MSU RETQRNING MATERIALS: Place in book drop to LIBRARIES remove this checkout from “ your record. FINES win — 7 be charged if book is returned after the date stamped below. SJHULATION MODEL ANALYSIS OF NACHINEY SELECTION FOR COLLECTIVE EJIDOS IN MEXICO By Omar Ulloa A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements For the degree of DOCTOR OF PHILOSOPHY in Agricultural Engineering Technology Department of Agricultural Engineering 1987 ABSTRACT Simulation Model Analysis of Machinery Selection for Collective EJidos in Mexico. by Omar Ulloa Collective eJidos located in the Yaqui Valley in Sonora, Mexico have high investment in agricultural machinery, but no studies have been made relative to the technical and economical performance of machinery. This dissertation is focused on the application of a computer model, developed at the Agricultural Engineering Department, Michigan State University, to the simulation of field and economic performance of agricultural machinery for wheat, soybean and cotton production. Data for definition of main parameters were collected in the Yaqui Valley, in order that the model be representative of the eJidos. Model validation was carried out through sensitivity analysis of the model to changes in maJor parameters, and in comparisons of simulated with actual machinery sets owned by the eJidos. After vaiidatidn the model was applied to select least cost machinery sets for five crop rotations under conventional and reduced tillage systems, and to compare custom hired vs. owned machinery. The main conclusions of the study were as follows: Agricultural machinery management and repair were the most important and urgent topics that needed research, training and technical assistance. This was indicated by eJidatarios, technicians and eJido leaders. The machinery selection model, MACHSEL, proved to be effective to simulate agricultural machinery systems for wheat, soybean and cotton production in the Yaqui Valley. The sensitivity analysis showed reasonable reactions to changes in size, type of soil, rotations, probability of suitable days, and economic parameters. The eJidos own more power and machinery than required for least cost at the 0.8 probability level. Cost savings of up to 21.41 could be obtained for a 300 hectare H-S rotation, reducing tillage operations with no yield decrease. The reduced tillage system reduced total cost per hectare by 18.21 as compared with conventional tillage on a 600 hectare H—S-C crop rotation. Custom hiring machines was a common alternative in the Yaqui Valley. If the eJldos had to pay full prices for their machinery purchases, savings of up to 311 could be obtained by custom hiring cotton pickers and combines. when the real cost of machines declines, due to interest rates below inflation, custom hiring will not be cost effective. The validated computer model is applicable to Mexico for teaching and technical assistance related to agricultural machinery management. a Approv Jor P ofessor //“ , ,//" , Approvedagz?1utJéz2;;Z;ééir 2Zi2%k§:;,. Department Chairman Dedicated to: "Y wife Marina "Y daughters Claudia Vanessa Maria Soledad Valentina Isabel ACKNOWLEDGMENTS The author wishes to express his sincere gratitude to the following: Dr. Merle L. Esmay, the author's maJor professor and committee chairman, for his invaluable guidance during the graduate program, and for his editorial help while writing this manuscript. Dr. C. Alan Rotz for his guidance with the cemputer model, and his editorial help while writing the manuscript. Drs. Robert Stevens and Robert Nilkinson, who served on the author's guidance committee, and for their editorial help while writing the manuscript. Ing. Agustin Cruz-Aicala for coordinating the collaboration of CRUNO and Coalition, for data collection in the Yaqui Valley. The Regional Center of the Northwest and the Agricultural Machinery Department of the University of Chaplngo, and the Coalition of Collective EJidos, for their support for the research project. Claudia and Soledad for their help in typing the manuscript. LIST OF LIST OF Chapter TABLE OF CONTENTS TABLES FIGURES 1. INTRODUCTION 1.1. 1.2. 1 .3. PROBLEM STATEMENT RELEVANCE OF THE TOPIC THE STUDY AREA 2. OBJECTIVES 3. LITERATURE REVIEH 3.1. 3.5. 3.6. AGRICULTURAL OVERVIEW OF MEXICO 3.1.1. Land 3.1.2. Main Crops 3.1.3. Labor AGRICULTURE IN THE STATE OF SONORA 3.2.1. General Overview 3.2.2. The Yaqui Valley AGRICULTURAL MECHANIZATION IN MEXICO 3.3.1. Existence of Machinery 3.3.2. Machinery Manufacture 3.3.3. Agricultural Machinery in the State of Sonora CROP PRODUCTION SYSTEMS IN THE YAOUI VALLEY 3.4.1. Nheat Production 3.4.2. Soybean Production 3.4.3. Cotton Production COLLECTIVE EJIDOS IN THE YAOUI VALLEY SYSTEMS APPROACH FOR AGRICULTURAL MACHINERY SELECTION 3.6.1. Systems Approach 3.6.2. Information Requirements for Machinery Selection 3.6.3. Data Collection for Agricultural iv viii xiii d deb 0°“ 0 m ‘1 $70" a N a» “J” 16 17 20 20 22 24 27 30 31 34 34 36 Machinery Selection 4.DATA COLLECTION 4.1. 4.2. TYPE OF DATA AND PROCEDURES J-A I EhrzrwdEeN-L J a QIDJIJ“¥HD"‘ 3 AGRICULTURAL MECHANIZATION TRAININGS, Type and Source of Data Collected Preliminary Activities .1. Rapid Appraisal 2. Training Course .2 2. . Data Collection and Procedure .3.1. 3 .3 3. Type and Price of Machinery .2. Data Collection in Summer 85 3. Direct Measurements 4. Data Collection in May 86 Shortcomings of the Data Collection ASSISTANCE AND RESEARCH NEEDS 4.2.1. 4.2.2. EJIDO 4.3.1. 4.3.2. 4.3.3. 4.3.4. 4.3.5. 4.3.6. Training Needs Technical Assistance Needs Agricultural Machinery Research Needs AND CROP PRODUCTION DATA EJido Size Parcel Size Crop Rotations Crop Area and Yield Crop Production Systems Horkable Days AGRICULTURAL MACHINERY IN COLLECTIVE EJIDOS 4.4.1 . 4.4.3. Inventory of Agricultural Machinery Experience in Agricultural Machinery Responsibles for the Machinery Horking Days Operator Hages Programming of Machinery Operations Purchase of Machinery Custom Hired Operations MACH I NERY PARAMETERS 4.5.1. 4.5.2. 4.5.3. 4.5.4. 4.5.5. 4.5.6. Duration of Machinery Resale Value Annual Use of Machinery Failures & Repair Costs Speed, Field Capacity, Efficiency of Machinery Draft Force Measurements and Field V TECHNICAL 39 39 4o 40 4o 41 41 41 41 42 43 45 45 47 47 49 49 52 61 61 61 64 64 66 67 69 69 70 70 71 72 73 ‘.7. 4.8. 4.9. 5. 5.1. 5.2. 5.3. 5.4. 6. 6.1. 6.2. 6.3. AGRICULTURAL MACHINERY AVAILABLE IN THE YAOUI VALLEY 4.6.1. 4.6.2. 4.6.3. 4.6.4. 4.6.5. Agricultural Machinery Manufacture Agricultural Machinery Dealers Available Sizes and Prices of Equipment Custom Hire Machinery Services Price of Custom-Hired Operations ECONOMIC PARAMETERS 4.7.1. 4.7.2. 4.7.3. 4.7.4. General Inflation in Mexico Credit Loans for Agricultural Machinery Purchases Price of Machinery Price of Fuel and Hages DISCUSSION OF RESULTS OF DATA COLLECTION DATA USED IN THE COMPUTER MODEL DESCRIPTION OF THE MODEL AND ASSOCIATED FILES MACHINERY SELECTION MODEL MICROCOMPUTER VERSION OF MACHSEL INPUT DATA FILES 5.3.1. Machinery Data Files 5.3.2. MODEL Rotation Files ASSUMPTIONS MODEL VALIDATION SENSITIVITY ANALYSIS 6.1.1. 6.1.2. 6.1.3. 6.1.4. 6.1.5. Probability of Suitable Heather EJido Size Rotations Soil Type Economic Parameters SIMULATED VS. ACTUAL MACHINERY SETS DISCUSSION OF MODEL VALIDATION 7. SIMULATION RESULTS 7.1. COPARISMS FOR TILLAGE SYSTEMS vi 73 73 75 75 76 76 77 77 79 79 82 87 90 90 92 94 102 105 110 110 110 114 117 123 123 126 129 132 132 7.2. CUSTOM HIRED OPERATIONS 7.2.1. Owned vs. Custom Hired Operations 7.2.2. Custom Hired vs. Owned with Negative Interest Rates 8. CONCLUSIONS 8.1. CONCLUSIONS 8.2. RECOMENDATIONS FOR FURTHER RESEARCH APPENDIX A APPENDIX 8 APPENDIX C REFERENCE vii 138 138 141 145 145 147‘ 149 154 161 193 Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11 3.12 3.13 3.14 3.15 3.16 3.17 4.1 LIST OF TABLES Area Seeded From 1979-1983 in Million metres I I I I I I I I I I I I I I I I I Land Tenure in Mexico. . . . . . . . . . . Land Tenure in Irrigation Districts 1 975/1 976 I I I I I I I I I I I I I I I I I Crop Area, Yields and Value of Production in Mexico. . . . . . . . . . . . . . . . . Economically Active Population in Primary Sector, Mexico . . . . . . . . . . Irrigation Districts and Land Distribution in the State of Sonora. 1980 . . . . . . . Main Crops in the State of Sonora. ‘979/1980I I I I I I I I I I I I I I I I I Existence of Agricui turai Machinery in Tractors and Laborabie Land on Main Regions in Mexico. 1981. . . . . . . . . . Existence of Machinery in Irrigation Districts by Regions . . . . . . . . . . . Existence of Small Implements and Animal Drawn Plows, by Regions. . . . . . . . . . Tractor Manufacture & Imports in Mexico. ‘966 to 1980 I I I I I I I I I I I I I I I Machinery in the Yaqui Valley (Irrigation DI Btf‘I Ct 41 ) ‘ 984-85 a a e e e a e e a e e Harvested Area, Production and Value of Crops. Yaqui Valley. Sonora, Mex. 1980/81 Rotations in the Yaqui Valley. . . . . . . 11 11 13 14 18 19 19 21 21 23 I 25 Bi Timeliness Cost for Planting and Harvesting in the Yaqui Valley. . . . . . . . . . . . 26 Changes in Area and User in the Yaqui Valley (in Percent) . . . . . . . . . . . . . . . 33 List of EJidos Selected for Data Collection 44 viii Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.14 4.15 4.16 4.17 4.18 4.19 Relative Importance, Priority and Urgency of Agricultural Machinery Research Topics in Collective EJidos . . . . . . . . . . . Crop Rotations Used in Collective EJidos . Area and Yield of Hheat in Collective EJidos of the Yaqui Valley . . . . . . . . Area and Yield of Soybean and Cotton in Collective EJidos of the Yaqui Valley. . . Operation and Dates for Hheat Production in Collective EJidos of the Yaqui Valley . Operation and Dates for Soybean Production in Collective EJidos of the Yaqui Valley . Operation and Dates for Cotton Production in Collective EJidos of the Yaqui Valley. ‘985 I I I I I I I I I I I I I I I I I I I Number of Passes and Cases Reported for Field Operation on Hheat, Soybean and Cotton in Collective EJidos. . . . . . . . Operations and Number of Passes for Hheat, Soybean and Cotton Production in Collective EJidos of the Yaqui Valley. . . Agricultural Machinery in Collective EJidos. Yaqui Valley, Sonora, Mexico. . . Range of Horklng Hours per Day . . . . . . Payments for Tractor Repair. . . . . . . . Operating Speeds in Collective EJidos. . . Prices for Custom-Hired Services in the Yaqui Valley. April, 1985 . . . . . . . . Percent of Inflation in Mexico . . . . . . Interest Rates for EJldos for Credits to Purchase Machinery . . . . . . . . . . . . Price Variations of Tractors. Mex. Pesos x 1 000 I I I I I I I I I I I I I I I I I I Price Variations of J. Deere Machinery, Aug. 80 - May 86. Thousand of Mexican Pesos. . . . . . . . . . . . . . . . . . . 48 51 53 53 57 58 59 60 62 65 74 74 78 80 80 81 81 Table 4.20 Price Variation for Implements. Thousand MexicanPesos.............. 83 Inflation and Price Variation for Implements. Sept. 81 - May 86 . . . . . . Table 4.21 83 Price of Fuel. January 1985 to September 1986. Mexican Sliiter . . . . . . . . . . Table 4.22 84 Table 4.23 Minimum Hages per 8-hour Day in Mexican Table Table Table Table Table Table Table Table Table Table Table Table 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6.1 6.2 6.3 Pesos. Yaqui Valley . . . . . . . . . . . 84 Soybean Valley. Equipment and Sizes Used for Hheat, and Cotton Production in the Yaqui 93 Non-Suitable Days as Determined by Daily Precipitation. . . . . . . . . . . . . . . 98 Number or Non-Suitable Hork Days Caused by a One-Day Rain for Clay Soil. . . . . . 99 Number of Non-Suitable Hork Days Caused by a One-Day Rain for Loam Soil. 100 Maximum Delay (days) Due to Heavy Rains DuringTwoorMoreDays. . . . . . . . . .101 Suitable Days Each Heek of the Year at Three Probability Levels for Clay and Loam Soil. YWI v.“°y I I I I I I I I I I I I . I I 103 Recommended Dates for Hheat After Soybean Field Operations . . . . . . . . . . . . . 106 Recommended Dates for Soybean After Hheat Field Mat‘MI I I I I I I I I I I I I I 107 Recommended Dates for Field Operation for Cotton Production After Soybean. . . . . . 108 Machinery Selection for Three Levels of Probability for Suitable Heather for 300 Ha Hheat-Soybean Rotation with Conventional Tillage on Clay Soil . . . . . . . . . . . 112 Machinery Selection for Three Levels of Probability for Suitable Heather for 300 Ha Hheat-Soybean Rotation with Reduced Tillage on Clay Soil . . . . . . . . . . . . . . . 113 Machinery Selection for Three Probability Levels for Suitable Heather for 600 He Table Table Table Table Table Table Table Table Table Table Table Table 6.4 6.5 6.6 6.7 6.8 6.9 6.10 7.1 7.2 7.3 7.4 Page Hheat-Soybean Rotation with Conventional Tillage on Clay Soil . . . . . . . . . . . 115 Effect of Size, Soil Type and Tillage System Upon Machinery Cost ( Thousand Max. 4 > for Hheat-Soybean Rotation, at 0.8 Probability Level. . . . . . . . . . . . . . . . . . . 116 Machinery Selected for Four EJldo Sizes for Hheat-Soybean Rotation, with Conventional Tillage, on Clay Soil, at 0.8 Probability Level. . . . . . . . . . . . . 118 Machinery Selected for Four EJido Sizes for Hheat-Soybean Rotation, with Reduced Tillage, on Clay Soil, at 0.8 Probability Level . . 119 Machinery Selected for Five Crop Rotations for 300 Ha at 0.8 Probability Level, Using Conventional Tillage on Clay Soil. . 121 Machinery Selected for Five Crop Rotations for 600 Ha at 0.8 Probability Level, Using Conventional Tillage on Clay Soil. . 122 Machinery Selected for Two Soil Types 600 Ha Hheat-Soybean Rotation Using 1 Conventional Tillage at 0.8 Probability Level. . . . . . . . . . . . . . . . . . . 124 Machinery Selection with Three Interest Rates. H-S Rotation, 600 ha with Conventional Tillage on Clay Soil. . . . . 125 Simulated vs. Actual Machinery Sets at 0.8 Probability Level. Hheat-Soybean Rotation, Using Conventional Tillage on Clay Soil. . 130 Machinery Selected for Two Ti l lage Systems for a Hheat-Soybean Rotation on Clay Soil. 133 Machinery Selected for Two Tillage Systems for a Hheat-Soybean-Cotton Rotation on C‘ay sci‘I I I I I I I I I I I I I I I I I 136 Machinery Selected for Hheat-Soybean and Hheat-Soybean-Cotton Rotation for a Large EJido 1200 ha, with Two Tillage Systems on Clay Soil . . . . . . . . . . . . . . . Custom Hired Operations vs. No-Custom xi Table 7.5 Table 7.6 Table 7.7 Hire, for 300 Ha of Hheat-Soybean-Cotton Thousand of Max t/ha . . . . . . . . . . Custom Hired Operations vs. No-Custom Hire, for 600 He of Hheat-Soybean-Cotton Cost of Machinery Sets with Negative Interest Rates in Thousand Mexican 4/Ha. Comparisions of Custom Hired Mixtures at Three Interest Rates. Thousand of “X ‘ can 4/ha I I I I I I I, I I I I I I I xii 140 140 143 143 Figure 1.1 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 4.1 Figure 4.2 Figure 5.1 Figure 5.2 LIST OF FIGURES Location of Place of Study . . . . . . . . Operation Schedules for Hheat, Soybean and Cotton Production in the Yaqui Valley. . . Date of Seeding and Yield for Hheat Production . . . . . . . . . . . . . . . . Seeding Dates and Yields for Soybean Prmt i on I I I I I I I I I I I I I I I I Organigram Coalition of Collective EJidos. Distribution of Sizes of Parcels in Collective EJidos. . . . . . . . . . . . . Percent of Total Area Seede with Hheat, Soybean and Cotton in Collective EJldos. . Flow Chart of Mbdlfied Program MACHSEL.. . Flow Chart for Suitable Days Program . . . xiii 26 29 29 33 51 54 91 97 CHAPTER 1 INTRODUCTION 1.1. PROBLEM STATEMENT Agricultural machinery is an important component in Mexican agricultural production systems. This is particularly true in highly productive irrigated lands. MUch effort has been made by the Mexican Government to introduce agricultural machinery since the first tractor imports in 1918 (SARH, 1984). Technical support for those programs have been inadequate, due to lack of trained personal, and little research has been carried out on machinery selection and management. Approximately half of the agricultural land in Mexico is held by private owners, and half by eJldos or colonists (social property). The mechanization level indicator, of hp/ha, is higher for private farms than for social property. Organizational problems, small holdings and lack of education and/or training have been maJor obstacles for mechanization efforts in eJidos. The collective eJldo is one type of organization of social property. The eJldo is worked as a unit, which can Justify the ownership of some tractors and implements. Machinery repair, maintenance, and management problems in collective eJldos of the Yaqui Valley have been described by Cruz et ai. (1982). No other studies have been made to 1 2 better understand those problems. This dissertation is focused on the application of a computer model, to simulate field and economic performance of agricultural machinery in 45 collective eJidos, located in the Yaqui Valley, in South Sonora, Mexico. Main goals were to analyse the applicable types of machines, methods, field performance and operating costs of agricultural machinery and identify the best agricultural machinery sets. Data for definition of parameters were collected in the Yaqui Valley in order that the model be representative of the eJidos. Data were collected from measurements, interviews and surveys. One reason for selecting the Yaqui Valley was the interest of the parties involved. This resulted in good facilities, and resources for collaboration. Another reason was the large parcels of land with similar types of machinery to those used in the United States. This facilitated the application of a computer model developed at Michigan State University. Another important consideration was that shortly after their creation, the eJidos were organized in a Coalition. For the purposes of the study the Coalition facilitated the gathering of required information. 1.2. RELEVANCE OF THE TOPIC The Yaqui Valley is one of the most productive irrigated regions in Mexico, and the collective eJidos are a significant sector in the Valley. The eJldos have high 3 investment in agricultural machinery, but no studies have been made relative to the technical and economical performance of the machinery. Hith the availability of computer hardware and software in developed countries, it was considered desirable to evaluate the appropriateness of using computer models in devei0ping countries. There is interest in determining their usefulness for planning, research and teaching purposes, and to determine the modifications that will be required for their use. Fifty collective eJidos associated with the Coalition of Collective EJidos of the Yaqui and Mayo Valleys owned 353 tractors, 90 combines, 142 disk plows, 195 offset disk barrows, 172 planters, and 57 sprayers (Ulioa, 1985). EJido leaders and technicians have complained of high repair and maintenance expenses, and use problems with machinery. Finding appropriate solutions could mean significant savings and lower production costs for eJidos. The study is the first one of its kind in the region, and thus a pilot study. Results will be useful for agricultural extensionists, farmers and eJldatarios. For the University of Chaplngo, it means a new line of regional research in agricultural machinery management envolving collaboration of faculty, students, local institutions and eJidatarlos. The methodology could be applied for similar studies in other regions, furthering agricultural mechanization research in Mexico. 4 1.3. THE STUDY AREA The Yaqui Valley is located between 27° 00' to 27° 40' latitude North, and from 109° 45' to 110° 20'iongitude. It is on the Pacific coast, South of the State of Sonora, in the Northwest of Mexico (See Figure 1.1.). The main city, Cludad Obregon, with 250,000 inhabitants, is 1,750 km from Mexico City. Climate is desertic, with minimum temperatures of one degree Centigrade in December and January and maximum of 44 degree Centigrade during July and August. The average annual rainfall is 300 mm. (SARH, 1984). The Valley, with 226,000 irrigated hectares is the largest irrigation district in the state of Sonora, and one of the most modernized production zones in the country (Freebairn,1977). The area is very level, at an average of 30 m. above sea level. Agriculture is mostly commercial cash crops produced with powered machinery. Animal traction is not used in the Valley. Hheat, the main crop, amounted to 251 of national production in 1970 (Freebairn, 1977). Soybeans and cotton were the next two main crops. EJidos are the most important sector in the agriculture of the Valley with holdings of 121,372 irrigated hectares (Castaflos, 1982). The 'eJido' is an agrarian community that received and held land under Mexico's agrarian reform of 1917. From 1915 to 1969 aproximately 75 million hectares were organized into eJidal lands, with about 2,800,000 beneficiaries (Freebairn,1977). The eJidos could be. worked by individual parcels or collectively >9su 00 1.0.... 00 250‘ 0839 U H n— — 0(a- ouaen «a 00 u XNE no “—438 3:959:95 >0— p0) pafl> \ >u.o coo0Loo.MWLu:r. ’ END ..~\.