -1982: a summary of research. Research circular 268. Ohio Agricultural Research and Development Center. Wooster, Ohio. 69 Rao V.R. and Hodgkin T. 2002. Genetic diversity and conservation and utilization of plant genetic resources. Plant Cell, Tissue and Organ Culture 68: 1–19, 2002. Robson A.D. 1989. Soil acidity and plant growth. Harcourt Brace Javanovich Publishers. Academic Press Australia. 30-52 Smidmore St. Marrickville, NSW. ISBN: 0-12-433312-5 Rochayati and Dariah. 2012. Acidic dry-land development: opportunities and challenges in Dry- land agriculture prospect in supporting food security. Indonesian Agency for Agricultural Research and Development (IAARD). Jakarta. pg. 187-206 Sudaryanto and Swastika. 2007. The Economic of soybean in Indonesia in in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 1-27 Sumarno and Adie M.M. 2010. The development strategies of soybean production towards sustainable of food self-sufficiency. Journal of Iptek Tanaman Pangan. Vol. 5 no. 1: 49-63. [in Bahasa Indonesia] Supadi. 2010. Impact of the sustained soybean import on food security. Journal of agriculture policy analysis. Vol 7, No. 1: 87-102 Syuaib, M.F. 2016. Sustainable agriculture in Indonesia: Facts and challenges to keep growing in harmony with environment. AgricEngInt. Vol. 18, No. 2. CIGR Journal Open access at http://www.cigrjournal.org Trakoonyingcharoen P., Kheoruenromne I., Suddhiprakarn A., Gilkes R.J. 2005. Phosphate sorption by Thai red Oxixols and red Ultisols. Soil science. Vol 170 No. 9: 716-725. USDA, 2015. Legume seed inoculation. Plant materials technical notes number: TX-PM-15-01. United States Department of Agriculture-Natural Resource Conservation Service. Link: http://nrcs.usda.gov/internet/FSE PLANTMATERIALS/publications/etpmctn12525.pdf Whitney A.D. 1998. Soil Salinity. Recommended Chemical Soil Test Procedures for the North Central Region. North Central Regional Research Publication No. 221 (Revised). Link: https://www.canr.msu.edu/uploads/234/68557/Rec_Chem_Soil_Test_Proce55c.pdf Widiatmaka, Ambarwulan W., Setiawan Y., Walter C. 2016. Assessing the suitability and availability of land for agriculture in Tuban Regency, East Java, Indonesia. Applied and Environmental Soil Science Volume 2016, Article ID 7302148, 13 pages. http://dx.doi.org/10.1155/2016/7302148 70 CHAPTER 3. EVALUATION OF A SELECTED SET OF SOYBEAN LINES FOR TOLERANCE TO ALUMINUM TOXICITY Abstract Efforts to increase soybean production in Indonesia have not been successful due to two main factors: limited availability of high-yielding varieties, and limited availability of suitable land to increase soybean production due to the best available land being used for rice and corn. The land available for expanding soybean production in Indonesia has acidic Ultisols soils. Plants grown in acidic soils often face aluminum toxicity as Al3+ becomes readily available for uptake when pH is low. In the previous study, we had selected 20 germplasm accessions that performed well on Peat moss, an acidic growth medium. However, Peat moss does not contain aluminum (Al), hence, we were unable to test the response of the 20 selected lines to aluminum toxicity. To address this limitation, we conducted a greenhouse study where the previously selected 20 soybean lines were subjected to two levels of Al; 0.0% and 5% Al (by weight). Root length, number of root nodules, and plant height were taken as the dependent variables 35 days after planting, as the criteria for determining germplasm that best tolerates Al toxicity. The data collected were analyzed using ANOVA and LSD. All 20 selected lines survived and grew well at the 5% Al treatment. The measured variables were significantly different at P < 0.0001. Plant height and root length of the 20 lines were higher in the medium with 5% Al compared to the control with 0.0% aluminum. Of the 20 lines tested, PI628871 accession had the longest root length and PI567643 accession had the highest plant height. When comparing the initial and final pH levels of the growth medium, we observed a positive effect of adding Al to the growth medium as it increased the pH of the medium from an initial pH of 4.30 to a final pH of 5.23 - 5.34. The results indicated that all of the previously selected 20 lines would be tolerant to soils 71 with low pH and Al3+ levels up to 5% by weight and could perform well under Indonesian acidic soils. Introduction The availability of soybean as an important and affordable protein source for people of Indonesia has placed soybean as the third most important food crop. In order to meet food needs through domestic production, the Indonesian government has implemented various programs from plant breeding to soil fertility improvement for decades (Sumarno and Adie, 2010). However, these efforts failed to significantly increase soybean production in the country due to two main factors: limitation in the availability of high-yielding varieties, and limited land availability for soybean farming due to the competition of land-used for other remunerative crops such as rice and corn. Increasing soybean yield through cultivar development is widely used by many countries. High-yielding soybean varieties have contributed to a 30% to 50% increase in production (Specht et al., 1999; Surahman et al., 2012; Burton and Miranda, 2013). As such, plant breeding is critical for increasing food production in many countries including Indonesia. In Indonesia, while there is a great need to develop soybean varieties that perform well under different agro-ecologies (Arsyad et al., 2013), the major bottleneck for developing new varieties has been the limited access to germplasm resources. The soybean breeding programs in Indonesia was only able to release a total of nine varieties from 1918 - 1980 and this was achieved by crosses made between just two sources of soybean lines originating from Taiwan together with limited local accessions (IAARD, 2017). Introduction of soybean germplasm accessions to Indonesia from other countries and regions around the world that successfully grow soybeans could assist in enhancing the efficiency of the breeding program in the country. 72 In the early 1980s, the soybean breeding program in Indonesia underwent restructuring with an objective of enhancing the efficiency of breeding activities. To aid this effort, the government provided support to obtain soybean accessions from Thailand, the Philippines, Columbia, Nigeria, Taiwan, and USA. Furthermore, there was an expansion of the areas allocated to growing soybean, and programs were introduced to focus on improving soil fertility through calcification and fertilization (Sumarno and Adie, 2010; Arsyad, 2013; IAARD, 2017). As a result, by 2016, the Ministry of Agriculture of the Republic of Indonesia was able to release 85 soybean varieties. However, many of the newly released varieties did not meet the market demand for large- seeds. Moreover, the new land area that was allocated to soybean development contained acidic soils, which was not favorable for the newly developed varieties that were developed and tested under different conditions. Therefore, our objective is to complement the Indonesian government’s efforts by selecting better adapted soybean germplasm that are tolerant to acidic soils so that they can be used in the newly allocated land to increase production. Indonesia has a total of 102.8 million ha of low pH/acid soils – this is as much as 69.46% of total dry-land that is available for crop production. These acid soils are dominated by Ultisols, Oxisols, and Inceptisols which have a pH of 5.30 in some areas, however, many regions have pH 4.00 or lower (Nurlaeny et al., 1996; Mulyani et al., 2009; Rochayati and Dariah, 2012; Martinsen et al., 2015; Cornelissen et al., 2018). Given this pH range, these soils are considered to be infertile with low soil organic matter (SOM) content and hence, low water holding capacity, making the soil susceptible to erosion (Yulnafatmawita et al., 2014). Ultisols and other acid soils are not suitable for many crops like soybean because they contain low levels of nutrients and are prone to high metal toxicity (Bojorquez-Quintal et al., 2017; Santore et al., 2018). As a highly weathered soil, Ultisols often face a deficit of certain vital 73 nutrients such as phosphorous (P), Magnesium (Mg), and Calcium (Ca) (Fageria et al., 1988). While nutrient deficiencies may cause yield reduction, it can often be addressed through the application of appropriate fertilizer as needed. However, metal toxicity such as Aluminum (Al) toxicity is an issue that is more difficult to address in Ultisols. There is a strong correlation between pH and the solubility of Al in soils (Santore et al., 2018); thus, soil pH can be used as an appropriate variable to discover the exchangeable Al (Havlin et al., 2014). Aluminum is soluble in low pH; especially when pH drops to less than 5.5 and will precipitate as the soil pH increases above that level (Santore et al., 2018). The toxicity of Al to the plant occurs when the soil pH level is between 3.0 – 5.0 where Al3+, the most toxic form of Al, is released into the soil (Panda et al., 2009; Alleoni et al., 2010; Sposito, 2016). Aluminum could interfere plant growth in acidic soils (Panda et al., 2009; Bojórquez- Quintal et al., 2017; Rahman et al., 2018). Acidic soil in Indonesia consists of 48% - 89% of saturated Al with a range of 0.1 - > 4.0 cmol/kg available for plants to absorb (Subardja, 2007). The existence of Al as a toxic metal in the soil has become a central issue in crop production and is a significant barrier that affects plant growth and yield (Foy and Fleming, 1978; Alleoni et al., 2010; Krstic and Djalovic, 2012; Rengel et al., 2015; Rahman et al., 2018). The first target of Al toxicity on a plant is the root. Aluminum will hamper root growth and induce the plant to be having short and thick roots which reduce the plant’s ability to take up water and nutrients from the soil solution (Board and Caldwell, 1991; Alleoni et al., 2010; Liang et al., 2013). Peat moss, a widely used growing medium for greenhouse studies, is an excellent medium to select germplasm tolerant to Al toxicity in acidic soils. The pH of the peat moss growth medium ranges between 3.0 – 6.0 (Mofidpoor, 2007) and it consists of low nutrients (Will and Faust, 2010). There are also several advantages to using peat moss as a growth medium including its’ high-water 74 holding capacity and the cation exchange capacity (CEC). These two factors alone would ensure that the medium provides adequate moisture around the plant roots. Peat moss also consists of few pathogens and weed seeds compared to other media used for growing plants (Mofidpoor, 2007; Will and Faust, 2010; Robbins, 2018). Both cellulose and lignin are responsible for the structure of peat moss (Coupal and Lalancette, 1976). The characteristics of the peat moss growing medium are ideal for use in experiments related to evaluating nutrient deficiencies or the effects of metal toxicity in plants. However, peat moss does not contain aluminum, which is needed in this study for evaluating the response of selected soybean lines to acidic soils where Al3+ becomes readily available. Therefore, it is necessary to add aluminum to the medium in specific amounts