\v . COOULDD . . . (KO-com / no mb Xi , where: j i=1 Includes but is greater than x1 = A methodology for planning and management. X2 A multidisciplinary team. X3 = Organization. X4 8 Mathematical modeling techniques. 35 X5 Disciplined non-quantitative thinking. X6 3 Simulation techniques. X7 = Optimization Techniques. X8 Application of computers. Simulation usually refers to a computer program or other functioning model that represent a system of different design and management strategies. Optimization refers to maximizing or minimizing some criterion of performance of the system while satisfying other constraints of a physical or social environmented nature (Manetsch and Park, 1977). MaJor phases of the systems approach are: (1) feasibility evaluation: (2) abstract modeling: (3) implement design; (4) implementation: and (5) system operation. Feasibility evaluation is a critical phase, aimed towards the generation of a set of feasible system alternatives,g capable of satisfying identified needs. Abstract modeling has as its output, the broad specifications for a system design and/or management strategy to be implemented in the real world. Implementation design completely specifies the details of system and/or management strategy. Implementation is to give physical existence to the desired system. Operation is the only valid test of the system's adequacy. Application of system analysis to agricultural engineering problems are summarized by Hetz (1982). Esmay (1974), described an applicable system analysis approach and proposed a flow for development of a standarized approach 36 for engineers involved in feasibility studies. Farm machinery is a maJor subsystem of the agricultural production system. Rumsey, Gantz and Chancellor (1986), pointed that a great body of generic and situation-specific literature exists concerning the optimization of cost-effectiveness of farm machinery. Holak (1981), Muhtar (1982) and Rotz et al. (1983), discussed four methods of approach for selection of machinery requirements and associated costs: (1) enterprise budgets and custom hire rates, (2) whole farm profit maximizing with linear programming models, (3) least cost models which seek a minimum machinery cost complement for a given management structure, and (4) heuristic models for selecting multiple interprise machinery sets. 3.6.2. Information Requirements for Machinery Selection Machinery selection information may be generically categorized into three areas: (1) machinery data, (2) environmental data, and (3) economic data (Rumsey, Gautz and Chancellor, 1986). Four maJor blocks of information for machinery selection were identified by Rotz and Black (1985) as: (1) farm parameters, (2) crop and weather parameters, (3) machine parameters, and (4) economic parameters. The availability and accuracy of data, and the sensitivity of the model to changes in the data were further discussed by Rotz and Black (1985). Farm parameters included size or total land area, crop rotation, and predominant soil type. 37 Timeliness cost and suitable work time available during the working season are main crop and weather parameters. Timeliness data are usually obtained from experiment stations. Suitable work days are difficult to obtain, because records have not been- kept. Computer simulation has been used for generation of suitable work day probabilities from weather data for a specific location (Rosenberg et al., 1982: Hetz, 1982). Machinery parameters required for a computer model simulation included commercial sizes available, field efficiency, field speed, and power requirements (Rotz and Black, 1985), Hunt (1977), Bowers (1975). Machinery sizes are obtained from manufacturers or dealers of farm equipment. Machinery performance data may be obtained from direct measurements or from publications, such as: machinery text books, extension bulletins and the Agricultural Engineers Yearbook. Economic parameters include: initial cost of machinery: tax benefits: interest, discount and inflation rates: remaining values of machines: and fuel and labor prices. Rumsey, Gautzand and Chancellor (1986) pointed that in reality, generic information for machinery, environmental and economic data are often used, due to lack of machine-site, and crop specific information. 38 3.6.3. Data Collection for Agricultural Machinery Selection Machinery operation data should be obtained by direct measurements for the most releabillty. Other methods include farm surveys and gathering published information. Information is the foundation upon which research is based. Published date are considered to be secondary data: any data generated by the researcher are primary data (Andrews and Hilderbrand, 1976). Any observation or investigation of the reality about a situation may be called a survey (Ferber et al., 1980). Data collection methods are described an/or analyzed by various authors. Dillon and Hardaker (1980) indicated that there are three methods by which farm survey data can be gathered: (1) direct observation, including measurements; (2) interviewing respondents: and (3) records kept by respondents. Data collection is almost always an expensive operation (Casley and Lury, 1981). Paucity of resources for data collection in developing countries is pointed to by Zarkovich (1983). Under such conditions, efficiency becomes a serious problem. Rapid rural appraisal could be a starting point for data collection (Chambers, 1981). Sample data collection is widely accepted as a means of providing statistical data (Kaiton, 1985). Types of sampling, their advantages and disadvantages, are discussed by Dillon and Hardaker (1980), Ferber et al. (1980), Kalton (1985), Bullmer (1983), and Casley (1981). The most critical phase in data collection is that period during which data are actually collected (Bullmer, 1983). CHAPTER 4 DATA COLLECTION 4.1. TYPE OF DATA AND PROCEDURE The Yaqui Valley crop production conditions were identified in order to obtain main parameter values for the computer model. These existing characteristics of the eJidos (area, crops, rotations, type of soils, operations schedule, suitable days,etc.) were used to validate the model. A data collection process was carried out in the Yaqui Valley, in March 85 (2 weeks), July 85 (4 weeks), August and December 85 (one week) and May 86 (3 weeks) for the purpose of obtaining such information. 4.1.1. Type and Source of Data Collected Data were collected to obtain the information required by the computer model, as specified by Rotz and Black (1985). Crop and weather data were obtained at CIANO (Agricultural Research Center of the Northwest) of the National Agricultural Research Institute of Mexico (INIA), from the Technical Area (Agric. Extension Service) of the Coalition of Collective EJidos of the Yaqui and Mayo Valleys (CECVYM), and from the eJidos. Machinery data were obtained from agricultural machinery dealers in Obregon City, from the eJidos, and 39 40 from custom-hired enterprises. The data included available sizes» and prices of machinery, speed, field capacity, efficiency, power requirements, operating cost, resale value and others. Economic information, such as; inflation, price of crops, labor and fuel, were obtained from the Credit Union of Coalition, from the eJidos, and from the Agricultural Economics Center of the Postgraduate College in Chaplngo. 4.1.2. Preliminary Activities 4.1;2.1. Rapid Agggaisal. The process of data collection was initiated with a rapid appraisal in May 1984. This consisted of a 7-day trip to the Yaqui Valley, to visit eJidos, private farms, agricultural machinery dealers, private and governmental custom-hired machinery enterprises, and the experiment station at CIANO. Questionnaires, prepared at CRUNO (Regional Center of the University of Chaplngo, for the Northwest) and Coalition were also tried during the initial visit to the eJidos. 4.1.2.2, Trgining course, A training and research proJect was submitted for approval to the Agricultural Machinery Department and Subdirectlon of Regional Centers of the University of Chaplngo, and to the Coalition. A training course on machinery maintenance for eJldatarios was done in September 1984. 41 4.1.3. Data Collection and Procedure 4.1.3.1. Type and Price of Machinery. The first activity in data collection was done in March 85. Information was collected on the type and prices of machinery commercialized in the Yaqui Valley, and about custom-hired machinery enterprises. A direct questioning procedure was used to obtain price lists on equipment from local dealers. 4.1.S.2. ata Collection in Summer 1985. The next stage of data collection was carried out during the summer of 85. A new questionnaire prepared at the Agr. Machinery Department of Chaplngo was used. A technician and 6 senior students of agronomy, assisted in visiting the 50 eJidos with Coalition. An inventory of machinery, was developed. The information obtained was summarized in Table 4.11. A survey on the management, use and problems with the machinery at the collective eJidos was also carried out during the summer of 86. Persons interviewed were work foreman, machinery foreman and ejldo authorities. The data obtained during summer surveys were processed and reported in December 85 (Ulioa, 1985). 4.1.3.3. Direct measurements. In August 85, two technicians from CRUNO and Coalition carried out measurements of speed and losses of cotton pickers, and in December the author made field measurements of sedbed preparation and seeding of wheat. The candidate returned to MSU, in January 86, for a period of one year. Preliminary field research results were 42 presented to the Guidance Committee in January. 4.1.3.4. ‘Data Collection ingfig¥:1986. The gathering of field data was completed during a trip to the Yaqui Valley in May 86 when harvesting of wheat and planting of soybeans were taking place. These are the most critical periods for machinery operations. In preparation for this stage of data collection, the course AEC 868, Data Collection in Developing Countries was taken at Michigan State University . The methodology considered elaborating questionnaires, selection and training of enumerators, pretest and data collection. The field work was carried out in the Yaqui Valley from May 12 to June 2, 1986, with the support of one agronomist of CRUNO and 4 enumerators hired for this proJect. The data collection work on the collective eJidos consisted of: a) A group interview about training, technical assistance, and research needs with respect to agricultural machinery. b) A survey on a sample of representative eJldos to obtain data on machinery management. c) Measurements of; operating speed, time losses and effective field capacity, and traction power requirements. The sample population for this study were 45 collective eJidos. Four eJidos located in the Mayo Valley, which was another irrigation district, were left out of the original list of 50; another eJido was left out because 43 it was no longer associated with Coalition. Inasmuch as the type and number of machines as well as the organization for use depended on the size of the eJidos, a stratified sampling was used. Five strata of 9 eJidos each was used. The first strata included the largest eJidos, and so on, down to the smallest in the last strata. Two eJidos were selected for each strata for measurements and 3 eJldos for interviews and survey. The eJidos selected were coded, with a Roman number representing the strata. The following digits 1 and 2 were assigned to those eJidos in which surveys, interview and measurements were carried out. The number 3 indicates that no measurements were made. The list of eJidos selected for this in depth studies is shown in Table 4.1. 4.1.4. Shortcomings of the Data Collection There were some limitations in the collection of agricultural machinery data. No previous studies had been made in the Yaqui Valley, and therefore no published information about machinery performance or management was available for this region. Most eJidos had not kept records on machinery use and management other than for accounting purposes. Only a few eJidatarios (authorities, work foreman, surveillance council) work the year round in the eJido. They are elected for 3 year periods and many of the records they kept were no longer with the eJldos. Most of the eJidos had ,eiected new authorities at the beginning 44 Table 4.1. List of EJidos Selected for Data Collection EJido EJido Name Code Ii Felipe Nerl I2 Yucuribampo I3 Ignacio Zaragoza Ill Bachomobampo II2 Genovevo de la 0 I13 San Jose Bacum III1 Belisario Dominguez III2 Estacidn Luis 1113 15 de Mayo IV1 Heroes de Cultaca IV2 Precursores de la Revolucldn IV3 2 de Abrii V1 Plano Oriente V2 Vicente Padilla V3 6 de Enero 45 of the year, thus this was a maJor problem. There was good collaboration and interest shown by the eJidatarios in a maJority of cases. The data obtained, although not as complete as desired, provided an adequate information base for the simulation‘ model validation and analysis. 4.2. AGRICULTURAL MECHANIZATION TRAINING, TECHNICAL ASSISTANCE AND RESEARCH NEEDS A group interview technique was used on 'collective eJldos of the Yaqui Valley in May 86. The group of eJidatarios interviewed at each eJido included one eJido authorithy, the work foreman or machinery foreman, and a machinery operator. The eJidatarios and technicians interviewed agreed that there were needs for training, technical assistance and research on general and specific aspects of agricultural mechanization. 4.2.1. Training Needs Of 15 groups interviewed, 12 responded that there was a need for agricultural machinery training in the collective eJidos. The main reasons given for the need were: the ejidatarios had low knowledge about machinery in seven cases, to do a better Job in seven cases, and the eJido needed more trained persons in seven cases. Only one eJido had requested a course to Coalition 46 to improve the training about machinery. Three eJidos had requested a training course to machinery dealers, and one to the technicians of Coalition. Two training courses for eJldatarios had been offered by the Agricultural Machinery Department of the University of Chaplngo. There were some questions asked about the reasons for the low attendance to these courses. Detailed answers are shown in Appendix A 4.2.2. Technical Assistance Needs The need for more technical assistance on agricultural machinery was expressed by 12 of 15 groups interviewed. The main topics indicated were: machinery repair by 13 groups, use of workshop equipment by 11 groups, studies on how the eJido is using the machinery by 10 groups, to keep records of expenses and to calculate operating costs by 10 groups. Nine groups would like to have assistance for machinery maintenance, and seven for selection of tractors and equipment for the ejido. 4.2.3. Agricultural Machinery Research Needs Eleven groups interviewed responded that research or studies were very important, and three that were important. The main reasons were: to know which equipment or new methods would be better for the eJidos in 11 cases, because the eJidatarios and technicians are awaiting research results in 9 cases. Six groups expressed that little was known on how the machinery was being used in the eJldo. 47 The groups interviewed were asked to assess the importance and urgency of seven research or study topics. The answers were weighted using the following scale: Very important or very urgent need : 10 points Important or urgent topic ' I 7 points Little important or little urgent : 3 points Not important or not urgent topic : 0 points The groups interviewed were asked which of the seven research topics should be studied in the first place, and so on, down to the seventh place for the topic with lower priority). The weights assigned to the answers were: Topic in first place: 20 points Topic in second place: 15 points Topic in third place: 10 points Topic in fourth place: 5 points Topic in fifth place: 3 points Topic in sixth place: 1 point Topic in seventh place: 0 points Management and repair of machinery resulted in the first places, when the aspects of importance, priority and urgency were considered together. Machine design and tillage methods resulted in the last places (See Table 4.2). 4.3. EJIDO AND CROP PRODUCTION DATA 4.3.1. EJido Size The size of eJidos varied form 19 to 1583 cultivable hectars. The most common sized were 101-400 hectares (25 48 Table 4.2. Relative Importance, Priority and Urgency of Agricultural Machinery Research Topics in Collective EJidos. Research topic Importance Priority Urgency Average Mach. Management 98 100 99 99 Mach. Repair 94 98 100 94 Operating costs 100 83 93 92 Machine shop 91 80 96 89 Calibration on mach. 91 78 88 86 Tillage methods 90 55 87 77 Machine design 87 45 77 70 Source: Group interviews in collective eJidos, Yaqui Valley, Son. Mexico, May 1986. 49 eJidos) and 401-1000 hectares (21 eJidos), with 2 eJidos less than 100 hectars and 2 eJidos over 1,000 hectars. 4.3.2. Parcel Size The size of parcels within the eJidos varied from 11 to 30 hectars (19 parcels) and from 76 to 100 hectares (13 parcels). Fifty percent of the parcels were less than or equal to 50 hectares, with decreasing percentage of medium (51-100 hectares) and large size parcels (over 100 hectares) as shown in Figure 4.1. The land was very level, with almost no obstacles (trees, stones). 4.3.3. Crop Rotations 1) Hheat-Soybean rotation was used in 12 of the eJidos surveyed, being the most important in 10, and second most important in the other two. 2) Hheat-Soybean-Cotton rotation was used in 7 of 13 eJldos, being the most important in one, and second most important in the other 6 eJidos. 3) Hheat-Maize-Cotton rotation was used in 7 of 13 eJldos, being the second most important in 3, and third most important in 4. 'Other rotations were wheat-sesame (4 eJidos), wheat-wheat (3 eJidos), . wheat-sorghum (1) and wheat-soybean-sorghum (1). (See Table 4.3). 50 0 /° 50 7. L40 27%, 2:7. 20 « SMALL iWEDunfl LAKGE O-SO SI-uoo . oven. iOI HAS Figure 4.1. Distribution of Size of Parcels in Collective EJidos. 51 Table 4.3. Crops Rotations Used in Collective EJidos. Crop Rotations Strata “-3 H- S-C H-l'l-C H-S-S H-H OTHERS I 3 2 2 1 1 0 II 2 0 3 1 0 1 III 2 2 0 1 0 0 IV 3 3 1 0 1 0 V 2 0 1 1 1 1 Total 12 7 7 4 3 2 Source! Survey in 13 eJidos of the Yaqui Valley, May 1986. H p| Hheat; S = Soybeans; C = Cotton Maize; 88 = Sesame 52 4.3.4. Crop Area and Yield In the Yaoui Valley there were two main croping seasons: The winter season, during which the main crop was wheat, and summer season, during which soybeans and cotton were the main crops. Hheat was' the main crop on the collective eJidos. The average area seeded From seasons 1981/82 to 1985/86 were 15,180 hectares per year, which represented 68! of the total cultivable hectares of the collective eJidos associated with Coalition. The average area with soybeans and cotton, from 1981 to 1985, were 13,238 hectars and 1,803 hectars per year, respectively, which represented 59! and 81 of the cultivable area of the collective eJidos (See Tables 4.4 and 4.5) The yields For wheat varied From 4.8 to 5.3 ton/ha, from 1.7 to 2.0 ton/ha for soybean, and from 2.0 to 2.28 ton/ha for cotton. Approximately 701 of the cultivable area in larger eJidos (strata I and II) was seeded with wheat, and 821 to 84! in medium and small ejidos. The area seeded with soybeans was less than the wheat area and varied from year to year because it depended on the water remaining in the Alvaro Obregon dam. The area seeded with soybean has been up to 47 to 58! of the total cultivable land on larger eJidos, and up to 67 to 82: on medium and small eJidos. The area seeded with cotton was low and has been decreasing from past years, due to high production costs and low international price of cotton (Figure 4.2). 53 Table 4.4. Area and Yield of Hheat in Collective EJidos of the Yaqui Valley. YEAR AREA YIELD HECTARS TON/HA 1981/82 17,390 5.3 1982/83 15,598 5.0 1983/84 13,245 5.3 1984/85 14,209 4.8 1985/86 15,462 NA AVERAGE 15,180 Source: Technical Assistance Area, Coalition. Unpublished data. TABLE 4.5. Area and Yield of Soybean and Cotton in Collective EJidos of the Yaqui Valley. YEAR SOYBEAN COTTON HECTARS TON/HA HECTARS TON/HA 1981 15,117 -- -- -- 1982 12,891 2.0 . 858 ~- 1983 13,749 1.84 1,277 2.8 1984 9,393 1.7 4,135 2.0 1985 15,040 1.7 2,745 2.5 AVERAGE 13,238 1,803 Source: Technical Assistance Area, Coalition, Unpublished data. 54 O o / so i. w 5 w 3’. «r — 3L vi 2: EL 60 1» fl 1 s : J» :: 3 E s E i: ': no i 3* L: d : f: -— I :2 .2 4} —— h_ H ”-4 :1 : J F: 20 a E I E; d __ a ._ ’— — c —/ Z 4. — / 2 C F? _. :3? ._ C 2/ “I; ’- 0 fl / é __ / :4 :3; I Ti? ITI Ci! <2 _I i U‘ .1 p P a, P Figure 4.2. Percent of Total Area Seeded with Hheat, Soybeans and Cotton in Collective EJidos. 