as needed for the experiments to determine the response of selected lines. We had previously selected 20 soybean lines that are tolerant to acidic soils out of 706 lines obtained from USA, China and Brazil (detailed in Chapter 2). Provided we are selecting soybean accessions obtained from the USDA-NSRC based on their ability to withstand the acidic soils available to expand production in Indonesia; it is critical that we also observe how tolerant our selected lines are to Al toxicity. Therefore, the purpose of this study was to evaluate the 20 selected lines for tolerance to aluminum toxicity so that the best performing genotypes would have better adaptation to naturally acidic Indonesian soils. This study would thus provide useful information on how each selected line responds to a certain level of Al before they are used in field evaluations in Indonesia. Materials and Methods We used a completely randomized experimental design (CRD) with two replications in this greenhouse study to evaluate the response of the 20 selected soybean lines to aluminum (Al) 75 toxicity. The total number of the experimental units was 80, obtained from 20 soybean lines x 2 Al levels x 2 replications. All units were placed randomly on one bench in the greenhouse at Michigan State University. Plant material The plant material selected for the study are the 20 soybean accessions (out of the original 706 accessions obtained from USDA-NSRC) that best performed in a medium of Peat moss at pH levels of 4.5 to 5.5 (detailed in Chapter 2). The lines included in the experiment were: PI628871, PI628962, PI567611, PI556744, PI556727, PI615695, PI628925, PI567779A, PI556537, PI628842, PI594922, PI556515, PI590932, PI628929, PI628880, PI567410C, PI567643, PI556612, PI675661, and PI556564. Potting media In this experiment, we wanted to determine the effect of added aluminum on the growth of soybean lines at 5% level (by weight) in comparison to how the lines perform under 0% aluminum (the control). For the growth media with 0% Al, we used the Peat moss media without the addition of any Al - a treatment designed to show only the effect of low pH on plant growth. We selected to test the effect of Al on plant growth at 5% level because we assume that as much as 4% of Al would be bound to CEC sites and another 1% of Al to be bioavailable to the plants. To prepare the growth medium, we added a readily soluble form of Al to the media two days after raising the pH of the peat moss media. Given that Peat moss has a much lower initial pH level of 3.5 than desirable for our growth medium, as an initial step, we first raised the pH level of the growing medium to a pH of 4.5 by adding sodium hydroxide (NaOH) as described in Chapter 2. Sodium hydroxide was 76 allowed to mix with the Peat moss media for two days after mixing to allow it to raise the pH to the desired level of 4.5. The pH of the media was measured using a digital pH meter available at the Michigan State University Soil Laboratory. Adding Al to the media was done after ensuring the growing medium had the desired pH level of 4.5. The source of Al used in this study was Aluminum hydroxide (Al(OH)3), in powder form, which was added to the medium following the treatment of 5% of the medium by weight. The peat moss weight for each pot was 100 grams; hence, the amount of aluminum hydroxide added to each pot was five ± 0.05 grams. The number of experimental units with Al treatment was 40 pots. Therefore, the total amount of aluminum hydroxide needed in this study was 200 grams ± 2.0 grams. In order to have an even mixture, the media was stirred gently in a small box and left for a full day before being used as a planting medium for the experiment. Planting Before planting the selected soybean lines in the prepared soil medium, we used a seed treatment of Bradyrhizobium japonicum (Wrigth et al., 2013) as an inoculant. This treatment was done 15-20 minutes before planting the seed. The amount of inoculant used was 0.4 grams per 100 grams of soybean seeds (USDA, 2015) mixed with a small amount of water to ensure the attachment of the inoculant to the surface of the seeds. This seed treatment is used by soybean farmers in Indonesia. Since it is critical to ensure the medium has sufficient moisture to support seed germination, we added an adequate amount of distilled water to the growth medium until it was moist but not too wet. Moisture was also crucial for the aluminum ions to be available for uptake by plants. We used distilled water in this study to ensure the pH level is maintained at a desirable level and would not affect the treatment. 77 All seeds of the 20 selected soybean lines were planted a day after the mixing of Al(OH)3 to the growth medium at 2.5 cm below the surface. Planting was done after all seeds were treated with the inoculant with three seeds per pot. Other than the seed inoculant and aluminum, no fertilizer or treatments were given to the plants. The plants were watered daily using distilled water to maintain soil moisture. Variables and data analysis We determined the effect of aluminum on plant growth by measuring plant root and shoot growth (Delhaize and Ryan, 1995; Bloom and Erich, 1996; Rout G. et al. 2001; Yang et al., 2013). We measured root length and number of root nodules of each plant at the end of the study or 35 days after planting, along with the plant height, which was measured every seven days. We used the Proc GLM procedure (SAS, 2012) to analyze the observed data and the Fisher’s Protected Least Significant Differences (LSD) at a 5% significance level to test the significant differences among treatments based on the results of the analysis of variance (ANOVA). Results and Discussion We found significant differences among lines and aluminum levels using the analysis of variance test at P < 0.0001 (Table 3.1). These differences indicate that each line has a different ability to grow and adapt to the given growing medium and aluminum treatment. The interaction between lines and aluminum treatments was also found to be significantly different. Therefore, we conducted a multiple comparisons test using LSD method to determine differences between treatments. 78 The results of the LSD test for root length is presented in Table 3.2. The root length of 20 selected lines grown in the medium with 0% aluminum ranged from 5.88 cm to 11.70 cm, with PI567779A having the longest root length and significantly different from five other lines. All of the lines were able to grow at the given pH level of 4.5 with different lengths of roots. However, the root length of all the 20 selected lines increased significantly between 23.3% to 218.4% when treated with 5% Al. The highest increase in root length was in PI675661, with a 218% increase compared to the control. The roots of this line grew even longer than PI567779A, which had the longest roots at 0% Al, and the increase was only 38.5% after treatment with 5% aluminum. Based on root length, line number PI628871 had the longest root length when treated with 5% aluminum, and it was significantly different from nine other lines with the same treatment. The plant height of all the 20 tested lines is presented in Table 3.3 and Al influence on changes in plant height from day 7 to day 35 can be seen in Figure 3.1. At 0% of Al, plant height ranged from 9.75 cm to 19.08 cm, with line number PI675661 as the shortest plant and PI556537 being the tallest and significantly different from six lines. However, 18 out of 20 lines had an increased plant height on the medium supplemented with 5% Al, with an increase ranging from 8.7% to 130.8%. In the 5% Al treatment, plant height of PI567643 was the highest with 33.67 cm and was significantly different with 18 other lines in this study. Accession PI675661 had the highest increase in height at 130.8% when compared to its height in 0% Al. Figure 3.1 shows the difference in plant height in the 0% and 5% Al treatments starting at 14 days after planting for all strains except lines PI567410C and PI625695. The number of root nodules observed for the 20 selected lines is presented in Table 3.4. The results show a positive correlation with the 5%b Al treatment. In the control pots with 0% of Al, the number of root nodules in the lines ranged from 1.0 to 11.75 with the PI567410C having 79 the highest number of root nodules. Furthermore, results show that all lines were able to form root nodules after being inoculated with Rhizobium. The number of root nodules for 17 lines increased significantly between 24.1% to 600.0% when grown on medium supplemented with 5% Al. However, there were three lines, PI567410C, PI628962, and PI628871, which showed a negative correlation when treated with 5% Al. In these three lines, the number of root nodules deceased between 23.4%, 14.6%, and 8.7% respectively. The three variables measured in this study, root length, plant height, and the number of root nodules formed, show that all the 20 soybean lines perform well on soils with low pH of 4.5 and up to 5% aluminum. All lines were able to grow well and form root nodules in the low pH growth medium without the addition of any nutrients. Given that we conducted this experiment using lines especially selected to perform well in low pH soils, it is not surprising to find all lines performing well under these conditions. Tolerance of soybeans to acidic soils and aluminum toxicity depends on the genotype, physiological age, and the environment (Liao et al., 2006; Bojórquez-Quintal et al., 2017). Genetic factors could influence the differences seen in root growth and plant height. These differences would be useful to increase the genetic diversity of the soybean accessions in Indonesia and be used for further improving soybean varieties. We were able to observe a positive effect of adding Al to the growth medium by comparing the initial and final pH levels for the control with 0% Al and treatment with 5% Al. The pH of the growing medium at the beginning and end of the experiment in pots with 0% Al remained about the same and only ranged from 4.27 to 4.44; however, in the medium with 5% Al treatment, pH level increased about 1.0 or from an initial pH of 4.30 to a final pH level of 5.23 – 5.34. We believe this change was favorable to the plants (Table 3.5). Aluminum treatment to the 80 peat moss in this study provided a better environment for soybeans to grow. Peat moss is a medium with a high CEC (Mofidpoor, 2007). Perhaps this characteristic allowed ionic exchange in soil solution due to the strong absorption level of Al and helped increase the pH of the medium. Perhaps the amount of Al given to the medium we tested was not high enough to cause a toxic effect to the soybean plants. In low concentrations, the presence of Al will be beneficial to the plant and will stimulate root growth (Osaki et al., 1997; Bojórquez-Quintal et al., 2017). The results observed in this study seem to support this observation. Similarly, in the case of the number of root nodules formed, 17 out of the 20 lines showed a positive increase when treated with 5% Al. The number of root nodules of soybean were highly correlated with the level of pH of the growth medium (Foy, 1992). When the pH level of the medium increased, it stimulated plant root growth and improved the opportunity for the rhizobium to interact with the roots and form more nodules. Given that the pH level in the medium with 5% Al was higher compared to the control but was not over a pH level of 6.0, it supports the observations made by Rice et al. (1977) that soil pH influenced the number of root nodules on alfalfa in the pH under 6.0 and had a slight or no effect when the pH level increased to or higher than 6.0. We assumed that the positive effect of Al in a low concentration could be different if the plants were exposed to Al for a more extended period. In this study, we were unable to expand our experiment further due to the unavailability of greenhouse facilities on campus. However, given that the naturally occurring acidic soils in Indonesia fall in the range tested in our experiment, we believe the 20 lines used in this experiment to perform favorably under Indonesian soils. 81 APPENDIX 82 Table 3.1. Analysis of variance for plant height Source Lines Al level Lines*Al level Error Corrected Total DF Sum of square Mean square F value Pr>F 19 1 19 40 79 658.15 34.64 5.88 <0.0001 1342.26 1342.26 227.86 <0.0001 270.29 235.63 2506.33 14.23 5.89 2.41 0.0094 Table 3.2. LSD means separation for root length Accession PI628871 PI556744 PI625695 PI556727 PI590932 PI628880 PI675661 PI628842 PI628929 PI556537 PI556612 PI556564 PI567779A PI567611 PI567643 PI628962 PI556515 PI628925 PI567410C PI594922 Root length (cm) Al 5% 20.48 a ** 19.30 ab 18.88 abc 18.73 abcd 17.95 a-e 17.85 a-e 17.75 a-e 17.23 a-e 16.98 a-e 16.68 a-e 16.55 a-e 16.20 bcde 16.20 bcde 15.90 bcde 15.83 bcde 15.73 bcde 15.25 bcde 14.90 cde 14.53 de 14.03 e Al 0% 8.03 a-e 10.05 abcd 10.35 abcd 10.85 abc 7.95 a-e 7.50 a-e 5.58 e 6.80 de 11.33 ab 10.20 abcd 6.58 de 8.50 a-e 11.70 a 6.90 cde 7.23 bcde 8.28 a-e 8.85 a-e 8.90 a-e 5.88 de 11.38 a ** means within columns followed by the same letter are not significantly different (P<0.05) 83 Table 3.3. LSD means separation for plant height Accession PI567643 PI567779A PI556727 PI556744 PI628929 PI594922 PI556612 PI556537 PI628925 PI556515 PI556564 PI675661 PI567611 PI628842 PI628871 PI590932 PI628880 PI567410C PI625695 PI628962 Plant height (cm) Al 5% Al 0% 33.67 a ** 15.42 a-e ** 28.40 ab 27.43 bc 27.38 bcd 18.97 a 18.40 ab 18.35 ab 25.63 bcde 15.06 a-e 24.62 b-f 24.42 b-f 24.22 b-f 23.40 b-g 22.63 c-g 22.53 c-g 22.51 c-g 22.03 defg 21.98 efg 21.48 efg 20.83 efg 20.47 efg 19.95 fg 18.67 fg 17.12 g 18.30 ab 18.93 a 19.08 a 14.90 a-e 16.95 abc 16.14 abcd 9.75 f 13.57 a-f 9.95 ef 10.68 def 12.28 cdef 11.85 cdef 18.35 ab 16.12 abcd 12.48 b-f ** means within columns followed by the same letter are not significantly different (P<0.05) 84 Table 3.4. LSD means separation for number of root nodules Accession PI556612 PI556727 PI556537 PI594922 PI567779A PI628925 PI625695 PI567643 PI556744 PI567410C PI628842 PI628962 PI556515 PI556564 PI567611 PI628929 PI675661 PI590932 PI628880 PI628871 Root nodules number (unit) Al 5% 18.75 a ** 14.25 ab 13.50 ab 13.25 ab 13.00 ab 12.50 ab 10.50 ab 10.25 b 9.00 b 9.00 b 9.00 b 8.75 b 8.50 b 8.25 b 8.00 b 7.25 b 7.00 b 6.75 b 6.75 b 5.25 b Al 0% 9.75 abc 4.75 abc 2.00 bc 2.75 bc 3.50 abc 7.25 abc 2.50 bc 5.50 abc 7.25 abc 11.75 a 2.50 bc 10.25 ab 6.00 abc 4.25 abc 2.25 bc 5.50 abc 1.00 c 4.00 abc 4.75 abc 5.75 abc ** means within columns followed by the same letter are not significantly different (P<0.05) Table 3.5. pH of the medium pre- and post- study Growth Medium samples Initial pH 1 2 3 4 5 4.30 4.40 4.32 4.34 4.30 Final pH 5% Al 5.34 5.26 5.23 5.28 5.30 0% Al 4.30 4.44 4.27 4.34 4.29 85 Figure 3.1. Means of plant height in 20 soybean lines from day 7 to day 35 after planting (A0: 0% aluminum, A5: 5% aluminum treatments) 86 Figure 3.1. (Cont’d) 87 Figure 3.1. (Cont’d) 88 Figure 3.2. Means of root length in 20 soybean lines (at 35 days after planting) 89 Figure 3.3. Means of plant height in 20 soybean lines (at 35 days after planting) 90 Figure 3.4. Means of number of root nodules in 20 soybean lines (at 35 days after planting) 91 REFERENCES 92 REFERENCES Alleoni L.R., Cambri M.A., Caires E.F., Garbuio F.J., 2010. Acidity and aluminum speciation as affected by surface liming in tropical no-till soils. Nutrient management and soil and plant analysis. Soil Sci. Soc. Am. Journal 74:1010-1017. Doi: 09.0254/ssaj2009.0254 Arsyad D.M, Adie M.M., Kuswantoro H., 2013. Assembling of soybean superior varieties for specific agroecology in soybean – production and development techniques. Indonesian Agency for Agricultural Research and Development. In Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/03/dele_9.darman-1.pdf Bloom P.R. and Erich M.S., 1996. The quantitation of aqueous aluminum in the environmental chemistry of aluminum. Second edition. Chapter 1:1-38. Lewis Publisher. ISBN: 1-56670- 030-2. Board, J E. and Caldwell A.G., 1991. Response of determinate soybean cultivars to low pH soils. LSU Agricultural Experiment Station Reports: 349. Link: http://digitalcommons.lsu.edu/agexp/349 Bojórquez-Quintal E., Escalante-Magaña C., Echevarría-Machado I., Martínez-Estévez M., 2017. Aluminum, a friend or foe of higher plants in acid soils. Front. Plant Sci. 8:1767. doi: 10.3389/fpls.2017.01767 Burton J. and Miranda L., 2013. Soybean improvement: achievements and challenges. Ratar.Povrt. 50:2 (2013) 44-51. doi:10.5937/ratpov50-4158 Cornelissen G., Jubaedah, Nurida N.L., Hale S.E., Martinsen V., Silvani L., Mulder J., 2018. Fading positive effect of biochar on crop yield and soil acidity during five growth seasons in an Indonesian Ultisol. Science of The Total Environment Volume 634:561-568. https://doi.org/10.1016/j.scitotenv.2018.03.380 Coupal B. and Lalancette J.M., 1976. The treatment of waste waters with peat moss. Water Research Vol. 10: 1071-1076. Pergamon Press. https://doi.org/10.1016/0043- 1354(76)90038-5 Delhaize E. and Ryan P.R., 1995. Aluminum Toxicity and Tolerance in Plants. Plant Physiol. Vol.107: 31 5-321. Fageria N.K., Ballgar V.C., Wright R.J., 1988. Aluminum toxicity in crop plants. Journal of Plant Nutrition, 11:3, 303-319. DOI: 10.1080/01904168809363804 online source: https://doi.org/10.1080/01904168809363804 93 Foy C.D. and Fleming A.L., 1978. The physiology of plant tolerance to excess available aluminum and manganese in acid soils. Foy C.D., 1992. Soil chemical factors limiting plant root growth. Advance in soil science Vol. 19. Springer-Verlag New York Inc. Link: https://link.springer.com/content/pdf/10.1007/978-1-4612-2894-3_5.pdf Havlin J.L., Tisdale S.L., Nelson W.L., Beaton J.D., 2014. Soil fertility and fertilization: an introduction to nutrient management. Eight editions. Published by Pearson Education, Inc. Upper Saddle River, New Jersey, USA. ISBN: 978-81-203-4868-4 IAARD, 2017. Description of soybean varieties (1918-2016). Published by the Indonesian Legume and Tuber Research Institute, Malang. In Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/09/kedelai.pdf Krstic D. and Djalovic I., 2012. Aluminum in acid soils: chemistry, toxicity and impact on maize plants in food production – approaches, challenges, and tasks. ISBN: 978-953-307-887-8. DOI: 10.5772/1870. Liao H., Wan H., Shaff J., Wang X., Yan X., Kochian L.V., 2006. Phosphorous and aluminum interaction in soybean in relation to aluminum tolerance. Exudation of specific organic acids from different regions of the intact root system. Plant physiology. Vol. 141: 674-684. Link: www.plantphysiol.org/cgi/doi/10.1104/pp.105.076497 Liang C., Piñeros M.A., Tian J., Yao Z., Sun L., Liu J., Shaff J., Coluccio A., Kochian L.V., Liao H., 2013. Low pH, aluminum, and phosphorus coordinately regulate malate exudation through GmALMT1 to improve soybean adaptation to acid soils. Plant Physiology, Vol. 161: 1347–1361. Link: www.plantphysiol.org/cgi/doi/10.1104/pp.112.208934 Martinsen V., Alling V., Nurida N.L., Mulder J., Hale S.E., Ritz C., Rutherford D.W., Heikens A., Breedveld G.D., Cornelissen G., 2015. pH effects of the addition of three biochars to acidic Indonesian mineral soils. Soil Science and Plant Nutrition, 61:5, 821-834, DOI:10.1080/00380768.2015.1052985 online source: https://doi.org/10.1080/00380768.2015.1052985 Mofidpoor M., 2007. Quality of peat moss as a component of growing media. Thesis. The University of British Columbia. Link: https://open.library.ubc.ca/cIRcle/collections/ubctheses/831/items/1.0100713 Mossor-Pietraszewska T., 2001. Effect of aluminum on plant growth and metabolism. Acta Biochimica Polonica. Vol. 48 No.3: 673-686. 94 Mulyani A., Rachman A., Dairah A., 2009. The spread of acidic-soil: potential and availability for agricultural development in Rock-phosphate: utilization of rock-phosphate as phosphate nutrient source. Pgs: 25-46. Link: http://balittanah.litbang.pertanian.go.id/ind/dokumentasi/buku/fosfatalam/anny_mulyani.pd f Nurlaeny N., Marschner H., George E., 1996. Effects of liming and mycorrhizal colonization on soil phosphate depletion and phosphate uptake by maize (Zea mays L.) and soybean (Glycine max L.) grown in two tropical acid soils. Plant and Soil (1996) 181: 275-285. Kluwer Academic Publishers. https://doi.org/10.1007/BF00012062 Osaki M., Watanabe T., Tadano T., 1997. Beneficial effect of aluminum on growth of plants adapted to low pH soils. Soil Science and Plant Nutrition, 43:3, 551-563, DOI: 10.1080/00380768.1997.10414782. online source: https://doi.org/10.1080/00380768.1997.10414782 Panda S.K., Baluska F., Matsumoto H. 2009. Al stress signaling in plants. Plant signaling and behavior 4:7 592-597 Rengel Z., Bose J., Chen Q., Tripathi B.N., 2015. Magnesium alleviates plant toxicity of aluminum and heavy metals. Crops and Pasture Science, 66:1298-1307. http://dx.doi.org/10.1071/CP15284 Rahman M.A., Lee S-H., Ji H.C., Kabir A.H., Jones C.S., Lee K-W., 2018. Importance of mineral nutrition for mitigating aluminum toxicity in plants on acidic soils: current status and opportunities. International Journal of Molecular Sciences 19, 3073. Doi: 10.3390/ijms19103073 Rice W.A., Penney D.C., Nyborg M., 1977. Effects of soil acidity on rhizobia numbers, nodulation, and nitrogen fixation by alfalfa and red clover. Can. J. Soil Sci. 57: 197-203. Link: https://www.nrcresearchpress.com/doi/pdf/10.4141/cjss77-024 Robbins J.A., 2018. Growing Media for Container Production in a Greenhouse or Nursery. FSA6097-PD-8-2018RV. The University of Arkansas System Division of Agriculture in little rock. Link: https://www.uaex.edu/publications/PDF/FSA-6097.pdf Rochayati and Dariah. 2012. Acidic dry-land development: opportunities and challenges in Dry- land agriculture prospect in supporting food security. Indonesian Agency for Agricultural Research and Development (IAARD). Jakarta. pg. 187-206 Rout G., Samantaray S., Das P., 2001. Aluminium toxicity in plants: a review. Agronomie, EDP Sciences, 21 (1): 3-21. DOI: 10.1051/agro:2001105. 95 Santore R.C., Ryan A.C., Kroglund F., Rodriguez P.H., Stubblefield W.A., Cardwell A.S., Adams W.J., Nordheim E., 2018. Development and aaplication of a biotic ligand model for predicting the chronic toxicity of dissolved and precipitated aluminum to aquatic organisms. Environment Toxicology and Chemistry. Vol. 37 No. 1: 70-79. Wiley online library. DOI: 10.1002/etc.4020 SAS, 2012. SAS Institute Inc., version 9.4 Enhanced logging facilities, Cary, NC, USA. Situmorang A.R.F., MUBARIK N.R., Triadiati. 