55 4.3.5. Crop Production System The crop production systems For wheat, soybeans and cotton were relatively uniForm in the collective eJidos. The eJidos had to proceed according to schedules oF the irrigation district, and Followed the recommendations oF the Field technicians oF Coalition to receive their allowances From the Credit Union or Banks. The July 85 and May 86 surveys , indicated variation in the type oF operations and equipment. The number oF tillage, Fertilizer application and plant protection operations are shown in Tables 4.6, 4.7 and 4.8 For all the ejldos oF Coalition. The main variation For the mechanization oF the 3 main crops From 1983 to 1985 are shown in Table 4.9. Typical mechanized systems For wheat, soybeans and cotton are shown in Table 4.10. 4.3.6. Horkabie Days The eJidatarios did not register or recall the number oF suitable days For Field operations. Records 0F 27 years (1959-1985) oF daily precipitation were obtained From the agroclimatoiogy area oF CIANO, along with the criteria to decide non-suitable days. The procedure to generate suitable days on a weekly basis is described in Chapter 5, Section 5.3.1.3. 56 Table 4.6. Operation and Dates For Hheat Production in Collective EJidos oF the Yaqui Valley Date oF the Operations1 Operation Ejidos Earlier Most Common Latest Doing Date Date No. Date Operation EJidos Subsoillng 6 09-1 09-4 3 12-1 Chiseling 12 09-1 10-1 5 12-1 Disk Plowing 34 07-1 10-2 11 12-1 Disk Harrow-1 41 07-1 10-3 13 12-2 Disk Harrow-2 41 07-1 10-4 14 12-4 Disk Harrow-3 20 07-1 10-4 9 12-4 Land Leveling 35 09-4 11-1 16 01-1 Furrowing 25 10-1 11-1 8 01-1 Bedding 17 10-3 11-4 6 12-3 Seeding 36 11-1 12-1 13 01-1 Applic. Solid Fertl l izer 36 09-1 11-1 15 02-1 Applic. Liquid Fertilizer 30 09-4 01-1 5 03-4 Ground Spraying 10 12-1 01-4 3 03-4 Aerial Spraying 35 12-2 01-4 7 04-3 Harvest 41 04-1 05-1 26 07-1 Straw Burning 38 05-1 05-3 11 07-2 1 First two digits indicate month; last digit indicates which week in that month. Source: Survey in the Yaqui Valley, July 85. 57 TABLE 4.7. Operation and Dates For Soybean Production in Collective EJidos oF the Yaqui Valley. Date oF The Operations1 No. oF Operation EJidos Earlier Most Common Latest Doing Date Dates No. Date Operation Subsoillng 8 02-1 05-1 3 05-4 Chiseiing 7 02-1 05-1 2 06-1 Disc Plowing 19 02-1 06-1 6 07-3 Disc Harrow-1 42 02-1 06-1 10 07-3 Disc Harrow-2 40 02-1 05-4 19 07-1 Disc Harrow-3 23 02-1 06-1 6 06-4 Land Leveling 21 02-2 05-1 7 07-1 Furrowing 40 02-2 05-3 10 07-2 Seeding 43 04-1 06-1 21 07-4 Cultipacker 23 05-2 06-4 ,5 08-1 Applic. Solid -- ---- ---- -- ---- Fertilizer 28 03-3 05-1 10 07-1 Applic. Liquid -- ---- ---- -- ---- Fertilizer 8 05-1 05-4 4 06-3 Cultivation-1 34 05-4 07-1 7 08-2 Cultivation-2 23 05-4 07-1 8 07-4 Ground Spraying * 3 05-1 ---- -- 08-4 Aerial Spraying ‘ 4 06-2 ---- -- 08-1 DeFoliation * 1 --_- 1 First two digits indicate month; last digit indicates which week * These operations had not been done at the time oF the surv in that month. ey. TABLE 4.8. Operation and Dates For Cotton Production in Collective EJidos oF the Yaqui Valley. 1985. Date oF the Operations1 No. oF Operation EJidos Earlier Most Common Latest Doing Date Dates No. Date Operation EJidos Subsoillng 15 12-1 01-1 9 02-3 Disc Plowing 18 11-4 01-1 8 02-4 Disc Harrow-1 24 12-1 02-1 6 03-1 Disc Harrow-2 24 12-1 02-1 6 03-2 Disc Harrow-3 17 12-1 02-1 4 03-1 Land Leveling 11 12-4 01-1 4 04-1 Furrowing 23 01-1 02-1 6 04-1 Seeding 23 02-1 02-4 61 04-4 Cultipacker 6 02-4 --- - 05-3 App. Solid Fert. 19 01-1 02-1 4 04-4 App. Liquid Part. 15 01-1 04-1 3 05-4 Manual Thinning 19 03-1 04-4 3 06-1 Cultivation-1 20 02-4 03-3 4 06-1 Cultivation-2 18 02-4 04-1 4 06-4 Ground Spraying * 12 02-1 04-2 4 05-1 Aerial Spraying * 13 05-1 06-4 6 07-4 DeFoliation * 9 05-4 07-3 3 08-2 Harvest * 6 07-4 08-1 - 08-1 Rotary Cutter * 4 08-2 --- - --- 1 First two digits indicate month; last digit indicates which week in that month. “ These operations had not been done at the time oF the survey. Table 4.9. Number oF Passes and Cases Reported For Field Operation on Hheat, Soybean and Cotton in Collective EJidos. Operation Hheat Soybean Cotton Passes Frec Passes Frec Passes Frec Chiseiing 0 24 0 24 0 4 1 10 1 1 1 Disk Plowing 0 10 0 20 0 6 1 23 1 5 1 6 Disk Harrow , 2: 5 2 14 2 2 3 25 3 12 3 8 4 2 - -- 4 2 Land Plane 0 11 0 20 0 5 1 14 1 2 1 6 2 1 - -- - - Hood Frame 0 2 1 22 1 9 1 21 2 3 2 3 2 9 3 1 - - Furrowing ‘0 6 1 14 1 9 1 21 2 9 2 2 2 - -- - - Broadcasting 0 6 0 3 0 1 Fertilizer 1 17 1 18 1 8 2 11 2 5 2 3 Field 0 16 - -- 0 6 Fertilization 1 5 - -- 1 4 Row-Cultivator - -- 2 8 3 5 - -- 3 11 4 7 _ -- 4 4 - - Ground Spraying 0 18 0 16 0 3 1 9 1 5 1 8 2 1 - -- - - Aerial Spraying 0 8 0 3 1 2 1 14 1 12 2 6 2 7 2 9 3 4 3 3 3 2 - - Source: Survey on 14 Collective EJldos, Hay 1986. 60 Table 4.10. Operations and Number oF Passes For Hheat, Soybeans and Cotton Production in Collective EJidos oF the Yaqui Valley. Field Operation Hheat Soybeans Cotton Chiseiing 0 0 1 Disk plowing 1 0 0,1“ Disk harrowing 3 2 3 Fertilizer spreading 1 1 1 Land plane 1 0 1 Hood Frame 1 1 1 Furrowing 1 1 1 Row cultivation 0 3 4 Ground spraying 0 0 1 Aerial spraying 1 1 2 Stalk cutter 0 0 1 Source: Survey in Collective EJldos, Hay 1986. * 50! disk plowed; 501 did not disk plowed. 61 4.4. AGRICULTURAL MACHINERY IN COLLECTIVE EJIDOS 4.4.1. Inventory oF Agricultural Machinery FiFty eJidos associated with Coalition had a total oF 353 tractors in July 85. This was an average 0F 7 tractors per eJido, and one tractor per 61.7 cultivable hectares. The number oF combines was 90, with an average oF one combine per 242 cultivable hectares. Table 4.11 presents a summary oF the equipment in the collective eJldos. Besides, 18 0F the 50 eJidos associated with the Coalition, created the Union '19 de Noviembre', an eJldai cooperative that owned and operated 3 planes For aerial spraying, 10 combines, 8 2-row cotton pickers, 26 equipment For ammonia inJection and 33 For aqua-ammonia application. 4.4.2. Experience in Agricultural Machinery In July »85 there were 3861 active members (ejidatarlos) oF which 702 were tractor operators, 144 combine operators, and 99 truck drivers. The maJority oF these operators had more than 10 years oF experience. There were only 17 mechanics and 18 welders For 8 eJidos workshops. The other ejidos had no workshops. This explains why the Coalition leaders complained about poor maintenance and high expenses For machinery repair. labia 1.11. Agricultural flachinary in Coiiactivo 611803. 62 Yaqui Valley, Sonora, Ianico Iuahar oi Alanine: E j i d o I a a a Cult. EJida- lract Coat Blah Blah Plant. Spray. 11a: trio: Io. Io. Pica iis'roa Equip Equip Alfredo Boniii 1583 287 17 6 6 7 6 - El Rodao 1689 189 11 3 5 6 1 1 Falipa Iari 987 163 11 1 3 6 6 i lariano Escobado-i 911 177 11 1 5 8 5 i iucurihaapo 911 156 13 1 5 6 5 3 Guillarao Priato 986 155 18 1 5 8 9 1 Col. Alianda (Fl. Iadaro) 881 178 26 7 1 8 6 2 Conatituyantas 825 132 11 2 1 6 3 2 ignacio Zarogoza 773 118 8 1 3 5 5 2 lariano Eacobedo-2 691 135 11 1 5 5 3 2 Aazario Ortiz Garza 672 115 11 1 1 6 7 - San iaidro 625 118 3 - 1 2 2 - Plan 66 Ayala 591 118 8 1 3 5 5 3 San Josa Bacua 553 123 7 1 2 1 - 1 Otiiio Montana 552 82 9 2 2 1 2 - 23 da Octuhrc 532 98 10 2 1 1 5 1 Bachoaohaapo 525 117 18 - 1 3 3 1 Ganoavo da la 0 521 111 9 3 3 6 1 1 5 da Junie 175 85 7 2 6 5 - 1 El Panaador 138 71 8 3 1 1 6 2 Roaaro Paiacioa 396 78 6 1 3 5 1 1 15 da Aayo 391 66 7 2 3 1 3 5 Estacibn Luis 392 66 1| 1 3 1 3 - Rayaundo Saravia 388 85 5 2 2 2 3 l Baiisario Doainguez 385 68 7 2 2 1 2 - labia 1.11. (Cont‘d) 63 luahar oi Iachinas E J i d o I a a e Cult. EJida- iract Coab Dish Disk Plant. Spray. 11a: tario: Io. Io. Pioa lie-ran Equip Equip Priaaro da Abrii 371 37 7 2 3 1 3 1 A. Ruiz Cortinaz 361 72 11 2 3 1 2 2 Vataranoa da ia Ravoiucidn 361 77 8 3 3 1 3 2 Savariano laiaaanta 311 51 6 2 1 3 2 2 Cuauhtaaoc CArdanaa 317 61 7 2 1 2 2 i Jacinto Lopaz 291 17 5 - 2 3 3 2 H6roaa da Cultaca 271 28 1 2 1 3 1 - 2 do Abrii 261 32 6 - 2‘ 2 2 - ignacio Pasquaira 251 39 1 2 3 1 1 2 El Chaaizai 225 11 2 - 1 1 1 - Eco. J. IuJica 222 32 5 1 3 1 1 1 El Porvanir 219 16 1 2 2 1 3 - Precursores da 1a Rev. 195 38 1 1 2 2 1 1 Plan Orianta 183 37 1 - 2 1 2 2 Ahalardo L. Rodriguez 167 25 1 - 2 5 2 1 ignacio Soto 157 31 1 - 2 3 2 1 licanta Padilla 152 26 1 - 3 3 2 1 Bonito Juaraz 115 21 3 3 3 2 - 8 do Fahraro 115 11 3 2 1 2 1 Francisco da Bocanagra 111 26 3 2 2 3 - 6 da Enaro 131 13 2 - 2 2 2 - Rio Yaqui 123 21 3 - 2 2 2 1 Pascuai Acuna 111 21 2 - 2 1 2 2 IArtiras da Cananaa 99 11 2 2 2 1 - El individual 19 1 - - - - - - lOlALS 22,286 3,861 353 98 112 195 172 57 Sourca: Survay on Coilactiva Ejidos. July 1985. 64 4.4.3. Responsibles For the Machinery Machinery maintenance and repair, programming and controllng was in the hands oF a work Foreman in 22 eJidos , a machinery Foreman in 16 eJidos and the surveillance head in 16 eJldos . Records oF maintenance and repair expenditures were kept globally For all the machinery in 42 eJldos. Individual or per machine records were maintained only in 5 eJldos, and 9 eJidos kept both types oF records. 4.4.4. Horking Day A working day For machinery operators was normally 8 hours in 39 eJidos , 12 hours in 5 eJidos, 7 hours in 3 eJldos and 6 hours in 2 eJidos. There were urgent operations (very common For the wheat-soybean rotation), where one operator would work continousiy up to 16 hours (double shiFt) or 24 hours (triple shiFt). The operations most oFten done with longer working days were disk plowing, disk harrowing and land leveling. In the survey oF May 86 (See Table 4.12), tillage was reported as being done For up to 24 hours with the same operator (approximately 20 eFFective hours). Other operations could be up to 10, 12 or 18 hours per day on some eJidos. For example, spraying could be done up to 18 hours per day, when the operation was done during noon and night. 65 Table 4.12. Range oF Horking Hours per Day. Field Operation Hour/day Tillage, seeding wheat 8 - 24 Spraying 6 - 18 Row cultivation 8 - 16 Furrowing, planting soybean and cotton 8 - 12 Cotton picking (machine) 7 - 10 Harvesting wheat and soybeans 6 - 10 Source: Survey in Collective EJidos, May 1986. 66 4.4.5. Operator Rages. Operator wages varied between eJidos, as they were Free to decide how much to take For labor From the credit received For crop production. Most oF the eJldos paid a Fixed amount per day or a percentage oF the rate established in the credit For a given operation. Payments For tillage, seeding , cultivation and spraying were on a per day basis, varying From 1800 to 3000 Mexican pesos per 8 hours. Payments were proportionally higher For longer working days. For harvest the payment was higher on a per day basis; and around 10 2 OF the authorized price per hectare harvested. 4.4.6. Programming oF Machinery Operations. Machinery use was programmed by the work Foreman in 16 0F the 50 eJldos, or between 2 or 3 persons including the work Foreman, surveillance head or somebody From the eJido authorities. In 6 eJidos, the General Assembly made decisions about the programming. Usually the programming was Adone with a one month lead time. Ten types oF programming problems were reported. The most Frequent problems were; machinery Failures in 11 cases, delay in supplies in 7 cases, and bad weather in 6. Records oF variable accuracy were maintained on the use oF machinery, mainly For the purpose oF paying the operators, and For crop expenses . No speciFic data were kept For particular machines or land parcels. 67 4.4.7. Purchase oF Machinery. Machinery purchases were made by the eJidos without date on machinery use. Decisions were based on practical experience, and the need oF more machinery to complete the Field work on time.In all cases the purchase oF new machinery had to be approved by the Assembly. Most oF the eJidos purchased new machinery because oF the guaranty and service given by dealers. A Few eJidos purchased used machinery when there were good opportunities, low prices, or when the eJido did not have enough money. The majority oF the eJidos purchased machinery through the Credit Union oF Coalition ( 34 eJidos), 15 eJldos purchased directly From dealers and 10 through Banrural. Forty one eJidos used special credits For durable assets (creditos reFaccionarlos), 11 obtained price reductions in direct purchases, 11 used private loans, and 7 obtained payment Facilities. By July 85, the eJidos indicated the need oF the Following equipment: 39 tractors, 18 combines, 2 cotton pickers, 13 trucks, 4 sprayers and 33 other implements. This is not a large amount oF machinery considering the 50 eJidos. This inFers general satlsFaction with the present machinery For their needs. It was also reported that they would sell 44 tractors and 8 combines. 68 4.4.8. Custom-Hired Operations. The survey oF July 85 indicated that the eJldos have used custom-hired machinery since they were created in 1976. For the last season they recalled 18 cases oF custom-hired work For seeding, 15 cases oF disk harrowing, 15 For harvest, 14 For spraying, and 11 For disk plowing. The area custom-hired per ejido varied From 40 to 860 hectares For seeding, 60 to 860 hectars For disk harrowing, 19 to 860 hectares For disk plowing and harvest, and 30 to 440 hectares For spraying. The quality oF custom-hired work was largely reported as good and timely; only seven cases were reported as deFFlcient and 3 and as not timely. Custom-hired operations reported on the survey oF May 86 were: disk harrowing and land leveling in 3 eJldos, Furrowing in one, wheat seeding in two, soybean planting in three, wheat harvest in six, and soybean harvest in Four. The area custom-hired was incompletely reported because oF poor recall and lack oF accurate records. Some data obtained were: disk harrowing: 245 hectars; land leveling: 158 hectars; wheat seeding:50 hectars: soybean seeding: 389 hectars; wheat harvest: 1780 hectars: soybean harvest: 784 hectars. 69 4 . 5 . MACH I NE PARAMTERS 4.5.1. Duration oF Machinery Much oF othe machinery purchased new since the collective eJidos were created in November 1976, was still in operation. ThereFore, at the time oF the study there were machines with 10 years oF use. The total hours worked For speciFic tractors and implements was not kept, nor could be recalled accurately by eJldatarios. Experienced dealers oF Ford, John Deere and Industries Vazquez in Obregon City (May 86), indicated that duration oF machinery in the Yaqui Valley depends on malntenanace and operating conditions. There were tractors 20 years old, and combines 15 years old still running. Dealers considered that with good care and maintenance the duration oF tractors in private Farms could be up to 14,000 hours, 12 to 15 years For combines and 6 to 10 years For implements such as disk plows, disk harrows, cultivators, planters, etc. Dealers beleive that there was a lower duration on collective eJidos (with good care) oF about 8,000 to 10,000 hours For tractors, and 10 years For combines (no indications oF hours oF use). Better care, maintenance and operation in private Farms, were considered among the reasons For longer useFul liFe oF machinery, as compared with collective eJidos. 70 4.5.2. Resale Value Selling 'or buying used equipment was not a common practice in the collective eJidos, although it existed in the Yaqui Valley. Resale prices depended on the conditions oF the machines, need and opportunity and ability to negotiate with potential clients. According to machinery dealers consulted, 10 year old operating tractors and combines sold For about 10! 0F new equipment price. Scrap values could be; 5 to 10X For tractors, while implements had practically no scrap value. 4.5.3. Annual Use oF Machinery Practically no detailed data on machinery use were available. The eJidatarlos did not emphasize the use oF hourmeters For the evaluation oF machinery perFormance. On the survey oF July 85, 34 eJidos estimates oF annual tractor use varied From 15 to 360 days/year, and combines (22 cases) From 15 to 120 days/year. For tractors, 14 eJidos estimated an annual use oF less than 60 days/year, 9 From 61 to 120 days/year, 5 eJidos estimated an use oF 121 to 240 days and 5 more than 241 days. ThereFore, the maJority used the tractors less than 1000 hours per year (120 8-hour days/year). On the survey oF May 86 one eJldo provided the Following Figures: 1000 hr/year, average 0F 8 years For a large tractor (IH 966); 350hr/year, average 0F 8 years For a small tractor (MF 165); 315 hr/year, average 0F 6 years For a combine (JD 7700); 500 hr/year For a disk harrow; 71 300 hr/year For a grain drill, and 280 hr/year For a row-crop planter.‘ 4.5.4 Failures & Repairs Costs The most common expressed problem with machinery was the high cost oF repair. However no records were kept For each machine in the eJido, not even the largest ones. Accounting included only costs oF Fuel, labor, repairs, etc. For the eJido as a whole. Some machines did have critical Failures that kept them down a slgniFicant length oF time. The recall was only on the large machines, but this could be a problem with implements as well. There were 3 cases oF tractors and 2 combines For which Failure was an engine break-down. These resulted in the keeping the machines out oF action For 15 to 240 days. In 6 cases the unavailabity oF repair parts was a cause For the delay in repairing the machinery. In one eJldo, payments For a major repair For a tractor represented about 10! 0F the price oF a new tractor. Machinery dealers had a Few records oF tractor and combine repair, but not complete.Table 4.13 depicts payments For repair oF two tractors given by the John Deere dealer in Obregon City. 72 4.5.5 Speed, Field Capacity, and Field EFFlclency oF Machinery The July 85 survey produced limited data on operating speeds, Field capacity and Field eFFiciency. Operators knew the tractor gear For a given operation, but not the speed in kilometers per hour. EFFectlve Field capacitieswere recalled in hectars per day, but this could be inaccurate, when diFFerent tractors, implements and operators were used on the same parcel. In May 86 the majority oF the ejldos worked at third gear For disk plowing; third and Fourth gear For disk harrowing; third, Fourth and FiFth gear For seeding. Cultivation varied From First to third gear For the First pass, and up to Fourth gear For the second cultivation. This inFormatlon is consistent wlh that obtained in July 85. EFFectlve Field capacity data obtained were reliable in some cases, but in others was inaccurate, due to poor recalling or poor estimation oF hours spent on a given parcel. Field eFFiciency was calculated From the Few reliable values as: 0.6 to 0.8 For disk plowing, 0.6 to 0.84 For disk harrowing, 0.5 to 0.7 For soybean and cotton planting, and 0.5 to 0.7 For wheat and soybeans harvest. Direct measurements oF operating speeds and time losses were carried out in August, December 1985, and May 86. An average speed oF 3.7 km/hr and a Field eFFiciency oF 0.77 were calculated For cotton picking” Manual picking oF 73 cotton required an average oF 83.6 person-hour per hectare. Average speeds in km/hr For wheat seedbed preparation and seeding, wheat harvesting, and tillage and planting For soybeans are shown in Table 4.14. 4.5.6 DraFt Force Measurements DraFt Forces were measured For disk plow, disk harrow and chisel plow, in May 86. An hydraulic dynamometer (Towner puli- meter), with a pulling capacity oF 30,000 pounds was used For measurements. The puilmeter was borrowed From Maquinarla General de Occidente, dealers oF Caterpillar in Obregon City. An average oF 24.7 drawbar kilowatt per meter (10.1 DBHP/Ft) was measured For disk plow. Measurements were made in 5 ejidos with 10 replications per trial. For disk harrow there were measurements in 7 ejidos, with an average oF 8.1 drawbar kilowatt per meter oF width (3.3 DBHP/Ft). Average depths and speeds For disk plowing, were 25.2 cm and 5.3 km/hr, and 14.7cm and 6 km/hr For disk harrow. 4.6. AGRICULTURAL MACHINERY AVAILABLE IN THE YAOUI VALLEY. 4.6.1. Agricultural Machinery ManuFacture. Agricultural machinery manuFacturlng in Mexico was concentrated around the main industrial centers. In the Yaqui Valley, the only manufacturer was Industries Vazquez, the largest in the northwest and one oF the 74 Table 4.13. Payments For Tractor Repair Year J. D. 42351 J.D. 44402 Payments, M.‘ Payments, M.’ 1982 6,014 58,111 1983 10,697 95,906 1984 25,770 534,706 1985 622,679 33,560 1 Tractor sold Jan.17, 1974 a Tractor sold Feb.29, 1980 Source: Equipos Agricolas del Yaqui, Obregdn City. Table 4.14. Operating Speeds in Collective Ejldos. Operation Km/hr No. oF Average Ejldos Decggggg 851 Disk Harrowlng 7.1 4 Hheat Seeding 10.9 3 Furrowing 9.4 1 ”,1 gen Hheat Harvesting 4.0 1 Disk Plowing 5.6 8 Disk Harrowlng 5.9 7 Furrowing 7.7 4 Soybean Planting 9.3 2 1 Seedbed preparation and seeding wheat. 9 Hheat harvest; Tillage and planting soybean Source: Direct measurements in the Yaqui Valley 75 largest implement manuFacturers in Mexico. Sales were directly at the Obregon City Factory and through established dealers in the region, and country. 