2009. the use of acid-aluminium tolerant Bradyrhizobium japonicum inoculant for soybean grown on acid soils. HAYATI Journal of Biosciences. Vol. 16 No. 4. Pages: 157-160. ISSN: 1978-3019 Sposito G., 2016. The chemistry of soil. Third edition. Oxford University Press. New York. ISBN: 978-01-906-3088-1 Specht J.E., Hume D.J., Kumudini S.V., 1999. Soybean yield potential – a genetic and physiological perspective. Crop Science Vol. 39 No. 6: 1560-1570. DOI: 10.2135/cropsci1999.3961560x. Subardja D. 2007. Characteristics and management of acid soils derived from volcanic rocks for extensification of maize in Sukabumi Regency, West Java. Journal of Soil and Climate. N0. 25/2007. In Bahasa Indonesia. Link: https://media.neliti.com/media/publications/134702-ID-none.pdf Sumarno and Adie M.M. 2010. The development strategies of soybean production towards sustainable of food self-sufficiency. Journal of Iptek Tanaman Pangan. Vol. 5 no. 1: 49-63. In Bahasa Indonesia. Surahman A., Hendriadi A., Kartiwa B., Sulistyo A., Mulyandari R.S.H., 2012. Achievement of soybean self-sufficiency in 2014 using system dynamics approaches. Policy on self- sufficiency and sustainable self-sufficiency of five main crops through dynamic system approaches. Indonesian Agency for Agricultural Research and Development. In Bahasa Indonesia. Link: https://www.litbang.pertanian.go.id/buku/aplikasi-system-modelling/ USDA, 2015. Legume seed inoculation. Plant materials technical notes number: TX-PM-15-01. United States Department of Agriculture-Natural Resource Conservation Service. Link: http://nrcs.usda.gov/internet/FSE PLANTMATERIALS/publications/etpmctn12525.pdf Will E. and Faust J.E., 2010. PB1618-Growing Media for Greenhouse Production. The University of Tennessee Agricultural Extension Service. Link: http://trace.tennessee.edu/utk_agexcomhort/28 96 Wright, David, Lenssen, Andrew W. 2013. Inoculant Use on Soybean Seed. Agriculture and Environment Extension Publications. 192. Link: http://lib.dr.iastate.edu/extension_ag_pubs/192 Yang L.T., Qi Y.P., Jiang H.X., Chen L.S., 2013. Roles of organic acid anion secretion in aluminium tolerance of higher plants: a review article. BioMed Research International. Hindawi Publishing Corporation. Vol. 2013. http://dx.doi.org/10.1155/2013/173682 Yulnafatmawita, Detafiano D., Afner P., Adrinal, 2014. Dynamics of physical properties of Ultisol under corn cultivation in wet tropical area. International Journal on Advanced Science Engineering Information Technology. Vol.4 (2014) No. 5. ISSN: 2088-5334 97 CHAPTER 4. EVALUATION OF TWENTY SOYBEAN LINES FROM USA, CHINA, AND BRAZIL FOR TOLERANCE TO ACIDIC SOILS IN INDONESIA Abstract In Indonesia, the industry prefers large seeded soybean varieties. However, given the land available for soybean production in Indonesia has acidic soils, any large seeded varieties developed must also be tolerant to acidic soils. While some soybean varieties currently available in Indonesia show tolerance to acidic soils, their seeds are categorized as small to medium sized. Since it is easier to improve the seed size trait through breeding, in our attempts at developing better soybean varieties for Indonesia, we focused on adaptability to acidic soils and tolerance to aluminum toxicity as the primary breeding objective. Hence, in the present study we evaluated a previously selected set of 20 soybean lines under Indonesian acidic soils for their tolerance to acidic soil and aluminum toxicity. The study was conducted for two planting seasons, in 2017 and 2018, in two locations, Tanah Laut and Banjarbaru Regency. To select the best performing out of the 20 lines under current farmer practices, a split-split plot design with three factors was used with lime as the main plot, organic fertilizer as the subplot, and soybean genotypes as the sub-subplot. Two farmer preferred varieties, ANJASMORO and DERING, were used as standard check varieties to evaluate performance. Plant height, root length, number of root nodules, number of pods, and yield were used to evaluate the performance of the 20 lines. All data were analyzed using ANOVA and LSD. Of the 20 lines tested, the best four genotypes with the highest yields were PI675661 with 3.08 tons/ha (for farmers who applied lime, but did not apply organic fertilizer), PI628880 with 2.46 tons/ha and PI628929 with 2.41 tons/ha (both: for farmers who did not apply lime, but applied only organic fertilizer), PI628880 with 2.03 tons/ha (for farmers who did not apply lime or organic fertilizer), and PI628871 with 2.32 tons/ha and 98 PI628929 with 2.28 tons/ha (both: for farmers who applied a combination of lime and organic fertilizer). In the 2018 season, the yield reported was the highest in PI628925 with 2.38 tons/ha (for farmers who applied a combination of lime and organic fertilizer), and PI675661 with 2.17 tons/ha and PI628929 with 2.03 tons/ha (both: for farmers who did not apply lime, but applied only organic fertilizer). The yields of these lines in both seasons were higher than the two standard check varieties. The two lines PI675661 and PI628929 can be considered as the promising lines with superior traits: number of pods, yield, and larger seed size. Introduction People in Indonesia have grown soybean since the 16th century (Hartman et al., 2011). In Indonesia, soybeans have been mainly used as a processed food since the 17th century (Sidharta, 2008). Therefore, soybean is considered to be a part of the Indonesian food culture and is used in daily diets. About 88% of soybean from the national production is used to make tempeh and tofu, the two most preferred high protein processed food products, while another 10% is used for soy milk and soy-based snacks (Saliem and Nuryanti, 2011). As many as 81,000 household units and industries are involved producing tempeh and tofu, providing significant employment opportunities to locals (The National Standardization Agency Republic of Indonesia - BSN, 2012). In addition to the dry grains, there is a demand for soybean meal, used as an essential ingredient and protein source in animal feed. With the increase in the livestock industry in Indonesia, this demand is expected to increase (Sudaryanto and Swastika, 2007; Bantacut, 2017). Given that more than 95% of soybean grain is processed into food products, the demand for soybean meal is met through imports. 99 The Ministry of Agriculture, Republic of Indonesia (2015) reported that the national demand for soybean reached 2.235 million tons of dry grain in 2014, a 5.67% increase from 2013. However, Indonesia can only produce about 955,000 tons which is 42.7% of the demand; hence, as demands increases, more imports are required. While efforts were underway to increase soybean production since the 1980s, due to the lack of varieties that met market demand and limited availability of land for soybean production, expected targets could not be reached. The most important qualities of soybean required for tempeh and tofu industries are the large seed size, yellow seed-coat color, and the amount of grain that can be shelled and processed into products (personal communication with tempeh and tofu industries in South Kalimantan Province in 2018). Appearance of both tempeh and tofu are attractive to consumers when they are made with yellow seeds (Krisnawati and Adie, 2015). However, soybean cultivars currently available are categorized as having small and medium sized seeds, which do not meet the market demand as farmers have difficulty in shelling the grain. With an interest in achieving self-sufficiency in rice, the most favorable agricultural land in the Java island was allocated to rice. This meant that the available land for increasing soybean production has to be in non-Java areas with acidic dry-lands. These dry-land areas are dominated by Ultisols representing 40.77% (Mulyani et al. 2009). While Ultisols have the potential to be used for agriculture, acidity (pH 4.27 – 5.30), low soil organic matter content, high saturated Aluminum (Al) levels, and high level of fixed Phosphorus (P) that plants cannot absorb (Rochayati and Dariah, 2012; Yulnafatmawita et al., 2014) limit their productive capacity. The total acidic dry land in Indonesia is more than 100 million hectares (ha) and is mainly located on the islands outside of the Java island. For the past 30 years, lower soil acidity was known to be the main factor obstructing agriculture production in these areas and liming is 100 recommended before planting. Besides liming, the Indonesian government has also recommended the use of organic fertilizer to improve soil fertility. Some farmers use liming to manage soil fertility issues brought forward by low pH. However, most smallholder resource poor farmers often do not have the capital to lime the soils, hence farmer-adoption of liming application has been low. Therefore, the government is considering the development of soybean varieties that can withstand acidic soils without great yield penalties as a means of assisting farmers to increase their economic gains by planting soybean in the acidic marginal lands. The soybean breeding program in Indonesia started in 1918, but this program was only focused on developing high yielding varieties with broader adaptability. Focus on specific characteristics such as adaptation to soil type only began in the 1990s. As the result, the Indonesian Agency for Agricultural Research and Development (IAARD) was able to release three varieties; ANJASMORO, TANGGAMUS and DEMAS, with tolerance to acidic soils. However, the seed size of these three varieties does not meet the market demand that requires larger seed sizes of > 13 g/100 seeds (Kristanto et al., 2013). Thus, developing large seeded, early maturing and high yielding soybean varieties that perform well on acidic soils, are critically needed for Indonesia in order to meet the industry and consumer demands (Arsyad et al., 2013). One of the main limitations in Indonesia’s soybean breeding program is the lack of germplasm with the favorable characteristics mentioned above. To bridge this gap, we focused on adaptive breeding. In this study, over 700 germplasm accessions obtained from the US, China and Brazil were first screened for their tolerance to acidic soils (Chapter 2) and aluminum toxicity (Chapter 3) and then were field tested in naturally acidic Ultisols soils in Indonesia to evaluate their agronomic performance for two seasons in 2017 and 2018. Provided Indonesia cannot rely on the Java island for increasing soybean production (Rachman, et al., 2007; Rochayati and Dariah, 101 2012; Susanti and Waryanto, 2017), the field testing was conducted in the Kalimantan region of the large island, dominated by acidic Ultisols. In this study, we were particularly interested in testing soybean varieties that have tolerance to acidic soils, large seed size and the preferred yellow seed coat color in comparison to the currently used varieties in the country. As such, this study is an important part of the government’s efforts in providing large seeded soybean varieties for the farmers. Therefore, our objectives were: to evaluate the 20 previously selected lines for tolerance to acidic soils in Indonesia and to select promising lines that can be grown by farmers and/or for use as parents in the soybean breeding program in Indonesia. Materials and Methods Location and experimental design The field research was conducted in two different seasons and sites. In the 2017 planting season, the study took place in Tanah Laut region as one of the agriculture centers in the South Kalimantan province. This area is located on 03064’ – 03°99’ of south latitude and 114,642° – 114,872° of east longitude. In the 2018 season, the study was conducted in Banjarbaru region which is located on 03°27' - 03°29' of south latitude and 114°45' - 114°45' of east longitude. This experiment used a split-split plot design with three factors including lime as the main plot, organic fertilizer as the sub plot, and soybean genotypes as the sub-sub plot. Lay out of these plots arrangement in the field is shown in Figure 4.1. 102 Treatments Two levels of lime were used as the main plots, which were 0.0 tons/ha and 5.0 tons/ha. Two levels of organic fertilizer were also used as the sub plots, which consisted of 0.0 tons/ha and 10.0 tons/ha. All units were arranged randomly in the field. The number of soybean lines used in the 2017 and 2018 seasons were the same, which were 20 lines previously selected (further described in Chapters 2 and 3) as the sub-sub plot, but the number of local varieties used as controls were different. In the 2017 season, five local varieties; ANJASMORO, ARGOMULYO, BURANGRANG, DEMAS, and DERING, were used as standard check varieties whereas in the 2018 season, due to limited availability of seed, we could only use 2 of these local varieties, ANJASMORO and DERING as standard check varieties. However, only two of the same local varieties will be used in data analysis for both seasons. ANJASMORO is a popular soybean variety widely planted in Indonesia for its’ larger seed size and higher yield compared to other varieties, and DERING is a variety which performs well when planted in the dry season. The individual experimental plot size was 1.6 x 1.0 m2 for the 2017 planting season and 1.0 x 0.8 m2 for the 2018 season. Each plot was separated by a small drainage channel of 0.2 m in depth and 0.3 m in width. The distance between main plots was 1.0 m. The total number of experimental units was 200 in the 2017 season and 176 in the 2018 season. The differences of plot size between the 2017 and 2018 season was because the availability of land for research on both locations was different. The planting population per hectare for both seasons were the same with each plant being planted using 0.4 m x 0.15 m row space. Planting depth was 2.5 cm with 2 seeds per planting hole. 103 Soil test Soil tests were conducted prior to planting date and after the study. The purpose of soil sampling was to determine the pH level, organic matter content, N, P, and K, total cation exchange capacity and the Al saturation level. The soil sampling was carried out using a soil drill in a composite manner with five sample points per site, each time sampling was carried out. The soil samples was taken at a depth of 20 cm (Ackerson, 2018). After the experiment, the soil samples were collected in accordance with organic matter treatments. All soil samples were sent to the Indonesian Swampland Agriculture Research Institute (ISARI) for analysis. ISARI is the IAARD’s national reference laboratory in the Kalimantan area located in Banjarbaru that conducts soil, plant, fertilizer, and water testing. Maintenance The plants were fertilized using commercial chemical fertilizers with the following dosage: 11.5 kg/ha nitrogen, 52 kg/ha P2O5, and 60 kg/ha K2O. These dosages are based on government recommendations for soybean planted on acidic dry land. All fertilizers were applied once at the time of planting (Yusuf and Harnowo, 2012). In this study, we applied only a half dosage of all fertilizer as recommended by IAARD to get the benefit from Rhizobium and organic fertilizer application. Watering and pesticide applications were done on a need basis. Observations and data analysis We observed variables at vegetative and reproductive stages. As such, measurements were taken at five points in the 2017 season and 3 points in the 2018 season. The main variables considered were plant height, root length, number of rood nodules, number of pods, and yield. 104 Data was subjected to analysis of variance using PROC MIXED in SAS (SAS, 2012). Fisher’s Protected Least Significant Differences (LSD) at a 5% significance level was used to test the significant differences among treatments based on the significant results obtained from the analysis of variances (ANOVA) test. Participatory selections with local farmers Research locations in Both Tanah Laut and Banjarbaru Regency were within the area of the South Kalimantan Assessment Institute for Agricultural Technology (AIAT) research stations. These two locations have become centers for dissemination of agricultural technologies to farmers and officers in the South Kalimantan Province. Therefore, while we had our own selection criteria, we used this opportunity to invite farmers and extension officers to evaluate and choose their preferred lines based on their own selection criteria. This participatory approach was important to us to gather useful information from groups that promote and/or use promising line(s) released from research efforts. Results and Discussion The soil test results are shown in Table 4.1. The soil analyses provided by IAARD (Eviati and Sulaeman, 2009) indicate both Tanah Laut and Banjarbaru soils are very acidic with pH levels < 4.0. Soil carbon stocks of both locations are categorized to be very low (<1.00%) with low nitrogen content (<0.20%). Therefore, the C/N ratio of both locations were low. Cation exchange capacity (CEC) of soil in Banjarbaru site was higher than Tanah Laut site which also had a higher level of phosphorous. These results indicated that the soils in both locations have 105 low nutrient content not suitable to support crops. However, the aluminum content was also low and at a level that can be tolerated by crops (Osaki et al., 1997; Bojórquez-Quintal et al., 2017). Line performance in the 2017 planting season There were significant differences among the lines at P < 0.0003 and significant interaction of lime and organic fertilizer application at P<0.0096 (Table 4.4). This result indicated each line has different abilities for producing seed influenced by both environment and genetic factors. Other than the genetic factors, environmental factors such as low soil pH level (Table 4.1), lower precipitation (Table 4.2), diseases, and practical difficulties had an effect on the yield. Application of lime and organic fertilizer improved soil quality and supported plant growth to obtain a higher yield. Moreover, the 20 tested lines were also genetically different from some aspects such as the maturity group (Table 4.3) and number of pods produced (Table 4.7). Calcification treatment of 5 tons/ha dolomite increased soil pH to about 1.0 point from 3.66 to 4.77, and the combination treatments of lime and organic fertilizer application further increased soil pH by 1.6 points from 3.66 to 5.26 (Table 4.1). Application of lime is widely used to increase soil pH and to provide calcium (Ca) and magnesium (Mg) to the growing medium to benefit plant growth (Gillman et al., 1998; Pagani, 2011). Soil pH can also be increased by applying organic fertilizer to the medium (Whalen et al., 2000). We observed this as the application of organic fertilizer as a sub plot resulted in the higher yield. In the first treatment, which is application of 5.0 tons/ha of lime as the main plot and 10.0 tons/ha of organic fertilizer as the sub plot, the highest yield was obtained by DERING (local standard check variety), PI628871, and PI628929. The yield of these three-soybean accessions/lines were >0.5 tons higher than ANJASMORO (the first local standard check 106 variety), the widely planted variety in Indonesia, and the other tested lines (Table 4.5). Moreover, the PI628871 and PI628929 had a larger seed size compared to DERING, which can fulfill the market demand for seed size, especially with PI628929 that had 18.92 gram/100 seeds and categorized as large seeded in Indonesia (Table 4.3). The second treatment, the application of 5.0 tons/ha lime as the main plot and 0.0 tons/ha organic fertilizer as the sub plot, lines PI675661 and PI628929 gave the highest yield. Line PI675661 produced 3.08 tons/ha was not only the highest yield obtained in the second treatment but also the highest among all tested lines in all treatments. In this second treatment, although the yield of PI675661 does not differ from the two local standard check varieties, the difference in yield exceeded by > 1.0 tons/ha. The other line, PI628929, yielded 2.26 tons/ha which was 0.5 tons higher than the local standard check variety, ANJASMORO (Table 4.5). Line PI675661 had a similar seed size and seed coat color to that of the local variety ANJASMORO, while PI628929, had larger seeds and fell in the large seeded category with the preferred yellow seed color (Table 4.3). As such, these two lines can be considered as promising lines to improve soybean production in acidic soils. For the third treatment, the application of 0.0 tons/ha lime as the main plot and 10.0 tons/ha organic fertilizer as the sub plot, lines PI628880 and PI628929 gave the highest yields. The yield of these two lines were 0.1 to 0.2 tons higher than local ANJASMORO and DERING varieties currently grown. Line number PI628929 had seed sizes larger than both ANJASMORO and DERING. Seeds of PI628880 were larger than DERING but were smaller than ANJASMORO. The third treatment is the treatment preferred by farmers because they can afford to obtain organic fertilizer but are often not able to purchase lime. Therefore, PI628929 shows promise to be used as a variety for planting in acidic soils. 107 The fourth treatment, the application of 0.0 tons/ha lime as the main plot and 0.0 tons/ha organic fertilizer as the sub plot, generated PI628880 and PI628962 as the lines with the highest yield. Line number PI628880 yielded 2.03 tons/ha which was 0.7 tons higher than both ANJASMORO and DERING local varieties, while PI628962 produced 1.72 tons/ha which was 0.5 higher than ANJASMORO and DERING. However, the seed size of both PI628880 and PI628962 lines were slightly smaller than ANJASMORO and hence would not be suitable to cater the market demands. As for number of pods, line number PI675661 generated more pods than ANJASMORO and DERING for the first and second treatments (Table 4.7). Since number of pods is one important component in soybean production, PI675661 has met another criterion to be a promising line beside the seed size and seed color. However, the third and fourth treatments show that both ANJASMORO and DERING perform better than PI675661. In the fourth treatment, there was an interesting result where PI628925 produced the highest number of pods exceeding ANJASMORO and DERING. Interestingly, PI628925 was selected by farmers as a preferred line considering plant height and maintaining the crop in the field and because PI628925 has a seed size similar to ANJASMORO. Therefore, PI628925 could become a promising line especially if it can be bred to improve seed size and pod number. The results obtained from the four treatments can be summarized based on farmer preferences. Lines PI628929 and PI675661 were considered as promising lines on acidic soils for farmers who could afford to add lime and organic fertilizer to improve soil fertility before planting. Line PI628880 could be considered in the soybean improvement programs for farmers with limited capital. 