4.6.2. Agricultural Machinery Dealers. Prominent dealers oF agricultural equipment in the Yaqui Valley were: Sonora Agricola, a representative oF Ford: and Equipos Agricolas del Yaqui,a representative oF John Deere. Both had main oFFlces in Obregon City. Smaller dealers were: Grupo Promansa, representatives oF Sidena, Canota and Hess; Servicios Agricolas, representing New Holland; and Combinadas, Tractores y Montacargas, S.A., a representative oF Allis Chalmers. Large dealers oF industrial machinery, which also sold crawler tractors For agricultural operations were: Maquinaria General de Occldente For Caterpillar: and DJMAKO, selling crawler tractors and industrial machinery. Both sold mostly imported machinery. 4.6.3. Available Sizes and Prices oF Equipment. The collective ejidos purchased new machinery, -generaliy From the dealers in Obregon City. Only For some special imported machinery, such as combines or cotton pickers would purchases be made directly From the U.S. The equipment available, and the prices For April 1985 is detailed in Appendix B. 76 4.6.4. Custom Hire Machinery Services. The intensive use oF the irrigated land oF the valley, with two crops per year in most cases, with critical periods For seeding, crop protection practices and harvesting, demanded the use oF large machinery. Custom-hire machinery operations were used For high capacity jobs requiring high capacity (usually imported) machines, which small or medium holders could not aFFord to own. Custom-hired services were provided by both governmental and private enterprises. There were two governmental services; one, was the Program For Agricultural Mechanization For small private Farmers, and two, was the Machinery Central oF the Rural Bank For the reservation oF the Yaqui tribe (Irrigation District 018). Both had their main oFFlces in Obregon City. The larger private enterprises were: AeroFumigadores Unidos del Yaqui y Mayo, with 71 planes: and Fumigaciones e Insecticides Union del Yaqui (FUMEI), with 44 aqua-ammonia applicators and 48 nurse trailers, 9 anhydrous ammonia applicators and 34 nurse trailers and 6 nurse trailers For calcium polisulphurum. 4.6.5. Price oF Custom-Hired Operations Prices For custom hire operations were established by a committee, chaired by the representative oF the Secretary oF Agriculture and Hydraulic Resources (SARH), with members oF other agricultural related institutions. Prices established were to be charged by government and 77 private custom-hire services. The list oF prices For custom- hire operations is presented in Table 4.15. 4 . 7 . ECONO'II C FARMETERS Economic Factors were critical For the simulation model, since the objective was to obtain the most economical machinery sets For collective ejidos. InFormation was obtained on inFlation in Mexico, and the prices oF crops, machinery, Fuel and labor. 4.7.1. General InFiatlon in Mexico. InFormation oF the Bank oF Mexico in Challta (1986), showed that the general inFlation in Mexico during the last 15 years varied From a low 4.5 x in 1970 to a peak 98.8 X in 1982. Table 4.16 depicts the values oF inFlation in Mexico For the last 15 years. It will be noted that there are 3 main periods: 1) "1970 - 1972 with low inFlation rates oF 4.5, 4.4 and 4.5 1. 2) 1973 - 1981, with medium inFlation varying From 12.3 to 29.71. 3) 1982 - 1985, with high inFlation rates, varying From 98.83 in 1982 and decreasing to 63.71 in 1985. This reFlects Mexico's economic crisis, which is still present. Table 4.15. 78 Prices For Custom-Hired Services in the Yaqui Valley. April, 1985. Operation Mex Slha Disk plowing 7,350 Subsoillng 5,700 Disk harrowing 2,950 Land leveling 3,250 Land leveling (tabion) 1,900 Fertilizing 1,800 Furrowing 2,150 Row-cultivation 1,800 Seeding 2,400 Cultipacker 1,100 Rotary shredder 3,500 Aerial spraying 3,000 Aqua ammonia apllc.1 9,200 Anhydrous ammonia apllc.1 35,600 Combine 12,000 Cotton picker 16,000 Tractor, one hour 3,600 1 Price per metric ton., product included. Source: Agricultural Mechanization Program, AeroFumigadores Unidos del Yaqui y Mayo, FUMEI. 79 4.7.2. Credits Loans For Agricultural Machinery Purchases The collective ejidos associated with Coalition purchased their machinery through the Credit Union oF Coalition, which had similar Functions as Banrural, the government bank For rural development. The conditions For purchasing machinery with the Credit Union were very Favorable For collective ejidos, as compared to the private banks. Table 4.17 shows the interest rates For machinery purchases as low as a halF or a third (1982, 1983) oF general inFlation. Dealers did not handle credit For their potential clients as they did beFore the economic crisis, because oF the high interest rates charged by the banks For private loans. 4.7.3. Price oF Machinery The price oF tractors, combines and implements increased at diFFerent rates during the last years. Combines had the largest increase: 46 times the initial price, From August 1980 to May 1986, while inFlation increased by a Factor oF 17.4. A utility tractor increased by a Factors oF 23.6 and a tillage tractor 28.6: disk plows 13.5 times; and disk harrows 12.76 times over the same period (See Tables 4.18 and 4.19). Prices oF domestic made implements increased less than inFlation. Imported machinery such as combines varied largely above inFlation, reFlecting the variation oF the exchange rate (Mexican pesos per one US dolar) since 80 Table 4.16. Percent oF InFlatlon in Mexico. Year InFlatlon x 1970 4.5 1971 4.4 1972 4.5 1973 12.3 1974 24.0 1975 18.1 1976 19.4 1977 20.7 978 16.2 1979 19.9 1980 29.7 1981 28.9 1982 98.8 1983 80.8 1984 66.0 1985 63.7 Source: Luis E. Challta, 1986. Table 4.17 Interest Rates For Ejldos For Credits to Purchase Machinery. Year Interest Rate 1980 13 1981 15.5 1982 - Jun 83 19 Jul - Dec 83 23 1984 27.5 1985 32 1986 38 Source: Credit Union, Coalition. May 86. 81 Table 4.18. Price Variations oF Tractors. Mex. Pesos x 1000 Date Ford MF MF IH 6600 285 290 784 January 81 403 396 -- 404 July 81 459 454 -- 432 March 82 539 590 -- 592 September 82 796 841 -- 820 February 83 1,170 1,235 1,392 1,205 May 83 1,474 1,555 1,754 1,518 October 83 1,816 1,912 2,197 discont. May 84 2,588 2,174 2,498 -- August 84 -- 2,742 3,150 -- March 85 3,310 -- -- -- January 86 4,799 -- -- -- May 86 7,883 -- -- -- City. June 1986. Source: Sonora Agricola, Obregdn Table 4.19. Price Variations oF J. Deere Machinery, Aug. 80-May 86. Thousand oF Mexican pesos. Date oF Tractor Tractor Combine Plow Harrow Price 2735 4235 7720* 3745 32 Aug 80 410 621 1,085 119 _ 186 Aug 81 I 527 684 2,003 160 196 Aug 82' 665 1,110 3,507 217 288 Aug 83 1,722 3,046 12,147 318 481 Aug 84 2,980 5,673 15,172 550 913 Aug 85 4,229 8,017 19,500 956 1,415 May 86 9,680 17,776 50,000 1,606 2,370 “1980,1981 Combine 6620 82 1982. Tractors up to 140 HP, manuFactured In Mexico (with around 501 oF imported parts), were in an intermediate situation, with a price variation a little above the general inFlation. Prices oF locally manuFactured equipment are shown in Table 4.20. The variation Factor in price From Sept 81 to May 86 was near the general inFlation For a shovel and a disk harrow. The increase oF a Fertilizer spreader was about halF the inFlation For the same period (See Table 4.21). The lower price increase oF implements reFlected price controi regulations oF domestic manuFactured equipment and/or a low demand For equipment due to lack oF money by producers. 4.7.4. Price oF Fuel and “ages During 1985 Fuel prices increased 143 1, and For the period oF January 86 to August 86 the increase was 83.51. Monthly variations oF Fuel price From January 1985 to September 86 are shown in Table 4.22. Variations oF minimum wages were obtained For the period 1976 to 1986. Mlnumum wages For machinery operators were 46.71 higher than the general wages For Farm workers (Table 4.23). 83 Table 4.20. Price Variation For Implements. Thousand Mexican Pesos. OFFset Disk Shovel 10' Fertilizer Date Harrow w/wheels Spreader Sept 81 234 83 -- Sept 82 369 150 64 Nov 83 677 283 120 Febr 84 934 290 150 Jun 84 1,120 377 187 Dec 84 1,271 483 178 Febr 85 1,462 537 207 Jun 85 1,571 642 248 Febr 86 2,577 1,192 392 May 86 2,620 1,210 398 Source: Industries Vazquez. Obregon City, Sonora. Table 4.21. InFlatlon and Price Variation For Implements. Sept 81 - May 86. Concept Max 9 Mex 3 Factor oF Sept 81 May 86 Increase InFlatlon 100 1,319.3 13.2 Shovel, 10' 83,592 1,210,000 14.5 OFFset harrow 234,286 2,620,000 11.2 Fertilizer 64,000 398,000 6.2 84 Table 4.22. Price oF Fuel. January 1985 to September 1986. Mexican Olliter. Month 1 985 1 986 January 26.0 63.2 February 32.0 65.5 March 32.8 67.8 April 33.6 70.1 May 34.5 72.6 June 35.3 75.1 July 36.2 77.8 August 37.1 94.2 September 38.0 116.0 October 39.0 -- November 40.0 -- December 50.9 -- Source: Fuel Stations, Texcoco Mexico. Table 4.23. Minimum “ages per 8-hour Day in Mexican Pesos. Yaqui Valley General Farm Machinery Year Worker Horker Operator 1976 69 66 97 1977 93 89 137 1978 105 100 147 1979 120 120 176 1980 145 145 213 1981 190 190 279 1982 255 NA NA 1983 415 NA NA 1984 625 625 917 1985 975 975 1430 1986 1520 NA NA Source: Diarios OFiciaies de la Federacidn. 4.8. DISCUSSION OF RESULTS OF DATA COLLECTION The needs analysis showed that the ejidatarios, technicians and ejldo leaders emphasized the need For training, technical assistance and research in agricultural mechanization. Eighty percent oF the answers were positive For training, 80 1 For technical assistance, and 93 1 For research needs. Machinery management and repair were the topics indicated as more important and urgent. The data collection process included all inFormation kept by the ejidos, and other resources available For the study. Data on size oF ejidos, size oF parcels, area seeded and yields were quite accurate, because good records were kept on these items at the ejidos and/or Coalition's oFFlces. Crop production systems and schedules varied within the ejidos (Tables 4.6 to 4.10), butin general the Field operations were within the (broad) recommendations oF the CAEVY. Machinery data collection presented some problems due to lack oF records kept by the ejidos. The results oF Field surveys and measurements were used to establish such parameters as operating speeds, Field eFFiciencies, and sizes and prices oF equipment. The inFormation obtained was used to Formulate rotation Files and the external File CONTIL which contained machine and economic parameters. Both Files were required by the computer model. The inFormation on machinery sizes and prices collected in 1985 was limited to the Few sizes oF machines 86 available From local dealers. The model needed more options to provide greater Flexibility oF selection. To solve this, it was assumed that machinery could be ordered From other places in Mexico, or imported by local dealers. OFFicial prices oF custom hired operations were obtained and used in the model. Data on prices paid by the ejidos was not considered reliable, because oF poor record keeping. The limited data obtained was presented in section 4.4.8. Results oF the survey indicated that custom hiring was an option that should be compared with owning the machinery by the ejidos. Economic parameters included in the model varied with the diFFicuity oF obtaining data and/or reliability. General inFlation and parameters related to machinery purchase were readily obtainable and reliable, since oFFiclal inFormation was available. Cost oF labor varied in the ejidos, thereFore the most common price paid to machine operators was used For model validation. Prices oF machinery Fuel and wages were obtained For the previous two to ten years. Since there was no clear pattern oF price changes, and it was diFFicult to predict any trend in price increases, zero inFlation oF Fuel, machinery and wages were used in the model validation. 87 4.9. DATA USED IN TI-E CG‘lPUTER MODEL Agronomic, economic and agricultural machinery operational data collected; in the collective ejidos, and/or From machinery dealers, Coalition's oFFice and government oFFlces, were used to Formulate values For the parameters in the input data Files, or in the data block oF the computer program. Sizes and prices oF agricultural machines For the Yaqui Valley replaced values For Michigan in the original computer program and/or in the machinery data File. Price For machinery were obtained From agricultural machinery dealers. Timeliness costs For planting and harvesting oF wheat, soybeans and cotton were calculated From crop yields and crap values, according to inFormation From the Experiment Station in the Yaqui Valley (Table 3.16). Prices oF crops For 1985 were obtained From Coalition. Timeliness cost occurs when a machine is not capable oF doing the job on the optimum crop yield period (Figures 3.2 and 3.3). Operation speeds and Field eFFiciencles oF machines were estimated From measurements made in the collective ejidos, and used in the machinery data File. Maximum widths oF machines sold by dealers in the Yaqui Valley were also used in the machinery data File. . Data obtained on repair, resale value oF machines and draFt Forces were not suFFlcient and/or reliable. ThereFore, the values For Michigan and already in the model 88 were used For this study. The usable liFe oF machinery was assumed to be 10 years. Most machinery purchased by the ejidos ten years ago was still in use, so ten years would be a minimum. running. Dealers also indicated an average duration 0F 10 years For machinery owned by ejidos. Suitable days For Field operations were calculated From daily rainFall records (Section 5.3.1.3.) because there were no records kept by ejidos. Machinery File data on suitable hours machinery File depended on the hours per days For diFFerent Field operations. Length oF working days varied on the ejidos, thereFore an average was estimated From the results oF the surveys, as Follows: Tillage Operations: 12 hours/day. Seeding, Cultivation and Spraying: 10 hours/day. Harvesting: 8 hours/day. Average wages For machinery operators in collective ejidos, and the price oF Fuel For 1985 were used in the model. Tax, insurance and shelter costs were assumed to be 11 0F the price oF new equipment, same as was already in the model, because no speciFic data For the Yaqui Valley were obtained. Income tax, discount rates, and inFlation rates were assumed to be zero. The ejidos do not pay income taxes, and the costs oF wages, Fuel and machinery were Fixed by the government according to the general inFlation rate. A low interest rate (11) was assumed in the model reFlecting the conditions For most ejidos that obtained subsidized credit loans For machinery purchases. For those loans, a zero 89 downpayment with 5 years to pay were used, according to inFormation given by the Credit Union oF Coalition For the last 7 years. The recommended dates For planting and harvesting, as recommended by the Experiment Station oF the Yaqui Valley, were used to set up the crop rotation Files. The Five most representative rotations (including wheat, soybean and cotton) and used by the ejidos were included in the rotation Files. Sequence oF Field operations and number oF passes correspond to those obtained From the surveys oF the collective ejidos. CHAPTER 5 DESCRIPTION OF THE MODEL AND ASSOCIATED FILES 5.1 . MACHIDERY SELECTION MODEL The mach i nery sel ect i on model ( MACHSEL ) was developed by Muhtar (1982), as an extension oF work by Holak (1981). It is a heuristic model designed to provide the most economic machinery complement. The program was intended For interactive use or with computer cards. Rotz et al. (1983), and Rotz & Black (1985) developed modiFications and Further validation oF the model. Minimum capacity For each machine was calculated based upon the operations required, the area to be covered, and time constraints For the operation. Minimum capacities needed to complete all Field operations within the time available were determined First. Tractor sizes were determined based upon maximum power requirements For implements. Row machines were matched i.e, the size oF the planter, row cultivator and ammonia application were set either equal or double the size oF the combine. Figure 5.1. shows the Flow diagram oF the modiFied programlMACHSEL. ‘ AFter the First set oF machines and associated costs were determined, a check was made to determine iF a lower cost set oF machines could be determined. Implements or combine sizes were increased and the entire process was repeated. 90 START OE TE RMINE “RIM COMPATIOLE SET lNCllEMENT TU NEIT LARGER TILLAGE SET SCHEDULE ALI. OPERATIONS ACCORDING TO PRIORITY LARGER TILLAGE EOUI'MEN T VAILAILE l YES CALCULATE TOTAL cost or wacwmtlv nus ileum!“ alone no“... alaas. use one cow Figure 5.1. INTERMEDIATE OUTPUT FIRST ’ASS 011 LOWER COST MORE ALTEHNATIVES lN ROW EQUIPMENT AVAILARLE FINAL OUT'UT ARGER TILLAGE EQUIPMENT AVAILAGtE INCREMENT TO NEXT FER [A must eémmam RESET TRACTORS lommliiiuu NO MAXIMUM NUMIE R OE TRAC TOHS INCREASE NUMBER OF TRAC TONS L__i iNCilEMENT TO NEXT LARGER AETERNAIIVE IN 110* EQUIPMENT 1 NO RESET TILLAGE SIZES TO MINIMUM Flow Chart oF ModiFied Program MACHSEL 92 5.2. MICROCOMPUTER VERSION OF MACHSEL A microcomputer version oF MACHSEL-was developed by Rotz in March oF 1986. The program was compiled in Lahey, F77L version oF Fortran. Data required by the model were stored in six input Files. Two Files contained machinery data and suitable hours For Field work, For conventional and no tillage systems. The other Four Files contained operation sequences For Four tillage methods and 12 crop rotations. The microcomputer version of MACHSEL was validated, as a part oF this study, to select best machinery sets For wheat, soybean and cotton production in the Yaqui Valley, state oF Sonora in Northwest Mexico. ModiFicatlons in the computer program and input data Files were required For the adaptation oF MACHSEL to this study. Timeliness costs For wheat, soybeans and cotton (Table 3.16) and sizes oF machines replaced Michigan data in the computer program. The machines included in this model were those; currently available in the Yaqui Valley, available by order From other locations in Mexico, or could be imported. The list oF machines and sizes considered are shown in Table 5.1. Row machines varied in size From 2 to 12 rows, except For sprayers that could be up to 24 rows in width. Subroutines; IMPSEL For selection oF a minimum set oF machines, and IMPINC For lncrementation oF machine sizes 93 Table 5.1. Equipment and Sizes Used For Hheat, Soybean and Cotton Production in the Yaqui Valley. Code Equipment Unit Sizes 1 Combine row 4,6,8,12 2 Cotton Picker row 2 3 SelF Prop. Sprayer row 8,12,26,24 4 Stalk Cutter Ft. 6,7 5 Cultipacker Ft. 10,12,15,18 6 Subsoiler Ft. 4,6,8,10,12,15 7 Fertilizers Ft. 20,30,40 8 Land Plane Ft. 10,12,14,15,18 9 Disk Plow disk 2,3,5,6,7,9 10 Disk Harrow Ft. 5.3,7,8,11,12.5,15.5, 18,22.5 11 OFFset Harrow Ft. 5.3,8,11,12.5,13.5, 15.5,17.5 12 Hood Frame Ft. 8,10,12,14,15 13 Grain Drill Ft. ‘ 8,12,14,16,20,24 14 Row Planter row 2,3,4,6,8,12 15 Furrower row 2,3,4,6,8,12 16 Sprayer row 4,6,8,12,16,24 17 Row-cultivator row 2,3,4,6,8,12 Source: Machinery dealers, Cludad Obregon, Sonora. 94 were slightly modiFied, For diFFerent sets oF machines considered. For example: the size equalization oF beet toppers with beet liFters, and combine headers with bean pullers were canceled, because these machines were not used in the Yaqui Valley. Cotton pickers, selF-propelled sprayers, stalk cutters and cuitipackers replaced bean pullers, mower-conditioners, beet toppers and beet liFters. For tillage: land planes and wood Frames, replaced chisel plows and Field cultivator, and Furrowers replaced min-till planters. Ten selected combinations oF row-equipment were considered in the model. An eleventh alternative in the original MACHSEL was not included because it contained a 24-row planter, which was assumed not a realistic option in in the Yaqui Valley. 5.3. INPUT DATA FILES Agronomic, economic and machinery data, presented in Chapter 4, were used to validate the model For the conditions oF the Yaqui Valley. Three input data Files were set up: One, was a machinery data File, CONTIL. Two, was a rotation File COVEN, For conventional tillage. Three, was a rotational File REDUC, For reduced tillage. 