108 The higher yields obtained by the lines mentioned above indicate applying organic fertilizer prior to planting provide better growing conditions for soybean, mainly on acidic soil. In this treatment, adding organic fertilizer even with no lime application helped increase the soil organic carbon to a higher level than other treatments (Table 4.1). Adding organic fertilizer to acidic soil would not only increase soil organic matter (SOM) content (McCauley et al., 2017), but also could reduce aluminum (Al) activity in the soil (Lyamuremye et al., 1996). The existence of Al in small amounts in the soil will stimulate plant root growth and increase the plant’s ability to take up soil nutrients (Bojorquez-Quintal et al., 2017). The advantage of adding manure to increase soil quality specifically for acidic soil is beneficial for farmers in developing countries like Indonesia. Low crop productivity induced by low soil nutrient content and Al toxicity has changed farmers’ decision from planting soybean to other remunerative crops like rice. The common recommendation provided by government to reduce soil acidity is by applying lime to the soil. However, smallholder farmers cannot afford to purchase lime and tend to avoid the recommendation (Uguru et al., 2012). Therefore, the results of this study can be used to recommend the use of organic fertilizer for soybean production in acidic soils. Line performance in the 2018 planting season Significant differences were found among organic fertilizer applications, and lines as factors and the interaction between all factors, the 3-way-interactions, to the yield. These results indicated that combining lime and organic fertilizer application to the soil was the best treatment to obtain the highest yield. One of the positive effects of applying the combination treatment in this study was an increase in soil pH by 1.24 points from 3.88 to 5.12 (Table 4.1). Increase in soil pH levels helped to increase the yield. 109 In the first treatment, which was application of lime at 5.0 tons/ha as the main plot and 10.0 tons/ha of organic fertilizer as the sub plot, line number PI628925 obtained the highest yield with 2.38 tons/ha which was 0.4 tons higher than the local standard check varieties ANJASMORO, and more than 1.0 tons higher than DERING (Table 4.9). In the second treatment, the application of 5.0 tons/ha lime as the main plot and 0.0 tons/ha organic fertilizer as the sub plot, lines PI675661 gave the highest yield with 1.95 tons/ha which was 0.2 tons higher than ANJASMORO and 0.8 tons higher than DERING. In the third treatment, the application of lime at 0.0 tons/ha as the main plot and application of organic matter at 10.0 tons/ha as the sub plot, line PI675661 gave the highest yield followed by PI628929 with the second highest yield. The yield of line PI675661 was 2.17 tons/ha which was 0.7 tons higher than the local variety ANJASMORO and more than 1.0 tons higher than DERING. The yield of line PI628929 yield was 2.03 tons/ha which was higher than both ANJASMORO and DERING. In the fourth treatment, when lime was applied at 0.0 tons/ha as the main plot and organic matter was applied at 0.0 tons/ha as the sub plot, lines PI556744 and P628871 had the highest yields with 1.47 tons/ha and 1.43 tons/ha respectively. These yields were 0.3 tons higher than the local variety ANJASMORO and 0.5 tons higher than DERING. Line PI556744 also had a bigger seed size than ANJASMORO and was categorized as large- seeded. In terms number of pods, line number PI628880 generated more pods than both ANJASMORO and DERING for the first and third treatments, treatments that used organic fertilizer, while line number PI675661 produced the highest number of pods for the second and fourth treatments, treatments without organic fertilizer applications (Table 4.11). If number of pods are to be considered as a production variable, PI628880 and PI675661 would be the two 110 promising lines that can be suggested for acidic soils. However, the yield of all tested lines and local varieties in the 2018 planting season were lower than the 2017 planting season (Figure 4.2) due to a number of reasons. Some challenges influenced soybean yield in the 2018 study to be lower than that of the 2017 study due to climate, disease, and practical difficulties. The 2018 study began in the mid of May which was the end of the rainy season in the district of Banjarbaru. Furthermore, the rainfall was much lower in 2018 than that of 2017 season (Table 4.2). In order to maintain live and growing plants, all plots had to be watered two times daily when there was no rain during the day or the previous day. Pest infestations also contributed to the lower yields in 2018. During the 2018 study, there were no other crops around the field planted by farmers due to it being a dry season. Therefore, we observed higher pest infestations in 2018 than in 2017. Among the pests found in the field were: true white grubs, armyworms, grasshoppers, stink bugs (green), and stem borers. Combined with manual control, we had to spray pesticides three times during the growing season to protect the plants. We were able to make some important observations from these two seasons of field studies. Liming applications can increase soil pH as much as 1.0 point or more and is a good recommendation for farmers who are not resource constrained, to increase soybean production. Furthermore, higher yields can be achieved by combining the applications of both lime and organic fertilizer. Applying lime will also reduce the negative effects of aluminum and increase crop yields (Kamprath, 1984). However, for farmers who have limited capital, the application of organic fertilizer to acidic soils can be considered as the best option to improve soybean production. By doing so, farmers could benefit by increasing soil pH and the soil organic carbon 111 (SOC). In addition, application of manure also increases the availability of phosphorous and reduce effects from aluminum toxicity (Babou et al. 2007). The soil organic carbon is an important indicator of soil health (Wiesmeier at al. 2019). The content of SOC in the experimental fields was very low and needed enhancement through amendments such as application of cattle manure. Indonesia has high precipitation during the rainy season, from October to March, and has high temperatures during the dry season, from May to September/October. These seasonal differences influence SOC content in the soil (Wiesmeier at al. 2019). Applying organic fertilizer also enhances water holding capacity of the soil which is important for farmers who cultivate dry-acidic land (Haynes and Naidu, 1998). In summary, through our research efforts, we have identified several soybean lines out of the initial set of over 700 tested, that farmers could use to improve soybean production in acidic soils in Indonesia. We are also able to recommend soybean lines based on preferred farmer practices and seasonal weather patterns. The 20 lines that are able to withstand acidic soils can also be added to the IAARD’s soybean breeding program to facilitate the development of better varieties and to improve the seed size of local varieties. 112 APPENDIX 113 Table 4.1. Soil test results from two locations in 2017 and 2018 growing seasons Location/site Tanah Laut Before study After study - Treatment #1:** w/o lime and w/o organic fertilizer - Treatment #2: w/o lime + w/ organic fertilizer - Treatment #3: w/ lime + w/ organic fertilizer - Treatment #4: w/ lime + w/o organic fertilizer Banjarbaru Before study After study - Treatment #1: w/o lime and w/o organic fertilizer - Treatment #2: w/o lime + w/ organic fertilizer - Treatment #3: w/ lime + w/ organic fertilizer - Treatment #4: w/ lime + w/o organic fertilizer C-Org (%) N (%) C/N (%) CEC (cmol/kg) P (Bray 1, ppm) Al (cmol/kg) 0.95 0.15 6.42 15.03 19.26 2.48 pH* 3.66 3.97 0.97 0.20 4.8 4.00 1.09 0.12 9.05 5.26 1.08 0.10 10.44 4.77 0.96 0.16 5.82 25.90 1.08 29.48 1.66 26.65 0.00 23.79 0.00 3.88 0.93 0.18 5.17 21.95 52.91 0.00 3.90 0.78 0.08 9.74 3.98 0.73 0.08 9.43 5.12 0.84 0.09 9.13 4.79 0.72 0.06 11.93 84.20 0.00 6.99 0.00 119.15 0.00 187.97 0.00 *Soil was tested in the IAARD’s soil, plant, fertilizer, and water testing laboratory (Tanah Laut is location for 2017 season and Banjabaru is location for 2018 season) ** w/ = with; w/o = without 114 Table 4.2. Monthly rainfall during the field research in 2017 and 2018 growing seasons Location Jan Feb Mar Apr May June July Aug Sep Oct Nop Dec Total 2017 Tanah Laut 509 248 215 287 295 179 127 134 81 145 431 398 3,049 2018 Banjar baru 391 313 370 174 75 112 77 78 107 107 227 205 2,236 Table 4.3. PI number, seed weight, and maturity group of soybean lines and local varieties used in 2017 and 2018 growing seasons PI Number Weight of 100 seeds (g) MG / Origin PI594922 PI590932 PI556515 PI556564 PI556537 PI556727 PI556744 PI567611 PI567643 PI567779A PI567410C PI628842 PI556612 PI628871 PI628880 PI625695 PI628925 PI628962 PI628929 PI675661 ANJASMORO DERING 15.56 17.31 14.89 16.96 14.12 15.61 17.58 10.53 16.72 16.33 13.91 14.75 11.72 14.21 13.91 13.46 14.51 14.07 18.92 15.24 15.30 10.70 V / USA VI / USA VIII / USA VII / USA VIII / USA VIII / USA V / USA IV / China IV / China IV / China VII / China VIII / China V / China VI / Brazil V / Brazil VII / Brazil VIII / Brazil VII / Brazil IX / Brazil X / Brazil Local / Indonesia Local / Indonesia 115 Table 4.4. Analysis of variance for yield variable in the 2017 growing season Source of var. Lime Organic fertilizer Lines Lime*Organic Fertilizer Lime*Lines Organic Fertilizer*Lines Lime*Organic Fertilizer*Lines Block Block*Lime Residual DF 1 1 21 1 21 21 21 1 1 86 Sum of Square 0.1700 0.0529 20.5005 2.3994 5.7235 7.2673 4.7230 0.3645 0.1638 29.4071 Mean Square F-value Pr > F 0.1700 0.0529 0.9762 2.3994 0.2725 0.3461 0.2249 0.3645 0.1638 0.3419 1.04 0.15 2.85 7.02 0.80 1.01 0.66 2.22 0.48 0.4941 0.6952 0.0003 0.0096 0.7157 0.4583 0.8618 0.3760 0.4907 Table 4.5. Comparison of means for yield in the 2017 growing season Lines DERING P628871 PI628929 PI590932 PI628880 PI567643 PI567779A PI628962 PI628842 PI567611 PI556727 PI556744 ANJASMORO PI625695 PI567410C PI594922 PI628925 PI556515 PI675661 PI556564 PI556537 PI556612 W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Yield (t/ha) Fertilizer 2.37 a** 2.32 a 2.28 a 1.84 ab 1.83 ab 1.71 ab 1.54 ab 1.49 ab 1.43 ab 1.42 ab 1.33 ab 1.22 ab 1.20 ab 1.19 ab 1.18 ab 1.11 ab 1.10 ab 1.08 ab 0.87 b 0.86 b 0.79 b 0.53 b Fertilizer 2.03 ab 1.98 ab 2.26 ab 1.90 ab 1.98 ab 1.07 b 0.98 b 1.87 ab 1.72 ab 1.05 b 1.72 ab 1.48 b 1.61 ab 1.24 b 1.23 b 0.97 b 1.63 ab 0.78 b 3.08 a 1.45 b 1.39 b 1.65 ab Fertilizer Fertilizer 2.31 abc 1.79 abcd 2.41 ab 1.19 bcde 2.46 a 1.63 abcd 1.11 cde 2.02 abcd 1.71 abcd 1.07 cde 1.13cde 1.25 a-e 2.26 abc 0.97 de 1.48 a-e 1.16 bcde 1.49 a-e 1.73 abcd 1.75 abcd 1.65 abcd 1.60 abcd 0.30 e 1.29 b-f 1.65 abc 1.31 bcde 1.48 bcde 2.03 a 1.38 bcde 0.64 h 1.72 ab 1.29 b-f 0.77 fgh 0.74 gh 1.17 c-g 1.36 bcde 1.04 efgh 1.28 b-f 1.20 b-g 1.60 abcd 1.17 c-g 1.27 b-f 1.38 bcde 1.67 abc 1.11 d-h ** means within columns followed by the same letter are not significantly different (P<0.05) 116 Table 4.6. Comparison of means for plant height in the 2017 growing season Lines W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Plant height (cm) DERING PI628880 ANJASMORO PI675661 PI628929 PI567779A PI567611 PI567410C PI567643 PI590932 PI628925 PI628871 PI594922 PI556515 PI556727 PI628962 PI556744 PI556612 PI556537 PI625695 PI556564 PI628842 Fertilizer 78.50 a** 67.70 ab 61.20 bc 58.20 bc 54.60 bc 53.65 c 50.70 c 40.70 cd 36.70 de 34.20 def 33.63 def 33.20 def 24.10 ef 29.10 ef 28.95 ef 27.20ef 26.30 ef 26.00 ef 25.30 ef 24.50 ef 24.20 ef 20.80 f Fertilizer 70.00 a 54.20 bc 58.00 b 76.80 a 50.60 bcd 45.75 cde 41.35 def 48.90 bcd 36.95 efg 34.95 fgh 38.05 efg 35.10 fgh 24.40 ij 24.90 hij 30.55 ghi 26.60 hij 29.98 ghi 31.10 ghi 29.40 ghi 18.55 i 23.80 ij 22.60 ij Fertilizer 70.00 ab 66.80 b 76.50 a 83.30 a 45.90 d 56.15 c 32.30 e 48.40 cd 45.90 d 33.28 e 32.60 e 42.00 d 23.30 fg 28.10 efg 27.01 efg 27.50 efg 27.70 efg 24.90 efg 31.20 ef 20.60 g 25.80 efg 22.20 g Fertilizer 63.30 a 53.50 b 57.95 ab 64.80 a 44.00 c 42.25 c 33.20 defg 39.40 cd 37.05 cde 31.45 d-h 36.70 cdef 31.45 d-h 22.20 i 26.20 ghi 21.40 i 25.80 ghi 22.65 hi 27.70 fghi 28.50 e-i 23.70 hi 23.10 hi 21.40 i ** means within columns followed by the same letter are not significantly different (P<0.05) 117 Table 4.7. Comparison of means for pod number in the 2017 growing season Lines PI675661 ANJASMORO PI628880 DERING PI567611 PI567410C PI567779A PI628929 PI590932 PI628871 PI628842 PI628925 PI556612 PI625695 PI628962 PI556744 PI567643 PI556564 PI594922 PI556727 PI556537 PI556515 Pods number (unit) W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Fertilizer 118.30 a** 102.30 ab 101.70 ab 94.60 abc 90.90 abcd 74.50 bcde 70.60 b-f 67.70 c-g 65.80 c-g 63.70 c-g 63.00 c-g 59.50 defg 58.50 defg 55.80 efg 54.70 efg 51.30 efg 48.40 efg 40.70 fg 40.20 fg 40.50 fg 38.10 g 37.20 g Fertilizer 62.70 a 42.10 a-f 62.70 a 60.10 ab 55.60 abcd 53.10 abcd 45.00 a-e 57.40 abc 57.20 abc 50.70 a-e 44.40 a-e 55.20 abcd 43.70 a-e 39.30 a-f 39.90 a-f 30.00 cdef 24.20 ef 36.30 a-f 27.90 def 32.30 b-f 31.70 cdef 15.10 f Fertilizer 54.40 b-f 59.70 b-f 73.20 bc 125.60 a 61.10 bcde 69.40 bcd 71.60 bc 57.80 b-f 46.50 b-f 61.60 bcde 63.00 bcde 74.60 b 29.60 f 36.60 ef 56.80 b-f 41.20 def 44.10 cdef 39.20 ef 41.10 cdef 44.10 cdef 50.60 b-f 45.10 b-f Fertilizer 37.50 a-f 37.70 a-e 47.10 ab 37.90 a-e 40.20 a-e 39.70 a-e 26.60 ghi 42.60 abcd 36.30 c-g 37.70 a-e 41.40 a-e 47.80 a 32.60 d-i 43.80 abc 36.70 c-g 27.30 fghi 35.40 c-h 31.30 e-i 33.30 d-i 25.20 hi 37.20 b-f 24.70 i ** means within columns followed by the same letter are not significantly different (P<0.05) 118 Table 4.8. Analysis of variance for yield in the 2018 growing season Source of var. Lime Organic fertilizer Lines Lime*Org Fertilizer Lime*Lines Org Fertilizer*Lines Lime*Org Fertilizer*Lines DF 1 1 21 1 21 21 21 Sum of Square 0.5841 4.0289 19.4695 3.3948 5.4923 6.2674 8.7224 Mean Square F-value Pr > F 0.5841 4.0289 0.9271 3.3948 0.2615 0.2984 0.4154 1.71 37.91 8.72 31.94 2.46 2.81 3.91 0.3206 <0.0001 <0.0001 <0.0001 0.0008 0.0001 <0.0001 Table 4.9 Comparison of means for yield in the 2018 growing season Lines W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Yield (t/ha) PI628925 ANJASMORO PI567779A PI594922 PI556727 PI556744 PI567410C PI628962 PI567643 PI590932 PI628871 DERING PI628929 PI625695 PI556564 PI567611 PI675661 PI556612 PI628842 PI628880 PI556515 PI556537 Fertilizer 2.38 a** 1.80 ab 1.78 ab 1.58 bc 1.57 bc 1.50 bc 1.38 bcd 1.36 bcd 1.28 bcd 1.26 bcd 1.24 bcd 1.22 bcd 1.16 bcd 1.07 cde 1.04 cde 1.03 cde 1.02 cde 0.98 cde 0.96 cde 0.74 de 0.51 e 0.49 e Fertilizer 1.66 ab 1.70 ab 0.42 f 1.14 def 1.01 f 0.93 f 1.19 cdef 1.15 def 1.15 def 1.42 bcde 1.50 bcd 1.10 def 1.58 abc 1.14 def 1.00 f 1.09 def 1.95 a 0.85 f 1.22 cdef 1.46 bcde 0.40 f 1.07 ef Fertilizer 1.20 ef 1.40 b-f 1.29 cdef 1.25 def 1.97 abc 1.09 efg 1.04 efg 1.17 ef 1.96 abcd 2.00 abc 1.14 efg 1.16 efg 2.03 ab 0.82 fg 1.13 efg 1.42 bcdef 2.17 a 1.19 ef 1.06 efg 1.69 abcde 0.44 g 0.92 fg Fertilizer 0.99 bcd 1.15 a 0.45 gh 0.86 bcde 1.05 abc 1.47 a 0.50 fgh 0.98 bcd 0.82 cdef 1.09 ab 1.43 a 0.95 bcde 0.98 bcd 0.80 cdef 0.64 efgh 0.42 h 0.98 bcd 1.00 bcd 0.76 defg 0.90 bcde 0.43 h 0.38 h ** means within columns followed by the same letter are not significantly different (P<0.05) 119 Table 4.10. Comparison of means for pod number in the 2018 growing season Lines PI628880 PI675661 ANJASMORO PI628929 PI567410C DERING PI628925 PI567611 PI625695 PI567643 PI556612 PI556537 PI628842 PI590932 PI628962 PI567779A PI628871 PI556564 PI556744 PI594922 PI556515 PI556727 Pods number (unit/plant) W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Fertilizer 178.67 a** 171.00 a 112.00 b 94.67 bc 93.00 bc 91.33 bcd 85.67 bcde 68.67 cdef 65.33 defg 62.67 efgh 60.00 efgh 59.33 efgh 59.00 efgh 57.67 fgh 55.67 fghi 54.67 fghij 43.67 fghij 40.67 ghij 40.33 ghij 38.00 hij 28.67 ij 28.00 j Fertilizer 111.33 a 113.00 a 91.33 ab 68.67 abcd 35.00 cd 69.67 abcd 87.00 abc 41.33 bcd 24.33 d 33.00 cd 78.67 abc 38.67 cd 46.67 bcd 38.33 cd 39.00 cd 26.33 d 38.33 cd 31.33 cd 30.00 cd 37.00 cd 29.67 cd 28.33 cd Fertilizer 213.67 a 129.00 b 85.67 cd 86.00 cd 57.67 defg 101.00 bc 72.33 cdef 52.00 defg 43.33 efg 75.00 cde 60.67 defg 36.67 fg 43.33 efg 57.67 defg 32.33 g 52.33 defg 65.00 cdefg 34.33 g 39.00 efg 43.67 efg 34.33 g 54.67 defg Fertilizer 143.67 ab 158.00 a 48.00 cd 116.00 bc 43.67 cd 47.67 cd 70.33 c 50.67 cd 40.00 cd 28.33 d 40.67 cd 42.00 cd 42.67 cd 51.67 cd 45.00 cd 37.33 cd 43.00 cd 33.67 cd 46.00 cd 33.33 cd 15.00 d 40.00 cd ** means within columns followed by the same letter are not significantly different (P<0.05) 120 Table 4.11. Comparison of means for root length in the 2018 growing season Lines W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Root length (cm) PI628880 PI675661 PI628929 ANJASMORO PI628871 PI590932 PI628925 DERING PI625695 PI628962 PI567410C PI556612 PI567779A PI628842 PI556744 PI567643 PI556727 PI594922 PI556515 PI556564 PI567611 PI556537 Fertilizer 24.78 a** 24.68 ab 24.54 ab 23.59 abc 22.99 abcd 22.24 a-e 21.63 a-f 21.20 a-f 20.46 a-f 20.29 a-f 20.20 a-f 19.98 b-f 19.78 cdef 19.33 cdef 19.29 cdef 19.07 cdef 18.77 def 18.47 def 17.92 ef 17.76 ef 17.38 f 16.89 f Fertilizer 23.06 abc 23.20 ab 26.30 a 20.89 abcd 19.07 bcde 16.33 defg 20.80 bcd 17.58 cdef 16.77 defg 17.41 defg 15.52 defg 17.84 b-f 14.91 efg 16.26 defg 16.37 defg 19.36 bcde 14.80 efg 17.81 b-f 13.57 fg 12.03 defg 16.94 defg 17.12 defg Fertilizer 25.28 a 25.82 a 23.30 ab 23.29 ab 22.42 abc 18.48 b-f 22.18 abc 25.27 a 18.43 cdef 17.79 cdef 14.79 ef 19.22 bcde 17.17 def 14.99 def 19.61 bcd 18.31 cdef 18.42 cdef 18.74 bcde 13.82 f 15.78 def 18.56 b-f 16.17 def Fertilizer 25.89 a 22.73 abc 23.79 ab 18.72 cde 19.07 cde 18.24 cde 19.37 bcde 18.08 cde 15.02 ef 17.34 def 15.74 ef 14.79 ef 18.30 cde 17.58 de 19.41 bcde 15.28 ef 21.08 bcd 18.26 cde 12.80 f 14.90 ef 16.78 def 17.52 de ** means within columns followed by the same letter are not significantly different (P<0.05) 121 Table 4.12. Comparison of means for plant height in the 2018 growing season Lines PI628880 PI675661 PI628925 PI628929 PI590932 PI556744 PI567643 PI567611 PI567779A PI628871 PI556727 PI628842 PI556612 ANJASMORO PI567410C PI594922 PI556515 PI628962 PI556537 DERING PI625695 PI556564 Plant height (cm) W/ Lime W/O Lime W/ Organic W/O Organic W/ Organic W/O Organic Fertilizer 84.50 a** 74.94 ab 74.33 abc 71.78 abcd 70.00 a-e 69.67 a-e 60.89 a-f 58.78 a-g 57.67 b-g 56.44 b-g 55.11 b-g 54.83 b-g 53.67 b-g 53.17 b-g 50.78 b-g 48.67 c-g 47.78 defg 47.67 defg 45.44 efg 39.67 fg 35.50 fg 33.56 g Fertilizer 87.67 a 68.39 b 68.50 b 69.11 b 41.33 ef 49.22 de 46.00 def 42.11 ef 40.33 efg 63.94 bc 50.89 cde 43.33 def 37.33 efg 56.39 bcd 42.39 ef 41.94 ef 34.89 fg 43.94 def 38.11 efg 57.00 bcd 38.94 efg 26.56 g Fertilizer 93.00 a 90.33 a 72.11 b 87.11 a 54.83 cd 49.11 de 55.44 cd 50.67 cde 56.22 cd 63.11 bc 53.94 cd 43.56 de 48.44 de 54.39 cd 49.11 de 45.22 de 42.58 de 50.00 cde 45.33 de 46.33 de 38.67 ef 28.78 f Fertilizer 82.00 a 76.67 ab 70.78 b 75.72 b 38.00 efg 47.89 cde 47.83 cde 43.33 cde 47.67 cde 53.44 c 50.44 cd 36.67 efg 37.89 efg 39.78 def 42.61 cdef 42.00 cdef 30.92 fg 47.22 cde 43.89 cde 49.78 cd 31.00 fg 27.11 g ** means within columns followed by the same letter are not significantly different (P<0.05) 122 w/ OF, 10 ton/ha w/o OF, 0 ton/ha w/ Lime, 5.0 ton/ha V3 V21 V20 V15 V11 V1 V3 V21 V20 V15 V11 V1 V17 V12 V16 V7 V4 V19 Figure 4.1. Layout of main plots, sub plots, and sub-sub plots in the field research ** Number of blocks: 2 blocks in 2017 season and 3 blocks in 2018 season V17 V12 V16 V7 V4 V19 V5 V2 V14 V9 V13 V6 V5 V2 V14 V9 V13 V6 V8 V22 V18 V10 V8 V22 V18 V10 V8 V22 V18 V10 V3 V21 V20 V15 V11 V1 V3 V21 V20 V15 V11 V1 V3 V21 V20 V15 V11 V1 w/o Lime, 0.0 ton/ha w/o OF, 0 ton/ha V3 V21 V20 V15 V11 V1 V17 V12 V16 V7 V4 V19 V5 V2 V14 V9 V13 V6 w/ OF, 10 ton/ha V3 V21 V20 V15 V11 V1 V17 V12 V16 V7 V4 V19 V5 V2 V14 V9 V13 V6 V8 V22 V18 V10 V3 V21 V20 V15 V11 V1 V17 V12 V16 V7 V4 V19 V17 V12 V16 V7 V4 V19 V17 V12 V16 V7 V4 V19 V17 V12 V16 V7 V4 V19 V5 V2 V14 V9 V13 V6 V5 V2 V14 V9 V13 V6 V5 V2 V14 V9 V13 V6 V5 V2 V14 V9 V13 V6 V8 V22 V18 V10 V8 V22 V18 V10 V8 V22 V18 V10 V8 V22 V18 V10 w/o OF, 0 ton/ha w/ OF, 10 ton/ha w/ OF, 10 ton/ha w/o OF, 0 ton/ha w/o Lime, 0.0 ton/ha w/ Lime, 5.0 ton/ha 123 B l o c k - 1 B l o c k - 2 Figure 4.2. Means of yield in the 20 selected lines and 2 local varieties for both 2017 and 2018 growing seasons 124 Figure 4.2. Cont’d 125 REFERENCES 126 REFERENCES Arsyad D.M., Adie M.M., Kuswantoro H. 2013. Soybean varieties breeding on specific of agroecology in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 205-228. In Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp-content/uploads/2016/03/dele_9.darman-1.pdf Ackerson J.P., 2018. Soil Sampling Guidelines. Purdue University Extension. Bulletin number AY-368-W. Link: https://www.extension.purdue.edu/extmedia/AY/AY-368-w.pdf Babou O.J., Shiow-Long Tsai, Zeng Y Hseu. 2007. Relationship between compost pH buffer capacity and P content on P availability in a virgin Ultisol. Soil Science Vol. 172 No. 1: 68- 85 Badan Stardarisasi Indonesia [BSN]. 