95 5.3.1. Machinery Data Files The machinery File CONTIL contains machinery and economic parameters, and suitable hours For Field operations. The detailed content oF the File CONTIL is presented in the User's Guide For the model (Appendix C)._ Input data For machinery parameters were obtained From direct measurements, secondary data or estimations (speed, eFFiciencies, price oF equipment and custom-hire). Parameters For power requirements, repair and resale values were assumed to be equal to those used in the original model. Economic parameters included cost oF Fuel and labor along with the relative inFlation For machinery, labor and Fuel. Values For these parameters were those in eFFect in 1985 in the Yaqui Valley or in the collective eJidos. Interest was assumed at 11, because no real interest was charged to machinery. In Fact, real interest was negative, because credit was subsidized For eJidos at a rate below the inFlation. The periods For payment oF loan on machinery purchases were 5 years, with zero down payment. Time available For Field work was calculated based on records oF daily rainFall, and the hours per day For speciFic Field operations in the eJidos (Table 4.12, Chapter 4). A new computer program was developed to calculate suitable climatic days per week, based on 26 year records of daily rainFall. The Flow chart oF the computer program is 96 presented in Figure 5.2. Relationships For estimation oF non-suitable climatic days were developed with the assistance oF Francisco Lapez Lugo oF CIMMYT, Mexico; Field personnel oF CAEVY and consultation with researchers oF CAEVY and CIMMYT. Two predominant soil types oF clay and loam were considered. The procedure For determination oF non-suitable climatic days For speciFic operations was based on the Following criteria: a) Maximum precipitation that allows machinery to operate in the Field (Table 5.2.) b) Range 0F daily rainFall that impedes the operation oF machinery in the Field the same day (Table 5.2.). c) Empirical relationship between daily rainFall and non-suitable days when rainFall exceded the limit in point b) (Table 5.3. and Table 5.4.). d) Maximum non-suitable days that can occur due to heavy rains during one day, or continous rain periods. These periods were obtained From the 26-year record oF daily precipitation (Table 5.5.). The computer program consisted oF various steps. First, a File RAINFIL was Formulated which contains daily rainFall in milimeters, along with the day it occurred For the years 1960 through 1985. Second, the File RAINFIL was used to calculate non-suitable days For each week, during 26 years. An intermediate File DAYSPHK was created For 97 ‘ READ RAINFILL 26 YEARS DAILY RAINFALL‘ N Subroutines to Y Calculate Suitable Days ECALL SUBROUTINE HARVCOT DEPENDING OM is 1 HARVSOY HEEK men TILLCOT TILLHHT SEEDHHT END N OF DATA ‘I CREATE INTEMEDIATE FILE DAYSPHK SUM SUITABLE DAYS 1 FOR EACH HEEK, 26 YR w CALCULATE FREQUENCIES OF SUITABLE DAYS FOR EACH “EEK CALCULATE SUITABLE DAYS AT THREE PROBABILITY LEVELS l PRINT LIST OF SUITABLE DAY ( STOP > Figure 5.2. Flow Chart For Suitable Days Program. 98 Table 5.2. Non-Suitable Days as Determined by Daily Precipitation. Clay Loam "HEAT A1 89 A 8 mm mm mm mm Spraying(Jan) < 5 6-8 ( 6 7-9 Tillage(Oct-Nov) < 5 6-8 < 8 9-12 Seeding(Nov-ch) < 6 6-12 < 10 ii-i5 SOYBEAN Row-Cultivator ( 8 9-15 < 10 11-15 (Jun-Aug) Harvest(Sep-Oct) < 5 6-19 < 8 9-12 COTTON Tillage(Jan-Feb) < 5 6-8 < 7 8-10 Cotton Picker < 8 9-10 < 10 11-15 (Jun-Aug) ‘ A: Maximum rainFali(mm) that does not aFFect the operation the same day. 9 8: Range oF rainFall that impedes the machine iF it enters the Field the same day oF rain. Source: Francisco Lapez Lugo, CIMMYT, Mexico. Personal Communication. Table 5.3. Number or Non-Suitable work Days Caused by a One-Day Rain For Clay Soil. 99 Relationship between precipitation and “HEAT number 0F non-suitable days. Spraying(Jan) mm‘ 12 days1 5 Tiliage(Oct-Nov) mm 8 10 12 14 16 18 20 days 1 3 4 4 5 5 6 Seeding(Nov-Dec) mm 15 20 23 25 27 29 30 days 2 3 4 5 6 7 8 SOYBEAN Row-Cultivator mm 17 20 23 25 27 29 30 (Jun-Jui-Aug) days 2 3 4 5 6 7 8 Harvest(Sep-Oct) mm 13 16 19 22 26 days 2 3 4 5 6 COTTON Tiliage(dan-Feb) mm 10 12 14 16 18 20 days 2 3 4 5 6 7 Harvest(Jul-Aug) mm 14 17 20 24 28 days 2 3 4 5 6 1 Precipitation in a single day, mm 2 Non-suitable days due to above rainFall. Source: communication. Francisco Lopez-Lugo, CYMMYT, Mexico. Personal 100 Table 5.4. Number oF Non-Suitable work Days Caused by a One-Day Rain For Loam Soil. Relationship Between precipitation and “HEAT non-suitable days. Spraying(dan) mm‘ 12 16 20 24 28 days1 2 3 4 5 6 Tiliage(Oct-Nov) mm 14 17 20 24 28 days 2 3 4 5 6 Seeding(Nov-Dec) mm 18 22 26 30 34 days 2 3 4 5 6 SOYBEAN Row-Cultivator mm 20 24 28 32 36 (Jun-Jul-Aug) days 3 4 5 6 7 Harvest(Sep-Oct) mm 17 20 24 28 32 days 3 4 5 6 7 COTTON Tlilage(Jan-Feb) mm 14 17 20 23 26 days 2 3 4 5 6 Harvest(dul-Aug) mm 17 22 26 30 35 days 2 3 4 5 6 1 Precipitation in a single day, mm 2 Non-suitable days due to above rainFall. Source: Francisco Lopez-Lugo, CYMMYT, Mexico. Personal Communication. 101 Tfiie 5.5. Maximum Delay(days) Due to Heavy Rains During Two or More Days. Type oF Soil Month Operation RainFall Clay Loam A; January Tillage (cotton) 89 30 25 Spraying 89 30 25 July Cultivation (soybean) 90 27 24 Cotton Picking 90 29 26 August Cotton Picking 140 35-40 30-35 September Tillage 70 27-31 24-28 Soybean Harvest 70 26-30 22-26 October Tillage 105 25-30 21-24 November Tillage and 120 30-35 25-30 Seeding Hheat December Tillage and 65 24-27 20-23 Seeding Hheat Source: Francisco Lopez Lugo. communication. CIMYT, Mexico. Personal 102 determining suitable days per week For each year. Fourth, aFter analyzing "File DAYSPNK and checking with the real data, suitable days For clay and loam soil, at 0.8, 0.7 and 0.5 probability levels were determined, using cumulative distribution Functions For the 26 years For each calendar week (Shown in Table 5.6.). To obtain suitable climatic hours per week, the suitable days were multiplied by the number oF hour per day For speciFic periods. The main operations at diFFerent time periods were considered in assigning hours per day to a given week. Hours per day were based on results presented in Chapter 4, Section 4.4.4. Suitable hours per week, For clay and loam soil, at 0.8,0.7 and 0.5! probability level are shown in Appendix C. 5.3.2. Rotation Files Crop rotation Files contain sequences and calendar dates within which an operation should be completed. Two tillage systems, with 5 rotations each were designed For this study. These Files were: COVEN, For conventional tillage system. REDUC, For reduced tillage system. The content oF the two rotations Files used For validation oF the model are described and shown in the User's Guide (Appendix C). The tillage systems were prepared, based on data collected in the Yaqui Valley and presented in Chapter 4. The conventional tillage system is commonly used in the 103 Suitable Days Each Week oF the Year at Three Probability Levels For Table 5.6. Yaqui Valley Clay and Loam Soil. Type oF Soil Clay Soil Loam Soil HEEK‘ 801 703 501 801 70! 503 .Onvonunv0nun“0.0nvonunuonunv0.unv0.0nv0nu0.unv9.54.0nlnu0.2KTOnu0 7ul7.7al7.7al7.7~l?.7oI7.7"I7.7617.7—I7.7ol7.7,0574:u5,b7.6.9Ru6qI onu0.0.unv0.0nv0.0nu0.0nv0.unv0.UnuDAnnuonuQ.9.1‘.4ales3nve,7}fieu4 7n!$.75!7.7»!7.7~I?.7nl7.7—I7.7"(7.7al7.7alAv5162325¢245a59_0n¢4.5 zaliuznéAvonunvo.unvo.unv0Aunuoxunuo.UnuOAU1.1n‘9.1.07.1~lO—5n¢951 R66.bau3,b7.7n!7.7.!7.7al?.7al7.7~I7.7.l?.7,bfiu4.11.2A04.24In714u4 0.0nuoxunvDAUnuonunv0.unv0.unuDAUnvo.Unv0.unuohueq7ndnu8.0955.bnv0 7.7al7.7a!7.7"I7.7nlv.7—I7.7"I7.7»!7.7al7.7"(7.7.ba,5,bev7104:6vr7 Ozunv0.0nu0AUnuDAUnu0.unv0.unv0.UnVOAUnvoxuo,9n‘a.8.9ev7~34.9.99.3 7.!7.7-l7.7~l7.7.17.7al7.7"(7.7"(7.7517.7ulau5,ba.3.d2.5;0240.94.6 2.Unoonlnvoxunvonunvo.unvoxunvonunv0.Unu0.u1.1n¢9_6alo,0.11.6’01.2 6~I7.7.97.7»!7.7-I7.7ol7.7517.7”(7.7ql7.7.lAu5.41.1n¢nv5n59.0n¢4.4 -23456789mumnummnmmmanagzxmmmmmasmsxysmw 104 (Cont'd) Table 5.6. Type oF Soil Clay Soil Loam Soil HEEK‘ BOX 70% 501 BOX 701 501 000000000000 e e e e e e e e e m e e 777777777777 480009000009 66LLL6LLLLL6 2o19_0,6Aw2,bnu6.uaw adas6nla.5,bcm7lb?.6 0.0.0.0.0.0.0.0.0.00.0. I LLLLLLLLL7LL 900000000000 eeeeaeeeeeee 677777777777 £26.0.0.0.0.0.0.0.0.7. 556LLLLLLLL6 123456789012 4.4494.4494.4418u5_0 1Heeks or year beginning January 1. 105 eJidos, based on recommendation oF CAEVY and the Technical Assistance Area 'oF Coalition. Reduced tillage was an alternative system which does not include subsoillng and/or disk plowing. Disk harrow, Furrower and land leveling are reduced by one or two passes each. It was designed based on Field experiments carried out at CAEVY. Dates For operations are based on results oF survey on 15 eJidos, and inFormation From the CAEVY. Tables 5.7, 5.8. and 5.9. show the list oF operations and recommended dates. 5.4. MODEL ASSUMPTIONS The Following assumptions were made For the model analysis: -Size oF ejidos between 100 to 1200 hectares. -Economic assumption: Zero real relative inFlation For machinery, Fuel, and wages was considered. Credit For purchasing machinery was 13. -Prices and costs in the computer model are in thousand Mexican pesos For the period May-August 1985, when the major part oF economic inFormation was obtained (Exchange rate at that time was about 250 pesos per dollar). Two type oF tractors were considered in the model: 1) Primary or tillage tractors were assigned to disk plowing, disk harrowing, land plane and subsoiling. Minimum size assumed was 37 kw. 2) Lflfllity or secondary tractor were assigned to planting, 106 Table 5.7. Recommended Dates For Hheat AFter Soybean Field Operations. Code Machine Date Range Heek Number Operation Initial-Final Initial-Final 1 Combine Soybean1 9/20-10/15 38-41 6 Subsoiler 10/01-10/30 40-44 9 Disk Plow 10/15-11/30 42-48 11 Disk Harrow 10/15-11/30 42-48 11 Disk Harrow 10/15-11/30 42-48 8 Land Plane 10/15-11/30 42-48 7 Fertilizer Applic. 10/20-11/30 43-48 10 Disk Harrow 10/20-11/30 43-48 12 Hood Frame 10/25-11/30 44-48 13 Seeding2 11/14—12/15 46-50 15 Furrowing 11/15-12/15 47-50 16 Ground Spraying 01/07-01/30 2-4 1 Optimum date For combine soybeans: weeks 38-39. 2 Optimum date For seeding: weeks 47-50. Seeding was assumed on Dec. 1. Source: Centro Agricola Experimental del Valle del Yaqui. 107 Table 5.8. Recommended Dates For Soybean AFter Hheat Field Operation. Code Machine Date Range Heek Number Operation Initial-Final Initial-Final 1 Combine Hheat1 4/15-5/30 16-21 11 Disk Harrow 4/20-5/31 17-22 12 Hood Frame 4/20—5/31 17-22 7 Fertilizer Applic 4/20-5/31 17-22 10 Disk Harrow 4/20-5/31 17-22 15 Furrowing 4/20-5/01 17-22 15 Furrowing 4/30-6/14 18—23 14 Planting2 5/01—6/15 18-24 5 Cultipacker 5/15-6/30 20-26 15 Furrower 6/05-7/10 23-28 17 Row-Cultivator 6/20-7/25 25-29 15 Furrower 7/10-8/15 28—33 17 Row-Cultivator 1 Optimum date For combine wheat: weeks 16-18. 2 Optimum date For planting: weeks 18-22. Source: Centre Agricola Experimental del Valle del Yaqui. 108 Survey on Collective EJidos. Table 5.9. Recommended Dates For Field Operation For Cotton Production AFter Soybean. Code Machine Date Range Heek Number Operation Initial-Final Initial-Final 1 Harvest Soybean 9/20-10/15 38-41 6 Subsoil 1/01-2/15 1-76 9 Disk Plow 1/01-2/15 1—7 11 OFFset Harrow 1/01-2/15 1-7 11 OFFset Harrow 1/15-3/04 3-9 8 Land Plane 1/15-3/04 3-9 7 Fertilizer Applic. 1/22-3/04 4-9 10 Disk Harrow 1/20-3/04 4-9 15 Furrowing 2/04-3/04 6-9 15 Furrowing 2/14-3/14 7-10 14 Planting 2/15-3/15 8-12 17 Row-Cultivator 4/05-5/05 14-18 15 Furrowing 4/05-5/05 14-18 17 Row-cultivator 5/01-6/01 18-22 15 Furrowing 5/01-6/01 18-22 17 Row-cultivator 5/11-6/15 20-24 16 Ground Spraying 3/01-4/01 10-13 2 Harvest Cotton 7/20-8/30 30-35 4 Rotary Shredder 8/01-9/30 31-39 Sources: Centro Agricola Experimental del Valle del Yaqui. 109 Furrowing row cultivation, spraying, wood Framing and stalk cutting. Minimum size For utility tractors was 22 kw. CHAPTER 6 MODEL VALIDATION Two types oF analysis were made For the validation oF the model For the conditions oF the Yaqui Valley. The First analysis pertained to the sensitivity oF the model. This was to veriFy that the model responded reasonably to changes in maJor parameters. Secondly, machinery sets selected by the model were compared with selected actual machinery sets in representative sizes oF eJldos. 6.1. SENSITIVITY ANALYSIS SpeciFic hypotheses For main parameters were Formulated For validation oF the model, based on practical experience or previous studies. EJidos sizes oF 300, 600 and 1,200 hectares were chosen as representatives oF small, medium and large eJidos. The wheat-soybean crop rotation was most popular in the eJidos, so it was used For validation. Conventional tillage on clay and loam soils were considered in the validation oF the wheat-soybean rotation in the model. 6.1.1. Probability oF Suitable Heather. Hypothesis: Use oF a lower probability level For suitable weather will allow more available days smaller For Field 110 111 operations and decrease the machinery requirement. Three probability levels For suitable weather were compared: 0.8, 0.7 and 0.5. An 0.8 probability level means that the eJidatarlos could expect these results in 8 out 0F 10 years. Tables 6.1 to 6.3 present results oF computer model runs For 300 and 600 hectares oF the wheat-soybean rotation on clay soil. As was expected the model selected larger machines at 0.8 level. As the probability level decreased, there was more time available For a given operation, so the model selected Fewer and/or smaller tractors and machines. Timeliness cost decreased as probability level changed From 0.8 to 0.7, and was zero at 0.5 level For all example runs, because the model allowed more time to complete operations within the optimum dates. For 300 hectares oF wheat-soybean rotation with conventional tillage, the model selected the same utility tractors, combines, Fertilizer spreaders, wood Frames and row equipment at 0.8 and 0.7 levels. Other machines were larger at 0.8 level (Table 6.1) The model selected the same machinery set at 0.8 and 0.7 level For 300 hectares 0F “-8, with reduced tillage on clay soil (Table 6.2). The set selected at 0.5 level was smaller, and had zero timeliness cost, resulting in a 281 land 10! reduction in total cost, with respect to 0.8 and 0.7 levels. 112 Tmle 6.1. Machinery Selection For Tires Levels of Prabdwillty For Suitwie Heather For 300 He iheat-Soybm Rotation with Conventional Tillne on Clay Soil. Probability oF Sultdwle Header 0.8 0.7 0.5 Machines Size1 Hairs Size Hours Size Hairs Prima'y Tractors (kw) 2'96 316 21184 364 119 547 Utility Tractor (kw) 2'57 313 2'57 318 45 681 mine (row) 8 163 8 163 6 217 Fertilizer Sareader (m) 9.1 58 9.1 58 12.2 44 Lead Plate (m) 3.7 5 3.7 as 4.3 73 Hood Frme (m) 3.0 191 3.0 191 3.7 159 Did: Plow (disk) 2'5 195 2114 119 6 159 ms: Harow (m) 3.8 128 3.4 145 4.7 103 OFFset Harow (m) 3.8 229 3.4 260 4.1 212 Grain Drill (m) 4.3 56 3.7 65 4.9 49 Row Planter (raw) 8 43 8 43 6 57 Furrower (rain 8 153 8 153 6 204 Sprayer (row) 16 24 16 24 12 31 Rout-cultivator (rm) 8 103 8 103 6 138 Cost 803 Machinery 23.53 22.84 19.99 Fuel 8.56 8.60 8.64 deor 1.56 1.68 1.59 Timeliness 8.57 2.11 04!) Total 42.23 35.23 30.22 1 m and size indicated. 57 kw. each. For mle2'57mems 2tractors of 113 Tfile 6.2. Machinc'y Selection For Tires Levels oF Probdallity For Suitdale Heat!" For 300 lb Heat-Soybem Rotation with Refined Tillne on Clay Soil. Probdallity of Sultdale Health." 0.8 0.7 0.5 Ibchlnes Size1 Hairs Size iers Size M Prime-y Tractors (kw) 84.7 331 84.7 331 96.2 301 Utility Tractor (kw) 57.3 407 57.3 407 43 492 mine (row) 8 163 8 163 6 217 Fertilizer M (m) 9.1 58 9.1 58 9.1 58 Laid Pine (m) 3.7 fl 3.7 as 3.7 5 Did: W (m) 3.4 73 3.4 73 3.8 64 OFFset Ha'row (m) 3.4 173 3.4 173 3.8 153 Grain Drill (m) 3.7 65 3.7 65 4.3 56 Row Planter (row) 8 43 8 43 6 57 Farmer (row) 8 115 8 115 6 153 Sprayer (row) 16 24 16 24 12 31 Row-cultivator (row) 8 103 8 103 6 138 Cost Slha Machinery 18.11 18.11 17.11 le 5.53 5.53 5.66 Lmor 0.99 0.99 1.11 Tlnliness 8.57 2.11 0.1!) Total 33.20 26.74 23.88 1 m aid size indicated. tractors oF 57 kw each. For mle 2'57 moms 2 114 Comparisons For a 600 hectares eJido resulted in larger number and/or size oF machines selected at 0.8 level than the equipment selected at 0.7 and 0.5 levels (Table 6.3). A timeliness cost Factor was present at the” 0.7 probability level, while it was zero at 0.5 level. It doubled between the 0.7 and 0.8 probability levels. The results presented conFirm the hypothesis For the parameter that a lower probability level allows more available time and decrease the machinery requirements. 6.1.2 EJido Size Hypothesis: As the size oF ejidos increase the eFFiciency oF machinery use increases thus reducing costs. Various eJldo sizes were compared under diFFerent conditions. A summary oF the total costs For machinery sets selected at 0.8 probability level For a wheat-soybean rotation is presented in Table 6.4. Two tillage systems, on clay and loam soils were compared. The Following relationships were Found: a) The total cost machinery cost/ha decreased as the crop area increased For clay soil, while For loam soil the total cost/ha decreased From 150 to 600 hectares, but increased From 600 he to 1,200 hectares. b) The machinery costs For reduced tillage were lower than For conventional tillage. And c) machinery sets For clay soil had greater cost than For loam soils. Details oF these comparisons Follow. 115 Tdale 6.3. Machinery Selection For Tl‘ree Probability Levels For Suitable Heathlr For 600 He “teat-Soybem Rotation with Conventional Tillme on Clay Soil. Probdaillty of Suitdaie Heather 0.8 0.7 0.5 Machines Size1 it's Size it‘s Size it's Prima'y Tractors (kw) 3'119 365 2'119 547 211119 547 Utility Tractor (kw) 2'57 574 48 6% 2'48 682 Cdflne (row) 2'8 163 2'6 217 2'6 217 Fe~tilizer Spreader (m) 12.2 87 12.2 87 12.2 87 Land Plaie (m) 2114.3 73 4.3 146 4.3 146 Hood Prue (m) 2'3.7 159 2'3.7 159 2'3.7 159 Did: Plow (dist) 3'6 106 2'6 159 2'6 159 Did( l'la'row (m) 4.7 215 4.7 2% 4.7 2% OFFset i-imrow (m) 2'4.1 212 2'4.1 212 2'4.1 212 Grain 0m: (m) 4.9 98 4.9 W 4.9 98 Row Platter (row) 8 86 6 114 6 114 Furrower (row) 8 3% 6 4m 6 400 Sprayer (row) 16 47 12 63 12 63 Row-cul tivator (row) 8 207 6 275 6 275 Cost Slha Machinery 21 . 72 19.21 19.21 Fuel 8.56 8.66 8.66 Lbor 1.41 1.59 1.59 Timeliness 8.59 4.81 0.00 Total 40.28 34.26 29.45 1 Mater mid size indicated. tractors 0F 57 kw each. For mic 2'57mems two tractors of 57 Table 6.4. 116 EFFect oF Size, Soil Type and Tillage System Upon Machinery Cost (Thousand Mex. 4 ) For Hheat-Soybean Rotation at 0.8 Probability Level. Type oF Tillage Conventional Reduced EJido Size Clay Loam Clay Loam __w2; 150 43.97 34.52 37.00 28.66 300 42.23 34.30 33.20 26.16 600 40.28 31.78 32.64 25.29 900 39.93 32.24 32.16 25.32 1200 40.06 33.32 31.89 26.45 117 Machinery sets selected For Four eJido sizes and their costs, For conventional and reduced tillage, are shown in Tables 6.5 and 6.6. For conventional tillage the cost per hectare was higher For 150 hectare eJido, and decreased For a 300 and 600 hectare eJido. No important cost variation resulted From increasing the size From 600 to 1,200 hectares. There was no constant increment between eJido size and number and size oF machines selected, i.e, doubling the area in most cases did not result in doubling machines sizes or capacity. Depending on the operations and time available, the model increased the number oF machines or _incremented the size thus, changing the annual use oF machines. For conventional tillage where there are more time constraints, the larger ejidos had more Flexibility (more options) For selecting diFFerent combinations oF size and number oF machines, resulting in less machinery cost. The results presented in this section, in general conFirm the hypothesis For this parameter: although machinery reductions due to increased size were not great nor always consistent. 6.1.3. Rotations. Hypothesis: a) The inclusion oF more crops in a rotation will increase machinery eFFiciency and lower costs. b) Rotations that include crops with a high demand For Field operations (For 118 Table 6.5. Hachincry Selected ior Tour Ejldo Sizas ior Hheat-Soybean Rotation. nith Conventional Tillage, on Clay Soil, at 0.8 Probability Level. Sizo oi Ejido in Hectars 150 301 601 1210 flachlnos Size' Hours Size Hours Size Hours Size Hours Priaary Tractors (in) 56 567 2196 316 31119 365 7196 362 Utility Tractor (in) 40 624 2157 313 2157 574 5143 588 Cochin. iron) 6 116 8 163 218 163 616 145 Fertilizer Spraador la) 6.1 44 9.1 58 12.2 87 9.1 233 Land Piano in) 3 51 3.7 85 214.3 73 313.7 113 Hood Franc (a) 2.4 119 3.1 191 213.7 159 413.1 191 Disk Plon (dish) 5 95 215 95 316 106 715 109 Dist Narron 1a) 1.6 151 3.8 128 4.7 206 313.8 171 Oilsat Barron (I) 1.6 270 3.8 299 214.1 212 313.8 306 Grain Drill in) 2.4 49 4.3 56 4.9 98 214.3 112 Ron Plantar iron) 6 31 8 43 8 86 216 114 Furronar iron) 3 218 8 153 8 306 316 272 Sprayer iron) 12 17 16 24 16 47 12 125 Ron-cultivator iron) 3 147 8 103 2 207 316 184 Cost $1». lachinary 25.01 23.53 21.72 21.64 Fuai 9.21 8.56 8.56 8.61 Labor 2.88 1.56 1.41 1.74 Tiaolinass 6.87 8.57 8.59 8.06 Total 43.97 42.23 41.28 40.06 1 Hunter and size indicated. For axaapla 2157 loans 2 tractors oi 57 in each. Table 6.6. Machinery Selected for Four Ejido Sizes Tor Hheat-Soybean Rotation, nith Reduced Tillage, on Clay Soil. at 0.8 Probability Level. 