2012. Tempeh: Indonesian gift to the world. Jakarta. In Bahasa Indonesia. Online source: http://www.bsn.go.id/uploads/download/Booklet_tempe- printed21.pdf Bantacut T. 2017. Soybeans development for food sovereignty, industrial, and economy. Journal of Food. Vol. 26 No. 1. pages: 81 - 96 Bojórquez-Quintal E., Escalante-Magaña C., Echevarría-Machado I., Martínez-Estévez M., 2017. Aluminum, a friend or foe of higher plants in acid soils. Front. Plant Sci. 8:1767. doi: 10.3389/fpls.2017.01767 Eviati and Sulaeman, 2009. Technical instructions on soil chemical, plant, water, and fertilizers analysis. Second edition. Published by the Indonesian Soil Research Institute of the Indonesian Agency for Agricultural Research and Development. Bogor. ISBN 978-602- 8039-21-5. In Bahasa Indonesia. Accessed May 10th, 2019. Link: http://balittanah.litbang.pertanian.go.id/ind/dokumentasi/juknis/juknis_kimia2.pdf Gillman J.H., Dirr M.A., Braman S.K., 1998. Effects of dolomitic lime on growth and nutrient uptake of Buddleia davidii 'Royal Red' grown in pine bark. J. Environ. Hort. 16(2):1l1-1I3. Hartman G.L., West E.D., Herman T.K., 2011. Crops that feed the World 2. Soybean— worldwide production, use, and constraints caused by pathogens and pests. Food Sec. (2011) 3:5–17 DOI:10.1007/s12571-010-0108-x. Link: https://naldc.nal.usda.gov/download/48661/PDF Haynes, R.J. and Naidu, R. 1998. Influence of lime, fertilizer and manure application on soil organic matter content and soil physical conditions: A review. Nutrient Cycling in Agroecosystem: 51, 123-137 127 Kamprath E.J., 1984. Crop Response to Lime on Soils in the Tropics. ASA-CSSA-SSSA, 677 South Segoe Road, Madison, WI 53711, USA. Soil Acidity and Liming-Agronomy Monograph no. 12 (2nd Edition). Krisnawati A. and Adie M.M. 2015. Selection of soybean genotypes by seed size and its prospects for industrial raw material in Indonesia. Procedia Food Science 3. Pages: 355 – 363. doi: 10.1016/j.profoo.2015.01.039 Kristanto H., Arsyad D.M., Purwantoro. 2013. Acidic-dry land soybean characteristic. Cash crop Journal. Indonesian Agency for Agricultural Research and Development. No. 25-2013: 1–10. In Bahasa Indonesia Lyamuremye, F., Dick, R. P., Baham, J. 1996. Organic amendments and phosphorus dynamics in phosphorus chemistry and sorption. Soil Science 161(7):426-435 McCauley A., Jones C., Olson-Rutz K., 2017. Soil pH and organic matter. Nutrient management module No. 8 (4449-8). Montana State University Extension. Link: http://landresources.montana.edu/nm/documents/NM8.pdf Ministry of Agriculture Republic of Indonesia. 2015. Strategic plan on 2015-2019 period. Link: http://www1.pertanian.go.id/file/RENSTRA_2015-2019.pdf Mulyani A., Rachman A., Dairah A., 2009. The spread of acidic-soil: potential and availability for agricultural development in Rock-phosphate: utilization of rock-phosphate as phosphate nutrient source. Pgs: 25-46. In Bahasa Indonesia Osaki M., Watanabe T., Tadano T., 1997. Beneficial effect of aluminum on growth of plants adapted to low pH soils. Soil Science and Plant Nutrition, 43:3, 551-563, DOI: 10.1080/00380768.1997.10414782. Link: https://doi.org/10.1080/00380768.1997.10414782 Pagani A. 2011. Soil pH and lime management for corn and soybean. Dissertation. Iowa State University. Ames, Iowa Rochayati and Dariah. 2012. Acidic dry-land development: opportunities and challenges in Dry- land agriculture prospect in supporting food security. Indonesian Agency for Agricultural Research and Development (IAARD). Jakarta. pg. 187-206. Link: http://www.litbang.pertanian.go.id/buku/Lahan-Kering-Ketahan/BAB-III-6.pdf Rachman A, Subiksa IGM, Wahyunto. 2007. Soybean planting area development to sub-optimal land in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg.185-203 128 Saliem H.P. and Nuryanti S. 2011. The global economic perspective of soybean and cassava to support food self-sufficient. National seminar on the result of a variety of beans and tubers. Malang. Indonesia. in Bahasa Indonesia. Link: http://balitkabi.litbang.pertanian.go.id/wp- content/uploads/2012/09/01_SET_Handewi-1.pdf SAS, 2012. SAS Institute Inc., version 9.4 Enhanced logging facilities, Cary, NC, USA. Sidharta, Myra. 2008. Soyfoods in Indonesia in the world of soy. University of Illinois Press. Urbana and Chicago. pg. 195-207. ISBN: 9780252033414 Sudaryanto and Swastika. 2007. The Economic of soybean in Indonesia in in Soybean: production and development. Indonesian Agency for Agricultural Research and Development. pg. 1-27. In Bahasa Indonesia Susanti and Waryanto. 2017. Statistic of agriculture 2017. Published by Center for Agricultural Data and Information System Ministry of Agriculture Republic of Indonesia ISBN : 979- 8958-65-9 Uguru M.I, Oyiga B.C., Jandong E.A. 2012. Responses of some soybean genotypes to different soil pH regimes in two planting seasons. The African Journal of Plant Science and Biotechnology. Vol 6(1). Pages: 26-37. Whalen J.K., Chang C., Clayton G.W., Carefoot J.P., 2000. Cattle manure amendments can increase the pH of acid soils. Soil Sci. Soc. Am. J. 64:962–966. Link: https://dl.sciencesocieties.org/publications/sssaj/pdfs/64/3/962 Wiesmeier M., Urbanski L., Hobley E., Lang B., Lützow M., Marin-Spiotta E., Wesemael B., Rabot E., Ließ M., Garcia-Franco N., Wollschläger U., Vogel H-J., Kögel-Knabner I., 2019. Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales. Geoderma Vol. 333. Pages 149-162. https://doi.org/10.1016/j.geoderma.2018.07.026 Yulnafatmawita, Detafiano D., Afner P., Adrinal, 2014. Dynamics of physical properties of Ultisol under corn cultivation in wet tropical area. International Journal on Advanced Science Engineering Information Technology. Vol.4 (2014) No. 5. ISSN: 2088-5334. Yusuf A. and Harnowo D., 2012. Soybean technology supports tntegrated plant management. Published by the North Sumatera Assessment Institute for Agricultural Technology. Link: http://sumut.litbang.pertanian.go.id/ind/images/DokumenPdf/Brosur/SLPTT%20kedelai,%2 0brosur%20buku.pdf 129 CHAPTER 5. CONCLUSIONS AND FUTURE DIRECTIONS Conclusions This present study was intended to support the Indonesian soybean breeding program by broadening the number of accessions that are tolerant to acidic soils and has larger seed size to increase production areas and meet the market demands. Initially we screened 706 soybean accessions originating from the USA, China, and Brazil in a medium with pH 5.0 and selected 60 best performing accessions based on plant height and number of days taken to reach V2 stage. Of the 60 genotypes, the 20 selected lines from USA and the 20 selected lines from China reached the V2 stage in 12 - 24 days after planting while the 20 selected lines from Brazil took slightly longer to reach the V2 stage with 16 - 30 days after planting. In the second phase of the present study, 20 best performing lines out of the previous 60 were selected based on their performance on acidic soils under three pH levels of 4.5, 5.0, and 5.5. The 20 selected accessions with better performance on either two or all three of the pH levels based on plant height and root length are PI628871, PI628962, PI567611, PI556744, PI556727, PI615695, PI628925, PI567779A, PI556537, PI628842, PI594922, PI556515, PI590932, PI628929, PI628880, PI567410C, PI567643, PI556612, PI675661, and PI556564. The next phase of the present study was conducted to evaluate the responses of the 20 selected soybean lines obtained in the previous study to aluminum (Al) toxicity, which is a major limiting factor for soybean production in Indonesia in areas with low pH. We found that plant height and root length of the 20 lines were higher in the medium with 5% Al compared to the control with 0.0% aluminum. Of the 20 lines tested, PI628871 accession had the longest root length and PI567643 accession had the highest plant height. When comparing the initial and final 130 pH levels of the growth medium, we observed a positive effect of adding Al to the growth medium as it increased the pH of the medium from 4.30 to 5.28. Moreover, we assumed the amount of Al given to the medium was not high enough to cause a toxic effect to the soybean plants. As reported by some researchers, the presence of Al in low concentrations would be beneficial to the plant by stimulating the root growth. The results also indicated that the 20 selected lines would be tolerant to soils with low pH and Al3+ levels up to 5% (by weight) and thus, could perform well under Indonesian acidic soils. With the results obtained from the greenhouse experiments at Michigan State University, the 20 selected lines were then tested in low pH Ultisols soils in Indonesia for two growing seasons in 2017 and 2018. Given that depending on the resources farmers often lime the soil and/or add organic matter to improve the quality of low pH soils before planting soybeans, our experiments tested the 20 selected lines in four conditions; 1) without the addition of lime or organic matter, 2) addition of lime but no organic matter, 3) addition of organic matter but no lime, and 4) addition of both lime and organic matter. The experiment was conducted as a split- split plot design with three factors including lime as the main plot, organic matter as the sub plot and the 20 soybean lines as the sub-sub plot. The Table 5.1 summarizes the best performing lines under the four conditions tested. Future Directions Identifying some promising soybean lines that would perform well in acidic soils using the present study was the first step we embarked on to support the government’s efforts of increasing soybean production in Indonesia. The recent information from IAARD indicated that other scientists also have been working to improve characteristics of existing soybean varieties 131 with regards to tolerance to soil acidity and seed size. Therefore, the present research contributes to enriching the diversity of soybean lines tolerant to acidic soils in Indonesia. In addition, the fact that farmers were interested in some of the 20 accessions we tested in the field shows promise that these lines may have value for adoption as new varieties. A flowchart in Figure 5.1 provides a comprehensive overview of the future directions that can be laid out. The boxes with light shading are part of the national efforts in increasing soybean production. The boxes with dark shading show the work that has been completed during the present study. The white boxes outline the future directions. The two promising lines obtained from this study, PI675661 and PI628929, can be submitted for release through the Ministry of Agriculture (MoA) of Republic of Indonesia's variety release-procedure. While following this procedure, PI628925, another promising line, would be improved through breeding to increase pod number and seed size. In doing this work, we would work together with a soybean breeder from the Indonesian Legume and Tuber Research Institute. In addition, we would identify farmers who would be interested in further testing the promising lines in their fields with acidic soils to increase soybean production and use the produce to develop soy-based foods. To do this, we would work with local government, farmers, and soybean-based food industries. 132 APPENDIX 133 Table 5.1. The best performing soybean lines in both 2017 and 2018 growing seasons Season Line* Yield (tones/ha) Farmers practiced Organic Liming fertilization Remarks PI675661 3.08 Yes No Higher no. of pods, higher yield, larger seed size 2.46 No Yes Higher yield, seed size larger than DERING, PI628880 2017 2.03 No No Higher yield, seed size larger than DERING, PI628871 2.32 Yes Yes Higher yield, seed size larger than DERING PI628929 2.28 Yes No PI628925 2.38 Yes Yes 2018 Higher no. of pods, higher yield, larger seed size Farmers prefer the plant height (40-50 cm), few pods compared to PI75661 and PI628929 PI675661 2.17 No Yes Larger seed size than locals, higher no of pods * All lines mentioned here reported the yield more than the control varieties tested. 134 Figure 5.1. Future directions of the present study. The white boxes indicate the future directions with respect to the government work (grey boxes) and accomplishments of the present study (black boxes). 135