119 Size 01 EJido in Hectars 150 600 i200 Machines Size1 Hours Size Hours Size Hours Size Hours Priaary Tractors (tn) 54 244 84.7 331 20119 267 3096.2 402 Utility Tractor itn) 43 282 57 407 57 754 2'86 607 Coablna iron) 6 109 8 163 2'8 163 3'12 145 Fertilizer Spreader in) 6 44 9.1 58 12 87 9.1 233 Land Plane ia) 3 51 3.7 85 4.3 146 3.7 113 Disk Harron ia) 2.1 57 3.4 73 4.7 103 203.8 128 Oilset flarron ia) 2.1 136 3.4 173 2*4.1 141 313.8 204 Grain Drill ia) 2.4 49 3.7 65 4.9 98 204.3 112 Ron Planter iron) 6 29 8 43 8 85 12 114 Furroner iron) 6 76 8 115 8 229 12 306 Sprayer iron) 12 16 16 24 16 47 24 63 Ron-cultivator iron) 6 69 8 103 8 206 2012 138 Cost 0lha lachinery 23.46 18.11 17.60 17.57 Fuel 5.70 5.53 5.56 5.48 Labor 1.40 0.99 0.89 0.79 Tlaellness 6.44 8.57 8.59 8.06 Total 37.00 33.20 32.64 31.89 ‘Iuabar and size indicated. For enaaple 2’57 leans 2 tractors of 57 in each. 120 example cotton) will require larger and more machinery. Tables 6.7 and 6.8 show the results of simulation for 5 rotations used in the region, including wheat (H), soybean (S) and cotton (C). The rotations including cotton required additional machinery such as cotton picker and stalk cutter, and resulted in higher cost/ha than the rotations without cotton. For 300 and 600 hectares the cost For H—S-C rotation was 253 higher than the cost for “-5, and 16.51 (300 ha) and 13: (600 ha) higher than H-H-S-C rotation. The Hheat-Hheat and H-H—S were the less expensive rotations. Cotton and soybeans require more machinery and fuel. Timelines cost varied between rotation, being higher for rotations including cotton and soybean. Rains during cotton and soybean harvest seasons were responsibles for increased timeliness cost. Notice the zero timeliness for H-H rotation, due to no rains during the harvest season. The model selected more tillage tractors, with less hours of use, for rotations with two parcels (H-S, H—H). The machinery sets selected For rotations with 3 or 4 parcels included less tractors, with more hours of use. The same tendency could be observed For utility tractors, cotton pickers and disk plow. The validation results further confirm the hypothesis that more crops in a rotation lower costs with the exception of a high demand crop such as cotton. 121 Table 6.7. Machinery Selected for Five Crop Rotations for 300 He at ' 0.8 Prob. Level, Using Conventional Tillage on Clay Soil. Rotations H-S H-S-C U-U U-U-S H-I-S-C Machines Size Hours Size Hours Size Hours Size Hours Size Hours Priaary Tractors ikn) 2‘96 316 98 864 22139 372 119 648 98 893 Utility Tractor ihn) 2'57 313 2'43 389 2054 191 57 524 43 714 Calbine iron) 8 163 6 145 8 163 8 163 6 163 Cotton Picker iron) -- --- 2'2 81 -- --- -- --- 2 122 Stalk Cutter ia) -- --- 201.8 71 -- --- -- --- 1.8 106 Subsoiler -- --- 2.4 113 -- --- -- --- 2.4 85 Fertilizer Spreader ia) 9.1 58 9.1 58 12.2 44 12.2 44 9.1 58 Land Plane ia) 3.7 85 3.7 113 4.6 136 4.3 97 3.7 127 Hood Fraaa ia) 3.0 191 3.0 127 4.3 136 3.7 159 3 143 Disk Pion (dish) 2'5 95 5 255 2'7 136 6 212 5 286 Disk Harron ia) 3.8 128 3.8 128 5.5 89' 4.7 103 3.8 128 allsat Harron is) 3.8 229 3.8 255 4.7 246 4.1 236 3.8 267 Grain Drill 1a) 4.3 56 4.3 37 6.1 78 4.9 65 4.3 56 Ron Plantar 8 43 6 76 -- -- 8 29 6 57 Furroner iron) 8 153 6 204 8 76 8 127 6 178 Sprayer iron) 16 24 12 42 16 47 i6 31 12 47 Ron-Cultivator iron) 8 103 6 92 -- -- 8 . 69 6 69 Cost Olha - Machinery 23.53 32.44 26.59 21.99 26.61 Fuel 8.56 12.15 10.00 9.06 11.19 Labor 1.56 1.97 1.42 1.47 1.95 iiaellness 8.57 6.01 0.00 4.31 5.37 Total 42.23 52.27 38.00 36.83 45.11 122 Table 6.8. Machinery Selected for Five Crop Rotations for 600 Ha at 0.8 Probability Level, Using Conventional Tillage on Clay Soil. Rotations il-S li-S-C H-il il-ll-S ll-il-S-C Machines Size Hrs Size Hrs Size Hrs Size Hrs Size Hrs Priaary Tractors (kn) 3'119 365 2'123 739 4'139 372 2‘139 567 2'98 893 Utility Tractor ikn) 2'57 574 3'45 478 4'54 191 2'57 488 2'43 714 Coabine iron) 2'8 163 2'6 145 2'8 163 2'8 163 2'6 163 Cotton Picker iron) -- --- 3'2 108 -- --- -- --- 2'2 122 Stalk Cutter ia) -- --- 3'2.1 81 -- --- -- --- 2'1.8 106 Subsoiler -- --- 2'3 91 -- --- -- --- 2'2.4 85 Fertilizer Spreader in) 12.2 87 12.2 87 12.2 87 12.2 87 9.1 116 Land Plane ia) 2'4.3 73 4.3 194 2'4.6 136 4.6 181 3.7 254 Hood Fraae ia) 2'3.7 159 3.7 212 2'4.3 137 4.3 273 3.0 286 Disk Pion idisk) 3'6 109 2'6 212 4'7 137 2'7 182 2'5 286 Disk Harron ia) 4.7 206 4.7 206 5.5 178 5.5 178 3.8 255 01iset Harron ia) 2'4.1 212 4.1 472 2'4.7 247 4.7 411 3.8 534 Grain Drill ia) 4.9 98 4.9 65 6.1 157 6.1 105 4.3 111 Ron Planter 8 86 6 152 -- -- 8 57 6 114 Furroner iron) 8 306 6 407 8 153 8 255 6 356 Sprayer iron) 16 47 12 84 16 94 16 63 12 94 Ron-Cultivator iron) 8 207 6 184 -- -- 8 138 6 138 Cost 0lha Machinery 21.72 29.26 26.11 21.22 25.95 r001 0.51. 11.64 10.01 ' 9.03 11.19 Labor 1.41 1.76 1.42 1.34 1.95 Tiaeliness 8.59 7.69 0.00 4.31 5.37 Total 40.28 50.35 37.54 35.90 44.45 123 6.1.4. Soil Types Hypothesis: Ligther soils such as a loam versus a heavy clay, decrease machinery costs. Two types of soils clay and loam, were predominant in the collective eJidos. Table 6.9 presents simulation results for clay and loam soils for 600 Ha of wheat-soybean and wheat-soybean-cotton rotations. Conventional tillage, at 0.8 probability level was considered during validation. Changing from clay to loam soil resulted in less power, and less or smaller machines. Machinery and timeliness costs made the difference in total costs for the machinery between clay and loam soil. There was a 211 total cost reduction for loam soil, as compared with clay soil for the "-8 rotation, and 121 for the H-S-C rotation. The results obtained confirm the hypothesis for soil types, that machinery costs for crop production on loam soils are less than for clay soils. 6.1.5. Economic Parameters. Hypothesis: The model will show that a decrease in interest rates will influence the selection of more larger machinery that have a lower real cost. Three interest rates were compared; 11 which used for the model validation, -201 and -401. Results are presented in Table 6.10. As expected, there was a drastic decrease in the machinery component of total cost per hectare as interest rates dropped. The total cost per 124 Table 6.9. Machinery Selected for Tno Soil Types 600 Ha Hheat-Soybean Rotation Using Conventional Tillage at 0.8 Probability Level. Hheat-Soybean Meat-Soybean-Cotton Clay Loaa Clay Loaa Machines Size Hours Size Hours Size Hours Size Hours Priaary Tractors (kn) 3'119 365 2'129 478 2'123 739 2'111 739 Utility Tractor itn) 2'57 574 2'57 542 3'45 478 2'57 614 Coabine iron) 2'8 163 2'8 163 2'6 145 2'4 217 Cotton Picker iron) -- --- -- --- 3'2 108 2'2 162 Stalk Cutter ia) -- --- -- --- 3'2.1 81 2'2.1 121 sienna -- --- -- -- 213 91 3 ‘ 101 Fertilizer Spreader ia) 12.2 87 12.2 87 12.2 87 12.2 87 Land Plane ia) 2'4.3 73 4.6 136 4.3 194 4.3 194 Hood Fraae (a) 2'3.7 159 2'4.3 137 3.7 212 3.7 212 01st Plon (dist) 3'6 109 2'7 137 2'6 212 2'6 212 [list Han'on 1a) 4.7 206 5.5 178 4.7 206 4.7 206 Uliset Harron ia) 2'4.1 212 2'4.7 185 4.1 472 4.1 472 Grain Drill in) 4.9 98 6.1 78 4.9 65 4.9 65 Ron Planter 8 86 8 86 6 152 8 114 Furronar iron) 8 306 8 306 6 407 8 306 Sprayer iron) 16 47 16 47 12 84 16 63 Ron-Cultivator iron) 8 207 8 207 6 184 8 138 Cost 0/ha Machinery 21.72 20.45 29.26 25.36 Fuel 8.56 8.06 11.64 10.84 Labor 1.41 1.30 1.76 1.73 Tiaaiinass 8.59 1.97 7.69 6.30 Total 40.28 31.78 50.35 44.22 125 Tdale 6.10. Machinery Selection with Three Interest Rates. 00-3 Rotation, 6130 Fla with Corvvmtlonal Tillme on Clay Soil. Interest Rate, 3 l -20 -40 Machines Size1 Hrs Size Hrs Size it‘s Print-y Tractors (kw) 3"119 365 2'173 398 3139 319 Utility Tractor (kw) 2'57 574 2'86 419 2‘86 434 Mine (row) 2'8 163 2'12 109 21112 109 Fertilizer Spreader (m) 12.2 87 12.2 87 12.2 87 Laid lee (m) 2'4.3 73 5.5 113 2*4.6 68 Hood Franc (m) 2"3.7 159 2.4.6 127 2‘4.3 137 Disk Plow (disk) 3‘6 1% 2'9 106 3'7 91 Disk Han—ow (a) 4.7 215 6.9 142 5.5 178 Offset Fir-row (m) 2'4.1 212 5.3 328 2'4.7 1% Grain Will (a) 4.9 98 7.3 65 6.1 78 Row Plaster (row) 8 86 12 b7 12 57 Firrower (row) 8 3% 12 204 12 204 Sprayer (row) 16 47 24 31 24 31 Row-cultivator (row) 8 207 12 138 12 138 Cost SIha Machinery 21.72 12.89 5.53 Fuel 8.56 8.56 8.55 Labor 1.41 1.02 1.12 Timeliness 8.59 6.46 6.46 Total 40. 28 28.93 21 . 66 116.16.:- 81d size. For exaple 2'57 news 2 tractors of 57 kw each. 126 hectare decreased from 40,280 Mexican pesos per hectare with 11 interest, to‘ 28,930 Mex. slha with -203 of interest, which represent a 28.21 decrease. The cost per hectare further decreased to 21,660 Max Slha with.-401 of interest, which represent a decrease of 46.2! from the cost at 1! of interest. The machinery sets were different for the three interest rates (Table 6.10). In general the model selected larger machines as their real prices decreased because of lower interest rates. This effect is more noticed for row equipment, because the model selected the largest machines available, even though the annual use decreased. These results confirm the hypothesis that a decrease in interest rates influence the selection of larger machinery. Therefore the model has the capacity to react to changes in economic parameters, which could occur in specific periods of time, depending on government policies in Mexico. 6.2. SIMULATED VS. ACTUAL MACHINERY SETS A second part for the validation of .the model consisted of comparing simulated and actual machinery sets in collective ejidos. Hheat-soybean rotation, using conventional tillage in clay soils was used for simulation. Two actual eJidos were selected with equivalent areas to compare machinery sets with the least cost sets selected by the model at 0.8 probability level. Results of 127 these comparisons are presented in Table 6.11. The eJidos have purchased the machinery since they were created in 1976. Hheat-soybean was the most common rotation in the last five years. The small eJido, with an average area seeded of 300 hectares of wheat-soybean rotation had 7.6! more power of primary tractors than the power selected by the model. For utility tractors, the model selected two tractors of 57 kw, and the eJido owned two tractors of 57 kw and a tractor of 61 kw. Therefore the eJido had a 53! more power than selected for least cost. There was close agreement between the actual complement an the machines selected for combine and row equipment, fertilizer spreader and wood frame. The model selected one 8—row planter, furrower cultivator, whereas the eJido owned two 4—row of each of these machines. The machinery owned by the medium size eJido with 600 hectares of wheat-soybean had more capacity compared with the machinery sets selected, with the exception of primary tractors, land plane, wood frame, row planter and sprayer. Simulation resulted in half the actual number of utility tractors. The eJidos had 952 more utility tractor power than simulation power selected by the model. Actual harvesting capacity exceded the capacity selected by 37: On land leveling equipment, disk plow and offset harrow the model selected greater capacities. 128 Table 6.11. Siauiated vs. Actual Machinery Sets at .8 Probability Level. Hheat-Soybean Rotation, Using Conventional Tillage 0n Clay Soil. 300 Hectares 600 Hectares Siauiated Actual Machines Siauiated Actual Machines Machines Size1 Hours Muabar'size Size Hours Mulber'size2 Priaary Tractors inn) 2'96 316 110397 3'119 365 1101100382 Utility Tractor iln) 2'57 313 6112'57 2'57 574 61:2'57348 Coabine iron) 8 163 8 2'8 163 2'8; 6 Fertilizer Spreader ia) 9.1 58 10 12.2 87 2'10 Land Plane ia) 3.7 85 - 2'4.3 73 - Mood Fraaa ia) 3.0 191 3 2'3.7 159 3.6 Disk Plon idisk) 2'5 195 512'4 3'6 106 2'5 01st Harron ia) 3.8 128 3.2 4.7 205 3.2; 2.2 Ullset Harron ia) 3.8 229 2'3.7 2'4.1 212 3.73 3.2 Grain Drill ia) 4.3 56 3.7 4.9 98 4.2; 3.7 Ron Plantar iron) 8 43 2'4 8 86 2'4 Furroner iron) 8 153 2'4 8 306 3'4 Sprayer iron) 16 24 14 16 47 14 Ron-cultivator iron) 8 103 2'4 8 207 3'4 'Muaber and size indicated. For enaaple 2'57 aeans 2 tractors 01 57 in each. 3 0 ‘1' is used to separate aachines oi dliierant sizes. For exaaple, 110; 97 aaans one tractor 01 110 in, and one tractor 01 97 0n. 129 Row equipment agreed with selected capacities for row planter and sprayer; selected capacities were lower than actual capacity for furrower and row-cultivator. In general there was agreement between the actual machinery sets, and the model selected complement at 0.8 probability level. 6.3. DISCUSSION OF MODEL VALIDATION. The model was sensitive to changes in major parameters. Machinery selected at 0.8 probability level had larger equipment and higher cost per hectare. As expected timeliness cost decreased with a drop in probability level. At 0.5 level there was no timeliness cost, indicating that there was enough time available to complete the operations within the optimum period. The timeliness cost at 0.8 and 0.? levels indicates that it was less costly to afford some crop losses doing part of the work in the penalty period, than owning a larger or another machine. The runs with three probability levels for suitable weather were made for the purpose of testing the sensitivity of the model to changes in time available for field operations. A probability level of 0.8 was used in this study. Previous studies (Hetz, 1982) and practical experience in the U.S. (Rotz, 1983), indicated that is preferable to design machinery systems at 0.8 probability level. An 0.8 level means that the eJidos could complete the operations 8 out of 10 years, with the machinery set 130 selected. During the other two years the machinery may not complete the operations. The ejidos could work more hours per day, or custom hire specific machines during two years out of ten, when the machinery selected will probably not complete the required operations. The effect of area seeded (eJido size) on the total cost per hectare was appreciable in the range of 150 to 600 hectares. Over 600 hectares the total cost had little variation. These results indicate that the model had selected a balanced machinery set for 600 hectares, and from there on the costs increase in the same proportion as the area seeded. Due to the discrete nature of the machinery sets selected, and the matching of row equipment, some excess capacity may be selected by the model in some ranges, as the size is increased. This caused small ups and downs for total cost of machinery sets particularly over 600 hectares. The computer model was sensitive to changes in crop rotations. Machinery sets selected had different components, reflecting the capacity of the model to react to changes in operations and schedules, in the selection of the least cost machinery complement. The reactions were similar for 300 and 600 hectares for 5 different crop rotations. The model reacted as expected to soil type changes. Changing from clay to loam soil resulted in smaller and/or less equipment, with a decrease in cost per hectare. Actual machinery sets in two collective eJidos nearly matched the 0.8 probability level, reflecting 131 practical experience of eJidatarios in order to avoid losses during rainy years. In order to compare simulated results with actual machinery sets, the total machinery capacity needs to be considered. For example the model selected one 8-row planter, while the eJido owned two 4-row planters. There was a general pattern for some equipment. For row equipment it was common to use 4-row planters, cultivators and furrowers. For this study it was assumed that 6, 8 and 12-row equipment could be used in the Valley. Low cost and a surplus of labor in the eJidos could be a reason why the eJidos are not too concerned about using larger equipment, which in most cases needed to be imported. Hhen analyzing the differences between the size or number of machines selected by the model and the actual machinery, one consideration is that the eJido could have hired custom operations instead of purchasing the machines. The model did not included custom hire for validation because it was decided at the outset that the eJido would own all machinery. CHAPTER 7 SIMULATION RESULTS 7.1. COMPARISONS FOR TILLAGE SYSTEMS The computer model was applied to select machinery sets for five crop rotations used in the Yaqui Valley. Examples are presented for “-6 and H—S-C crop rotations for conventional and reduced tillage systems, on small medium and large size ejidos. Primary tractor power decreased to a third, and utility tractor power decreased by one half for reduced tillage as compared with conventionl tillage for "-8 rotation on a 300 hectare eJldo (Table 7.1). Disk plow and wood frame were not required, and harrows were smaller with reduced tillage. The grain drill had more time available due to less tillage operations, therefore a smaller machine was selected. Row equipment was the same for the two tillage systems, since they were done at different dates as tillage. Machinery and fuel cost decreased with reduced tillage, and total cost per hectare decreased by 21.41 for reduced tillage. Tractor power decreased with reduced tillage for a medium size eJido, with 600 hectares of "-8. Primary tractor dropped from three to two, and utility tractors 132 labia 7.1. l33 flachinary Selectod for lao iiiiaoo Systoas for a Hheat-Soybean Rotation on Clay Soil. 388 hectares 688 hectares Conventional Reduced Conventional Reduced llach i nos Si 29 Hours 8 i 20 Hours 8 i u liars Si 20 Hours Priaary lractors (kn) 3'96 316 84.7 330.8 3*ll9 365 2'll9 267 Utility Tractor ila) 2'57 313 57 407 2'5? 574 57 754 Coabine iron) 8 l63 8 l63 2'8 163 2'8 l63 Fortiiizor Sproador (a) 9.l 58 9.1 58 12.2 87 l2.2 87 Land Plana (I) 3.7 85 3.7 85 2’4.3 73 4.3 146 Hood Franc in) 3.8 i9l -- -- 2'3.7 l59 -- -- Disi Plan idiot) 2'5 95 -- -- 3'6 186 -- -- Disk Harrou in) 3.8 i28 3.4 73 4.7 286 4.7 li3 Oiiaot Harrou ia) 3.8 229 3.4 l73 2’4.i 212 2'i.i iii Grain Drill ia) 4.3 56 3.7 65 4.9 98 4.9 98 Ron Planter 8 i3 8 43 8 86 8 85 Furrouor iron) 8 l53 8 li5 8 386 8 229 Sprayer iron) 16 24 lb 24 l6 4? i6 i7 Ron-Cultivator iron) 8 i03 8 l83 8 287 8 286 Cost ilha Nachinory 23.53 l8.ll 21.72 l7.60 Fuel 8.56 5.53 8.56 5.56 Labor l.56 8.99 l.ii 8.89 liloiiness 8.57 8.57 8.59 8.59 Total 42.23 33.20 48.28 32.64 134 decreased from two to one changing from conventional to reduced tillage (Table 7.1). The disk plow and the wood frame were not required for reduced tillage. One land plane instead of two was selected for reduced tillage. This doubled the hours of use, thus reflecting more time available, due to fewer tillage operations. The same size of disk and offset harrows were selected, but the hours of use decreased for reduced tillage. Row equipment and fertilizer spreaders were not affected by the change to the reduced tillage system. Machinery and fuel costs per hectare decreased by 191 for reduced tilage. Conventional vs. reduced tillage practices were compared for a H-S-C crop rotation for small and medium size ejidos. Results are presented in Table 7.2. For a 300 hectare eJido less power and fewer hours of use were required for reduced tillage. The simulation model selected the same number of utility tractosr, but with slightly fewer hours of use for reduced tillage. Subsoilers, disk plows and wood frames were not required for reduced tillage, thus reducing machinery and fuel cost. The grain drill and harrows were smaller for reduced tillage, while row equipment remained the same. Total cost per hectare for reduced tillage decreased by 16.51, as compared with conventional tillage. For 600 hectares of H-S-C rotation (Table 7.2) there was a similar pattern as for 300 hectare. Tractor power and/or hours of use were reduced, while grain drill and 135 labia 7.2. Hachinery Selected for leo liilage Systees for a Hheat-Soybean-Cotton Rotation on Clay Soil. 388 hectares 608 hectares Conventional Reduced Conventional Reduced hachines Size Hours Size flours Size Hours Size Hours Prieary Tractors the) 98 864 67 485 28123 739 119 615 Utility Tractor ital 2'43 38? 2’43 334 3’45 478 3'45 488 Coabine iron) 6 145 6 145 2'6 145 2'6 145 Cotton Picker iroa) 2’2 81 2'2 81 3'2 188 3'2 188 Stalk Cutter ia) 281.8 71 241.8 71 3'2.i 81 342.1 81 Subsoiler 2.4 113 -- --- 2'3 9i -- --- Fertilizer Spreader in) 9.1 58 9.1 58 12.2 87 12.2 87 Land Plane (e) 3.7 113 3.7 113 4.3 194 4.3 194 Rood Fraee (e) 3.8 127 -- -- 3.7 212 -- --- Dist Plou (disk) 5 255 -- -- 2’6 212 -- --- Dish Harroe 1e) 3.8 128 2.4 133 4.7 286 4.7 138 Offset Harroe ie) 3.8 255 2.4 239 4.1 472 4.1 283 Grain Drill ia) 4.3 37 3.7 44 4.9 65 4.9 65 Roe Planter 6 76 6 76 6 152 6 152 Furrouer iron) 6 284 6 178 6 487 6 348 Sprayer iron) 12 42 12 42 12 84 12 84 Roe-Cultivator iron) 6 92 6 138 6 184 6 254 Cost ilha Machinery 32.44 28.88 29.26 24.71 Fuel 12.15 8.12 11.64 7.62 Labor i.97 l.43 1.76 1.17 lileliness 6.81 6.81 7.69 7.69 lotal 52.27 43.64 58.35 4l.l9 136 harrows were the same but with less hours of use for the reduced tillage. 'There was a decrease in machinery and fuel cost, with a 18.21 reduction in total cost per hectare for the reduced tillage system. The model was used to select the least cost machinery sets for 1,200 hectares of “-8 and H-S-C crop rotations (large eJldos). The conventional and reduced tillage systems on clay soil were compared (Table 7.3). For “-8 rotation there was a drastic reduction in primary tractor power, but utility tractor power had a slight increase. The model selected 3 tractors of 96 kw for reduced tillage, as compared with 7 tractors of 96 kw that were selected for conventional tillage. Three tractors of 86 kw (total of 258 kw) were required for reduced tillage as compared with five tractors of 43 kw (total of 215 kw) selected for conventional tillage. Disk and offset harrows had less hours of use. The rest of the equipment was the same in both tillage systems. No disk plows nor wood frame were required for reduced tillage. There was a cost reduction of 20.41 changing from conventional to reduced tillage system (Table 7.3). For H-S-C crop rotation there was a reduction to one half for primary tractor power and use, when changing from conventional to reduced tillage. Utility tractor power increased slightly with a decrease in hours of use. Reduced tillage did not include subsoiler or disk plow, therefore disk and offset harrowing were the only operations for seedbed preparation. Machinery and fuel cost decreased for 137 iabie 7.3. hachinery Selected for Hheat-Soybean and Rheat-Soybean-Cotton Rotation for a Large EJido 1288 ha, aith tao liliaoe Systaa on Clay Soil. Hheat-Soybean Hheat-Soybean-Cotton Conventional Reduced Conventional Rauced liachines Size Hours Size ilours Size iiours Size Home Priaary Tractors (Ru) 7'96 362 3896 482 48123 739 2’135 546 Utility lractor ital 5'43 588 3’86 687 5845 574 5'54 484 Coabine iron) 6'6 145 3'12 145 4’6 145 4'6 145 Cotton Picker iron) -- -- -- --- 6'2 188 6'2 188 Stalk Cutter ia) -- --- -- --- 582.1 97 572.1 97 Subsoiler -- --- -- --- 3'3 121 -- --- Fertilizer Spreader ia) 9.1 233 9.1 233 12.2 175 12.2 175 Land Plane ia) 383.7 113 383.7 113 2'4.3 194 284.6 181 Iood Fraae ia) 4'3 191 -- --- 2’3.7 212 -- --- Dist Plow idisk) 7’5 189 -- --- 4'6 212 -- --- Disk Harroe ia) 343.8 171 283.8 128 2'4.7 286 5.5 237 Offset Narroa ia) 383.8 386 383.8 284 2'4.1 472 2'4.7 247 Grain Drill 1a) 2’4.3 112 2’4.3 112 4.9 131 6.1 185 Ron Planter 2’6 114 12 114 6 384 6 384 Furroaer iron) 386 272 12 386 2'6 488 2'6 348 Sprayer iron) 12 125 24 63 12 167 12 167 Ron-Cultivator iron) 3'6 184 2'12 138 2’6 184 2’6 254 Cost ilha lachinery 21.64 17.57 29.18 24.99 Fuel 8.61 5.48 11.64 7.78 Labor 1.74 8.79 1.76 1.13 liaeliness 8.86 8.86 7.69 7.69 lotai 48.86 31.89 58.19 41.57 138 reduced tillage, with a 17! decrease in total cost per hectare as compared with conventional tillage. The examples presented in this section show one of the applications of the model for real world situations. The reduced tillage systems for five rotations were formulated based on results of 30 field experiments on tillage systems for the crop sequence "-8 carried out at the Agricultural Experiment Station of The Yaqui Valley. No statistically significant difference for wheat and soybean yields were found for conventional, conservation and minimum tillage systems (Moreno, Ortega and Samayoa, 1984). The model will be a powerful tool to analyze economic advantages of new improved tililage systems in the Yaqui Valley. The model has the potential capacity to handle new crop rotations and/or crop sequences that agronomists may want to introduce in the region. 7.2. CUSTOM HIRED OPERATIONS 7.2.1. Owned vs. Custom Hired Operations The computer model will allow an option of either the use of owned or custom hired machines for each field operation. Various options or combinations (mixtures) of custom hired and owned machines were compared. Examples for 300 and 600 hectares of H—S-C with conventional tillage on clay soil are shown in Tables 7.4 and 7.5. Full interest or payments on purchases of machinery were assumed for these computer model runs. 139 Three cases or mixtures of custom hired operations were compared for a wheat-soybean-cotton rotation. In the first case the cotton picker was custom hired; in the second case the cottton picker and the combine for soybean harvest were custom hired. The third case considered custom hiring cotton pickers, combines for soybean harvest, and tillage and seeding equipment. Custom hiring the cotton picker and combine resulted in the lowest machinery set cost for 300 and 600 hectare eJldos, as compared with no*custom hiring. Custom hiring the cotton picker was lower cost per hectare than nofcustom hiring. Custom hiring the cotton picker, combine, along with tillage and planting equipment resulted in a lower cost per hectare than owning the machines and a lower cost than custom hiring the cotton picker alone. For 300 hectares of H-S-C rotation, custom hiring the cotton picker alone reduced total cost by 21.51 as compared with owning the machine. Custom hiring the cotton pickers and the combine for soybean harvest, further reduced the total cost, with a 311 reduction compared with owning the machines (Table 7.4). For 600 hectares of H—S-C rotation, owning all the machinery was compared with: a) Custom hiring the cotton pickers, b) Custom hiring cotton pickers and combines for soybean harvest, and c) Custom hiring cotton pickers, combines and tillage equipment. Results of these comparisons are shown in Table 7.5. 140 Table 7.4. Custom Hired Operations vs. No-Custom Hire, for 300 Ha of Hheat-Soybean-Cotton. Thousand of Mex slha. Type of Cost No Custom Custom Hired Operations Work Cotton Picker C. Picker & Combing Machinery 32.44 19.22 16.02 Fuel 12.15 9.67 9.20 Labor 1.97 1.67 1.69 Timeliness 6.01 5.37 0.00 Custom Hork 0.00 5.35 9.39 Total 52.57 41.28 36.30 Table 7.5. Custom Hired Operations vs. No-Custom Hire, for 600 Ha of Hheat-Soybean-Cotton. Type of No Cotton C. Picker C. Picker, Hork Custom Picker & Combine Combine Hire Tillage Equipm‘ Machinery 29.26 19.00 15.22 13.39 Fuel 11.64 9.91 9.33 7.46 Labor 1.76 1.76 1.68 1.42 Timeliness 7.69 5.37 0.00 0.00 Custom Work 0.00 5.35 9.39 14.90 Total 50.35 41.39 8835.62 37.17 ‘ Tillage Equipment Custom Hired: Disk Plow, Offset and Disk Harrow, and Land Plane. 141 Custom hiring the cotton picker brought a total cost reduction of 14.31 $/ha (machinery , fuel,pius timeliness), while custom work amounted 5.35 $lha. Therefore there was a net total cost reduction of 8.96 slha, which is a 17.8! cost reduction from the cost with no custom hiring. Custom hiring cotton pickers and combines resulted in further reduction in total cost per hectare, as compared with custom hiring cotton pickers only. Machinery, fuel, labor and timeliness decreased by a total of 9.7 slha, while custom cost increased by 4.04 slha. Compared with no-custom hiring, this option had a 29! decrease in total cost per hectare. Custom hiring tillage equipment, along with cotton pickers and combines resulted in decrease of 3.98 slha machinery, fuel and labor, but custom cost increased by 5.51 $/ha. Therefore the total cost of this mixture increased as compared with custom hiring cotton pickers and combines. 7.2.2. Custom Hired vs. Owned with Negative Interest Rates The particular situation of the eJldos, with subsidized loans for purchasing machinery (Section 4.7.2.) was compared with custom hiring. Table 7.6 shows computer model example runs, with negative interest rates (interest rates lower than inflation), for 300 and 600 hectares of H-S-C rotation, with conventional tillage, clay soil, at 0.8 probability level. The machinery cost component of total cost per hectare decreased with lower (negative) rates. The total cost of the machinery set selected with a -203 of 142 interest rates decreased by 31.5! for 300 hectares of H-S-C, and by 27.41 for 600 hectares of H-S-C, as compared with the cost with a 1! interest rates. The total cost with a -402 of interest rate decreased by 56! for 300 hectares and by 453 for 600 hectares of H-S-C, as compared with a 11 interest rates. Cost reductions in total cost per hectare, due to lower interest rates, will affect custom hiring decisions. Table 7.7. shows comparisons of three custom hire options versus no custom at 11, and two negative interest rates. Price of custom hired operation were assumed to be the same for all options compared. Hhen the ejidos paid full prices (11 interest), the three custom-hired options had lower cost per hectare than no*custom hiring (i.e. eJido owned and operated equipment). At a -202 of interest rate the cost owned machinery decreased for all options, but the differences between the three custom hire options and no*custom hired were much smaller than there were for 1! interest. At a -401 lnterst rate for loans for machinery purchased the cost of owning all machinery decreased to 27,680 Mex slha. Since custom hired price did not change, owning the machines in this case was a lower cost option than custom hiring cotton pickers, combines and tillage equipment. Custom hiring cotton pickers was the same as owning the machines. Custom hiring cotton pickers and 143 Table 7.6. Cost of Machinery Sets Hith ‘ Negative Interest Rates in Thousand Mexican 8/Ha. 300 Hg, H-S-Q 600 Ha, N—S-C Type of Interest Rate, 1 Interest Rate, 1 1 -20 -40 1 —20 ~40 Machinery 32.44 19.83 7.05 29.26 16.92 8.04 Fuel 12.15 11.92 12.00 11.64 11.52 11.68 Labor 1.97 1.45 1.19 1.76 1.48 1.34 Timeliness 6.01 2.82 2.82 7.69 6.62 6.62 Total 52.57 36.02 23.06 50.35 36.54 27.68 Table 7.7. Comparisions of Custom Hired Mixtures at Three Interest Rates. Thousand of Mexican $lha. Interest Rates Percent Machines Custom Hired 1 -20 -40 No Custom Hire 50.35 36.54 27.68 Cotton Picker 41.39 32.99 27.20 C. Picker and 35.62 29.91 25.18 Combine C. Picker, Combine 37.17 33.85 30.52 ’and Tillage Equipm1 1 Tillage equipment custom hired: Disk plow, offset and disk harrow, and land plane. 144 combines was still a lower cost Option than no custom hiring the machines. Because the real cost of machinery for collective eJidos was much loss due to negative interest rates, a number of implications follow that will influence machinery decisions in the following directions: a) Encourage greater purchases of machinery, b) Increase the rate of machinery replacement to save on repair costs, and c) Less custom hiring would be cost effective. The examples for custom hiring versus no custom hiring show the capacity of the machinery selection model to analyze the effects of government policies that could affect machinery purchases, such as interest and inflation rates, and price of machinery and custom hired services. These comparisons will help ejidos, farmers, private and goverment custom hired enterprises, and machinery dealers to provide guidance for machinery management decisions. The computer model is intended to be used for teaching and training at the Agricultural Machinery Deparment of the University of Chaplngo. Its use for technical assistance for farmers and eJidos could be a potential application in the near future. - ml .41.- CHAPTER 8 CONCLUSIONS 8.1. CONCLUSIONS Training and technical assistance needs in agricultural mechanization aspects were indicated by 80! of 15 groups of eJidatarios and technicians interviewed. Research needs were pointed out by 93: of the groups interviewed. Agricultural machinery management and repair were the most important and urgent topics emphasized by the eJidos. The machinery selection model, MACHSEL, was adapted to the simulation of agricultural machinery operating conditions in the collective eJidos in the Yaqui Valley. The model was sensitive to changes in maJor parameters when using data from the Yaqui Valley. The model selected larger machinery sets at 0.8 probability level; machinery sets selected at 0.7 and 0.5 levels were similar in most cases. The model was sensitive to changes in area seeded. For “-8 rotation, conventional tillage at 0.8 probability level, there was a cost reduction of 8.41 from 150 to 600 He for clay soil. For loam soil there was a reduction of 8!. For reduced tillage on clay soil, the total cost decreased by 11.83 from 150 to 600 hectares, and 13.82 from 150 to 1200 hectares. 145 146 Crop rotations including cotton required more machinery and had higher cost per hectare. Rotation wheat-soybean-cotton was the most expensive of 5 rotations studied, with a total cost per hectare of 52,570 Mexican pesos (1985) for 300 hectares of area seeded. This cost was 251 higher than the cost for the wheat-soybean rotation, and 16.7! higher than H-H-S-C rotation. The model was sensitive to changes in soil type changes. Cost reductions up to 211 were obtained for machinery selected for loam soil as compared with clay soil, for a wheat-soybean rotation. The eJldos own more machinery than indicated as optimum for least cost at 0.8 probability level. Cost reductions could be realized by using fewer machines of a larger size, and reducing the number of passes of tillage operations. Machinery sets selected for reduced tillage required less tractor power and smaller or less hours of use of tillage equipment, as compared with conventional tillage. Machinery and fuel cost decreased, with total cost per hectare savings of up to 21.4! for 300 hectares of a "-8 rotation, and up to 18.21 for 600 hectare of a H-S-C rotation. The empirical data showed that it is likely that certain types of machinery; such as, cotton pickers and combines, are appropriate on a hire on custom basis. If the eJidos had to pay full prices (without subsidized 147 credit) for their machinery, savings of up to 311 could be obtained through custom hiring the cotton pickers and combines. Hhen the real cost of machines decline due to negative interest rates (interest rate lower than general inflation) for subsidized credit loans, less custom hiring is Justified. For example at a -401 interest rate owning cotton pickers and tillage equipment will be a less cost by option than custom hiring of machines. The computer model MACHSEL appears to be applicable to Mexico for teaching, and technical assistance related to machinery management. The collective eJidos of the Yaqui Valley could benefit from the model simulation studies to optimize their machinery sets for lower costs. 8.2. RECOMMENDATIONS FOR FURTHER RESEARCH To expand the model to include other crops and rotations in the Yaqui Valley. To adapt the model so that units of machines could be easily added or substracted from actual sets, to use the model for machine purchase or discharge decisions. To initiate studies to keep records on machinery management data in eJidos and private farms in the Yaqui Valley. 148 To carry out more field experiments with reduced tillage operations, for main crops in the Yaqui Valley and to experiment with larger machinery sizes. To perform measurements on field efficiency and draft power requirements for crop production equipment in different locations of the Yaqui Valley. To study agricultural machinery management strategies for private farms and ejidos. To keep records of suitable days for machinery operations and to analyze weather data for different locations in the Valley, and to define timeliness factors for field operations. To study the probability of losses beyond the 0.8, 0.7 or 0.5 levels. In other words what losses can be expected the other 2, 3 or 5 years out of ten. APPENDIX A AGRICULTURAL MECHANIZATION NEEDS ON COLLECTIVE EJIDO FARMS IN THE YAOUI VALLEY, SONORA, MEXICO. 199 ANSHERS TO GROUP INTERVIEH. MAY 1986 Training Needs. 1. On Do you think the eJidatarios need training on aspects of agricultural mechanization? YES: 12 NO:3 Hhen answer was no, why do you say they don't need training? - eJidatarios don't have time to attend courses .......1 - eJidatarios know all they need about machinery ......1 - courses are the same; there is nothing to learn .....1 If answer was yes, why do they need training? -they have few knowledge on machinery ................7 -if they are more trained they will dot better their work .................................................7 -to improve their social level .......................3 -the eJldo have few trained persons in machinery ......7 -to do other works needed by the eJldo .......... ..... .4 Sept. 84 and Aug. 85 there were training courses on agricultural machinery for eJidatarios. 4- Did the eJido receive a notice about these courses? -yes, of both of them ...............................3 -yes, of the first one .... ....... ............. ..... ..1 -yes, of the second one ...............................1 -yes, but they are not sure of which one, or both......2 -no notice of both courses .. ..... .....................2 -m.t kn“, "Ot 88.". eemmmmamaamaiemmemmmmm mmmmmmmmm m1 150 Total number of eJidatarios selected to attend those courses. 2,(2&1).0,0,1,1,0,1,1,3 In the case that they received notice, but did not select a person to attend the couses, what was the reason(s)? -It was discussed on the assembly, but there were no persons interested. .. ......... . ..... ........ ......... 1 -They teach the same ..................................1 On the eJido the selection to attend couses is on the assembly? YES: 13 NO: 2 If there are training courses on agricultural machinery the eJido pay transportation & allowances? YES:14 N030 Hhen somebody is selected to attend a course, do the eJido set up some conditions ( to teach other eJidatarios, to apply what he learned on the eJido, to report about the courses)? YES:12 NO:1 10. Hhat has the eJido done to promote training on agricultural machinery? - to ask for courses to the Coalition? YES:1 NO:13 - to ask for courses to agricultural machinery dealers? YES:3 NO:11 - to ask for courses to technicians of Coalition? 151 YES:1 NO=13 - they have established a fund for training expenses? YE330 N0313 - they have regulations for training? YES:1 NO:13 Technical Assistance Needs 1. Do you think the eJido needs more technical assistance on agricultural machinery? YES:12 NO:2 2. If answer was YES, in what subJect does the eJido need technical assistance? YES NO - repair of agricultural machinery 13 - - use of machinery shop equipment 11 2 - machinery maintenance 9 4 - planters and sprayers calibration 5 8 — studies on how is the eJido using the machinery 10 3 - to keep record of expenses on agricultural machinery - 10 3 - to calculate operating costs of agricultural machinery 10 3 — to select the tractors most convinient for the eJldo 7 6 - others - agricultural mechanics & welding 1 152 - quality of agricultural equipment materials 1 - weight of implements in relation to their work 1 Agricultural Mechanization Research Needs 1. How important is for the ejidos that universities such as Chaplngo, or agricultural experiment stations carry out research or studies on agricultural machinery in the Yaqui Valley? Very important ........11 Important..... ......... 3 Little important ...... 1 Not important ......... 0 For what reason is very important? a) The eJidatarios stay watching for research results.(9) b) The technicians of Coalition stay watching for research results.(8) c) Little is known on how the machinery is being used in the eJldo. (6) d) they would like to know which equipment or new methods would be better for the ejido. (11) e) the University use the results for teaching. (1) For which reason it is of little or no importance? a) Even with research, the eJidatarios will continue doing the same. (1) thch is the degree of importance, priority and urgency of the following topic for research or studies? See Table A-1. 153 lable 8-1 leportance, Priority and Urgency of Agricultural lechaaization leads on Collective Ejldos of the Yaqui Valley, Sonora, Heaico. laportance' Priority Urgencyu lopics 1 2 3 4 1 2 3 4 5 6 7 1 2 3 4 Iachiaery Deaing 8 3 4 8 2 1 - 1 1 2 7 4 6 4 1 lachinery Repair 18 3 1 1 1 4 2 2 3 1 1 8 6 - - Agricultural Hachinery Shop 18 1 3 8 2 1 4 2 3 - l 9 3 2 - agricultural Hachinery Ianagaent 9 4 2 8 4 2 2 1 2 2 1 18 3 - - Calibration of Equipaeat 18 1 3 1 1 3 3 2 1 3 - 8 3 2 1 Agricultural Inchinery Cost 11 2 1 1 3 1 2 4 1 1 1 9 3 1 1 liiiage 8 ‘4 2 1 1 3 - 1 2 3 3 9 l 3 1 Iaintenance 1 1 1 lasting of Equip-ant 1 1 i lDlaLS 68 18 16 4 14 16 13 13 13 13 14 58 26 12 4 8 laportance: 1.- very iaportant; 2.-iaportant; 3.- little iaportant; 4.- not iaportaat '8 Urgency: 1.- very urgent; 2.- urgent; 3.- little urgent; 4.- not urgent APPENDIX 8 LIST OF AGRICULTURAL MACHINERY AVAILABLE AND PRICES 154 W Make and Rated List Price Mex.$/H.P. M1 H-P- M49319 x 10.9.0. SIDENA 310-3 31 1,437 46.36 FORD 6600 77.1 3,310 42.9 FORD TW-25 (I) 160 9,850 61.56 FORD TW-35 (I) 190 10,800 56.8 MF 285 72 3,401 47.24 MF 290 80 3,913 48.9 J.DEERE 2735 82 3,743 45.65 J.DEERE 4255 120 7,110 59.25 J.DEERE 4650 (I) 185 13,558 73.28 STEIGER PUMA CM-165 (I) 167 12,500 74.85 Wfi Make and Model Width Rated List Price EL, H.P. _§£x 3 x 1&QQ_ J. DEERE 7720 4.8 145 19,123 A CHALMERS L-3 4.8 143 W J. DEERE 9910 2-ROW 114 19,189 155 SU§§OILER Mdce md Model Shanks Description List Price a Mex x 1000 Conota 3 Mounted 387 J. Deere MX50 3 Mounted 7561 J. Deere MX50 5 Mounted 10171 Ochoa 2 Mounted 200 Ochoa 3 Mounted 239 Vazquez STR-2 2 rect Mounted 234* Vazquez STR-3 3 rect Mounted 308* Vazquez SBR-2 2 curved Mounted 273 Vazquez SBR-3 3 curved Mounted 335* Vazquez SBR-4 4 curved Mounted 423* Vazquez ZM-4 4 heavy Mounted 559 Vazquez ZM-5 5 heavy Mounted 677 DISK PLOW Make and Model Disks Description List Price Mex 9 x 1000 FTA 51-3 3 Mounted rev. 566* FTA 51-4 4 Mounted rev. 671 IAMEX 3 Mounted rev. 998‘ J. Deere 3631 3 Mounted rev. 467 J. Deere 3745 4 Mounted rev. hidr. 816* J. Deere 3755 5 Mounted rev. hidr. 975 Kimball 5 Mounted rev. 1156 Sidena 2 Mounted rev. 285 lPrlce of May 86 * Most sold models for a given make. 156 OFFSET DISK HARROWS Make and Models Disks Width Description List Price Meters Mex $x1000 Durable MAT-1824 18 -- Trailed, whi. 793 Durable MAT-2024 20 -- Trailed, whi. 890 Durable MAT-3224 32 -- Trailed, whi. 1,360 ICP-14TL 14 -- Mounted 275 J. Deere Mx225 20 2.28 Trailed, whi. 838 J. Deere MX425 32 3.66 Trailed, whi. 1,204 Sidena 2-28TL 28 -- Mounted 1,140 Vazquez RDHT-20 20 2.3 Trailed, whi. 953 Vazquez RDHT-28 28 3.2 Trailed, whi. 1,396 Vazquez RDHT-32 32 3.7 Trailed, whi. 1,462 Vazquez RDHT-28 28 3.2 ----------- 1,492 Vazquez RDHT-32 32 3.7 ----------- 1,571 Vazquez RJ-20 20 2.3 Trailed, whi. 788 Vazquez RJ-28 28 3.2 ----------- 1,045 Vazquez RJ-32 32 3.7 Trailed, whi. 1,152 PLANE Make and>Model Size(feet) Description List Price Mex $x1000 Ochoa 45x10 Wheels, rem. ctri. 2,387 Ochoa 45x12 Wheels, rem. ctri. 2,404 Vazquez NR 45x10 Wheels, rem. ctri. 2,434 Vazquez NR 45x12 Wheels, rem. ctri. 2,461 Vazquez NR 35x12 Wheels, rem. ctri. 2,169 157 WOOD FRAME Me and Model Size Description List Price Mex $x1000 No mark 20x10 Trailed 180 SHOVELS Make and models Size Description List Price meters Mex $x1000 CT-310M 1.8 Mounted 151 EN-31 M 1 .8 Mounted 150 FTA-71-11 2.1 Mounted 210 Ochoa 2.1 Mounted 3501 Vazquez PT 2.1 Mounted 253** Kimball 2.4 Trailed, wheels 290 Kimball 3.0 Trailed, wheels 439 Kimball 3.6 Trailed, wheels 525 Vazquez ENH 2.4 Trailed, wheels 407 Vazquez ENH 3.0 Trailed, wheels 537* Vazquez ENH 3.6 Trailed, wheels 636* Vazquez ENH 4.2 Trailed, wheels 777 1 Price of May 86 *Most sold models for a given mark 158 21.19153. Malta md Models Size Description List Price Meters Mex $x1000 Ochoa 1.8 Medium, Mounted 125 Ochoa 1.8 Heavy 167 Pronansa 1.8 Mediue, Mounted 190 Vazquez TA-2 1.8 Medium, Mounted 140 Vazquez TA—1 2.15 Big, Mounted 230 FURROHER Make and Models Size Description List Price Mex $x1000 Vazquez EZ-4 2.8m Mounted 254 DISK BEDDER Make and Models Size Description List Price Mex $x1000 Ochoa Medium 6 disk, Mounted 225 Ochoa Heavy 8 disk, Mounted 855 Pronansa Light --------------- 321 Vazquez, BTP-3 ----- (contour) Mounted 191 Vazquez, BTP-1 ----- (wheat) Mounted 412 Vazquez, BCTL ----- ditcher, Mounted 328 Vazquez, BCTL ----- ditcher, Mounted 626 Vazquez, BATP ----- rice, Mounted 743 159 CQLTIPACKER Me and Models ' Size Description List Price Meters Mex $x1000 Universal 3.6 e Trailed 321 Vazquez 3.6 m Mounted 428 RON CULTIVATORS Make and Models Size Description List Price Meters Mex $x1000 Ochoa 1 3 shank s Mounted 287 Ochoa 4 rows Mounted 360 Promansa 9 shanks Mounted 271 Proeansa 4 rows Mounted 394 Vazquez C 00-11 2 rows Mounted 230 Vazquez 21 4 rows Mounted 444 Vazquez CB-4 4 rows Mounted 283 Vazquez ODD-2 4 rows Mounted 354 Vazquez 1 4 rows Mounted 385 FERTILIZER SPREQQER Make and Models Size Description List Price Mex $x1000 Iaesa F—300 300kg PTO, Mounted 195 Iansa C-450 --- ------ 2951 leesa F-600 600kg ------ 224 Long HOPC-400 400kg ------ 205 Vazquez IVSA-400 400kg ------ 207 160 W Make and Models Size Description List Price meters Mex $x1000 Fiona (Denmark) 3.0m ------ 1,350 J. Deere 8200 (USA) 3.7m ------ 1.669 RON CROP PLQNTER Make and Models Size Description List Price Mex $x1000 Iamex 4 rows Mounted 815 J, Deere»MP-25 4 rows Mounted 693 SPRAYERS Make and Models Size Description List Price Mex $x1000 AsperJet 400 it. 17 nozzles, Mounted 385 Aspermex 500 it 17 nozzles, Mounted 550‘ Iamsa 500 it 17 nozzles, Mounted 550 Robin 500 it 17 nozzles, Mounted 218 d. Deere 6000(USA) ----- self propelled 19,4181 §1§LK CUTTER Make and Models Size Description List Price Meters Mex $x1000 Iamsa 1.8 Mounted 287 Usel 1.8 Mounted 6701 Vazquez DR—72 1.8 fuse, mounted 357 Vazquez DR-72 1.8 clutch, mounted 429 1 Price of May 86. APPENDIX C MACHINERY SELECTION MODEL USER'S GUIDE 161 MACHINERY SELECTION MODEL USER'S GUIDE 1. Introduction The machinery selection model (MACHSEL) is a computer program created by Rotz and Muhtar (1982)1, for the selection of the 'best' set of machines for producing a set of crops in a given farm. The original version was [for interactive or batch use on a main frame computer. A new microcomputer version was created in March 1986. The program is compiled in Laheya, F77L, version of Fortran. 2. Description of MACHSEL and Associated Files. The computer model combines capacity and power matching, with cost analysis methods for the seiectlon of farm machinery. The diagram of the computer algorithm is shown in Figure 1. Data required by the model are stored in three input files. One file contain machinery data and suitable hours for field work, for conventional and reduced tillage. The other four flies contain operation sequences for two tillage methods and 5 crop rotations. 1 C. Alan Rotz, H.A. Muhtar, J.R.Biack. 1983. A Multiple Crop Machinery Selection Model. Trans.ASAE. 26(6): pp. 1644-1649. 2 Fortran 77 Language System for the Personal Computer. Reference Manual. Lahey Computer Systems, Inc. n/d. 162 D! it nmmc museum COMPATIBLE S! r i mcuuum 10 mu ““0”" “l 0"“"0M mcncmm 10 MM p.‘ : LARGER Atltnwnwt m ‘A'G‘R "LLAGI g" ACCOflOiNG TO PRIORITY ii "0* TOUIFMINT as 1 N0 “.6" TitlAG! no at“! IILLAGE sizes touamtm avuuou ‘ i0 museum ’ vu uncut cucuun 10!“ cost or WCM'rizi '"0 Ni" J must tommtm mcumtav nus "mums: nesu "‘00" ‘ tommmum mtumtmnt oumn uumun or uneven: "on menus: us was: us: on an: use AND cost Low“ (20:! 7 ’ mcnuse nuuun Of no macvons nous Autummvu m mm "s 1 I OUIWENI AVAILAIL E 'iNAL OUIPUI An output file with detailed results is created during execution of the program, and can be displayed on the screen Q or sent to a printer. 3.‘ How to Use MACHSEL 3.1. Requirements To run MACHSEL you need a microcomputer with at least 512 K bytes of memory,a math-coprocessor and a high density floppy disk drive or a fixed disk. 163 The compiled program MACHSEL and the associated files are stored on a high density floppy disk. 3.2. Running MACHSEL Remove the DOS diskette (system disk) from paper envelope on right side of disk drives. Insert DOS diskette in drive A (upper drive), and close the drive door. Switch on the printer and the computer. Halt a moment while the system checks itself out. Hhen DOS is ready, the symbol A) will be displayed on the screen. Hhen the red light on drive A goes off, remove system disk from its drive. Insert disk with MACHSEL in drive A. NOTE: The program will not run in drive 8, because it is not a high density drive. Before running MACHSEL, decide if you want to obtain output from the printer or Just want to watch the screen. If you want to print, continue to step 8; otherwise go to step 9. To obtain output from the printer, align the paper and press simultaneously the two keys: [Ctrl] [PrtScJ NOTE: Hit the keys shortly and quickly, since pressing a key for a longer time than necessary is 10. 11. 12. 13. 14. 15. 16. 164 like a repeated command (and the previous command will be cancelled). If after step 9 the printer is not printing, hit the two keys again. To run the program, type MACHSEL or machsel after the symbol A), and press the ENTER key, like this: A)machsel [ENTER] After 10 to 15 seconds the computer will display a title, and begin asking for input information. For a first try, use the same input information as in the example run that follows. Otherwise, use your own data. For each Question, select one of the options displayed on the screen. ngg_t e correggggding code number, and ggegs the ENTER key, Halt while the program executes (about two minutes). A summary of results will be displayed on the screen when the run is completed. Hhen you see the symbol A) on the screen, you may decide to examine file ”output”, which was created during execution of MACHSEL. Section 3.4 will explain how to examine this file. To make another run of MACHSEL, without changing the printing mode, go to step 9. Ohtherwise, if you want to change printing mode, return to to step 7. To finish the session, wait until the symbol A) is on the screen, and the red llgth on drive A is off. Then remove disk with MACHSEL. 165 3.3. Example Run An example .run using metric units will be u4 22 demonstrate the operation of MACHSEL. The eJldo is located in the Yaqui Valley and has 600 hectares of clay soil, and uses conventional tillage for a wheat—soybean rotation. A>machsel MACHSEL: A Farm Machinery Selection Model Michigan State University Version 2.0 Which type of units do you prefer to use? 1 English units 2 SI (metric) units 2 What is your farm area in hectares? 600 What is the predominate soil type? 1 Sandy (light soil) 2 Loam (medium soil) 3 Clay (heavy soil) 3 Which type of tillage do you wish to use? 1 Conventional 2 Conservation 3 Ridge tillage 4 No-till 1 What is your location and confidence level? 1 YAQUI VALLEY 80% '- 2 YAQUI VALLEY, 70% 3 YAQUI VALLEY, 50: 1 . Which crop rotation do you wish to use? WHEAT-SOYBEAN WHEAT-SOYBEAN-COTTON WHEAT-WHEAT WHEAT-WHEAT-SOYBEAN WHEAT-WHEAT-SOYBEAN-COTTON 01$de 166 The program will divide the total farm area into equal size parcels, one for each crop in the rotation. After receiving the rotation number, the model will display on the screen the list of operations for each parcel, indicating starting and ending dates (See printout below). These operations are automatically selected when we choose tillage system and rotation. To modify sequences and dates in input files refer to section 4.3. A message is displayed to indicate that you must wait while the program executes. FIELD OPERATIONS Parcel 1: 300. Hectares of Wheat following Soybeans Combine Sept. 17 to Oct. 15 Disk plow Oct. 1 to Oct. 22 Offset harrow Oct. 15 to Nov. 12 Offset harrow Oct. 15 to Nov. 12 Land plane Nov. 5 to Nov. 19 Fertilizer spreader Nov. 19 to Dec. 3 Disk harrow Nov. 19 to Dec. 3 Wood frame Nov. 26 to Dec. 10 Grain drill Nov. 26 to Dec. 17 Furrower Nov. 26 to Dec. 17 Sprayer Jan. 8 to Jan. 29 Parcel 2: 300. Hectares of Soybeans following Wheat Combine April 16 to May 7 Offset harrow April 16 to April 30 Wood frame April 23 to May 7 Fertilizer spreader April 30 to May 14 Disk harrow April 30 to May 14 Furrower April 30 to May 28 Furrower April 30 to May 28 Row planter May 14 to June 4 Row cultivator June 11 to July 9 Row cultivator June 11 to July 9 Furrower July 9 to July 23 The program will take about 2 minutes to execute. A summary of results will be displayed, showing the best machinery set (least cost system), and a cost summary for the selected system of machinery. See printout on next page. 167 mum SELECTED: Least cost systu of machines thich can cwlete all notations within the given time constraints. Mmdflne Eflze Nutmr the Cost Fueiume (h) (0) (Liters) Primm'y tractor 119.3 kw 3 $4.9 1952. 11407. Utility tractor 57.3 kw 2 574.2 1426. 8921. Cdine 8.0 row 2 163.0 3742. 5866. Fwtiiizer spreads‘ 12.2 meter 1 87.3 67. Land plane 4.3 meter 2 72.8 243. Disk plow 6.0 dis: 3 105.1 183. Disc W 4.7 meter 1 2%.2 261. Offset lac-row 4.1 mete~ 2 212.3 232. Wood fr-Ie 3.7 mutt 2 159.2 28. Grain (rill 4.9 mstr 1 98.0 £4. Row platter 8.0 row 1 $.5 207. Firrower 8.0 row 1 315.7 187. Sprayer 16.0 row 1 47.0 67. Row cultivator 8.0 row 1 206.5 154. iIEfl'SUHUWN: (O) (OVHmfiure) Phchhury flNEHLOB :fl.72 Fuel 5135.47 8.56 Labor 847.82 1.41 Timeliness 5153.67 8.59 Gmflmmierk (L00 (L00 Total 24“!»04 ‘NLZB This completes the explanation of the example run. Now you may continue to section 3.4 on how to examine file finish your "output". For another run of MACHSEL, or to working session, return to step 15 or 16 of section 3.2. Be aware that the previous file ”output” will be erased, and a file be created for each run. Therefore, new file .will ”output” will always contain results of your last run. 168 3.4. Detailed Results in File "Output" File ”output" contains the information already received, plus two tables: one showing the machinery systems that can complete all operations with the given time constrains: the other table presents the machine schedule for field operations (See pages 179-182). The interpretation of results is very straight forward. Cost figures are in Slyear, since the system is optimized for a ten-year period, and the annual equivalent cost is calculated. The machine schedule table shows the hectares or acres completed during each week, for all operations on every parcel. The zeros mean no operations in those weeks. Three options to examine file ”output” are explained next: a) displaying the file on the screen, without printing, b) printing the file, and c) storing files of various runs for later examination. 3.4.1. Display File ”Output” on the Screen To display the contents of the file "output" on the screen, you may use the following steps 1. If the printer is still printing since you pressed the [Ctri] [PrtSc] keys at the beggining of this session, press these keys again to cancel printing. You may also turn the printer off, with same result. 2. To examine the file while it is displaying, you can stop the screen, pressing the keys [Ctri] [S] at the same time. To start the screen, press the keys 169 [Ctri] [0] simultaneously . You may also keep the [Ctrl] key continousiy pressed, while pressing keys [S] and [O] alternatively. 3. To display file "output” on the screen use the command: A)type output [ENTER] Since the tables have about 120 characters per line, the lines on the screen will be wrapped. Therefore, for each line of the tables the screen will show two lines: the first 80 characters on one line, and the rest on a second line. The same will occur when you print file "output”. 3.4.2. Printing File Output As pointed above, file ”output” contains two tables with more than 80 characters per line. To print this file you may use a printer with a wider carriage, or program the printer for compressed printing. For compressed printing, press the ONLINE, FF and LF keybuttons of the printer in the following fashion: ONLINE and FF together You will hear a beep, and the light to the right of the ONLINE key will start flashing. ONLINE A beep will be heard FF LF ONLINE Light will stop flashing 170 The printer will stay in the compressed mode until you turn the printer off. You may also cancel the printing mode by pressing the sequence of keybuttons again. To send file "output" to the printer, type the following after the symbol A): A)copy output ipti CENTER] The printing obtained will be continous, with no top or bottom margins. The size of file “output" will vary, depending on the number of parcels, number of machinery systems that can complete all operations during optimization, and the number of machines selected. To format the printed output to show each table in a different page, you may print file "output“ using a word processing program. Appendix B shows the same file, printed by pages, using Volkswrlter. Similar results can be obtained using other word processing programs. 3.4.3. Storing ”Output" Files for Later Examination If you do not want to display or print output files immediately, you may store the files created after each run, for later examination. In that case, you need to copy the output files to a second disk. The following steps may be used: 1. Insert a second disk (two sides/double density) in drive 8. 171 2. Type the command: A)copy output b: filespec where: filespec= name you want for output files to be stored for later use. 4. Input Files Two types of data files are required during MACHSEL execution. A machinery file contains machinery and economic parameters, and suitable days for field operations. The other file contains operation sequences, with beginning and ending dates, and a code to indicate hired or owned machinery. These files can be modified to suit specific conditions of a farm, or to evaluate new tillage options. The procedure to set up or change these files is explained in section 4.3. 4.1. Machinery Data Files The version of the model for the Yaqui Valley has one file: CONTIL, with data for conventional and reduced tillage (See page 183). 4.1.1. Machinery garageters Data for tractors is on the first line of the files. The five values represent cost per horsepower, repair cost factors R01 and RC2, and remaining value factors RV1 and 172 RV2. The next 20 lines show parameter values for 20 equipment and/or operations that the model handles. Table 4.1 shows the list of parameters. 4.1.2. Economic ngameters. The line after the last machine contains economic parameters required by the model. The list of these parameters is depicted in Table 4.2. 4.1.3. Suitable Hours for Field Qgerations. The current files have been set up for the Yaqui Valley. There are three six-row blocks of values, containing suitable hours at three confidence levels: 801, 701 and 501. For each block, the first two lines correspond to sandy soils, which are not used in the model. Lines 3 and 4 correspond to loam soil, and lines 5 and 6 to clay soil. 4.2. Crop Rotation Files Crop rotation files contain operation sequences and calendar dates within which an operation should be completed. Two tillage systems for 5 crop rotations are the current options for the user. The file names are: CONVEN for conventional tillage system CONSER, for reduced tillage system To describe the content of a rotation file, let's examine file CONVEN (See pages 184-188). The first 5 lines have rotation code numbers and Table 4.1. 173 List of Machinery Paramenters 'in Data Files. Col Parameter O‘D‘iO 0| -LUJN-‘ j 11 12 13 14 15 16 Operating speed in miles per hour Field efficiency for farms under 400 acres Field efficiency for farms over 400 acres Type of tractor (1=tiilage, 2=utllity, 0=no tractor) Maximum implement width in feet Columns 6-9, draft values in HP/ft Intercept Slope for sandy soil Slope for loam soil Slope for clay soil Columns 10 and 11, purchase price of equipment Intercept Cost 0/foot (slope) Repair cost factor, RCi Repair cost factor, RC2 Remaining value factor, RV1 Remaining value factor, RV2 Custom hire rate, Siacre Table 4.2. List of Economic Parameters in Machinery Data Files Column Parameter dialiO‘QO‘G-AUJN-* «ii Fuel cost, Sliiter Wage rate, Slhour Tax, insurance and shelter rate Income tax bracket, expresed as a fraction Discount rate Machinery inflation rate Fuel inflation rate Wage inflation rate Interest rate Downpayment, as a fraction of initial cost Number of years for financing the machine 174 rotation names. This is the list displayed on the screen to prompt the user for a rotation selection. The zeros after rotation 5 signal the end of rotation options. Information for 5 rotations follows. The program will use the data for the rotation specified by the user. As an example, let's examine the data for the first rotation, wheat-soybean. The lines for this rotation represent the following: 1 WHEAT-SOYBEANS Head or name of rotation 2 Number of parcels 5 3 Code numbers for harvested crop and planted crop NOTE: Code crop numbers are: 3=wheat, 5 = soybeans, 7=cotton. 1 38 41 2<- Own or custom hired machinery 9 40 42 2 (1=hire, 2=own) 16 2 4 2 T “I Week to and machine operation Operation code Week to begin machine operation The code numbers for the Operations handled by MACHSEL are shown in Table 4.3. Three zeros indicate end of a rotation. The file continues in that fashion for 5 rotations. 175 Table 4.3. Machinery Codes in Rotation Files Code Type of Machine 1 Combine 2 Cotton Picker 3 Self Prop Sprayer 4 Stalk Cutter 5 Cultipacker 6 Subsoiler 7 Fertilizer Spreader 8 Land Plane 9 Disk Plow 10 Disk Harrow 11 Offset Harrow 12 Wood Frame 13 Grain Drill 14 Row Planter 15 Furrower 16 Sprayer 17 Row Cultivator 18 Furrower 19 Offset Harrow 20 Row Cultivator Four zeros indicate end of operations list for the parcel. 4.3. Modifications of Input Files To modify the input files, the most convenient way is using a word processing program. Retrieve the file on disk, make the modifications and store it back. Be aware that the columns in the file must have correspondence with the format in the program. 4.3.1. Jflgghingrv Filgg_ Parameters for machinery listed may be modified if you have a better value. Just replace the values on the file 176 for the new ones. The machinery listed could be modified, but you need to be careful since the computer program has special instructions for some type of machinery, particulary harvesting machinery. The safest way will be to replace an implement for other of similar type. You may need to modify parameter values for the machines. - Adding more machines will not be recommended, since you will need changes through out all the computer program. The economic parameters can be changed in the same way as machine parameters. Just replace the original value for the new one. 1 Suitable hours per week for field operations are stored for the Yaqui Valley, Sonora, Mexico. Data for other locations could replace current data. It is also possible to have similar data for various sites. This will require to modify SUBROUTINE READIN in order to recognize all options available. 4.3.2. Modify Rotgtion Files, A crop rotation file may be modified to add or to drop rotations, and/or to change operation data for a particular crop in a rotation. To organize crops harvested and planted on a given rotation note that the priority order for planted crop must be followed, and it is the following: wheat, cotton and soybeans. If you do not adhere to this priority order, there will be discrepancy in the output. 177 The list of operations for a crop in a given rotation could be modified to accommodate a different sequence of operations. The initial and and dates for operations could be changed to better represent the schedule for a particular farm. The last figure in the rows for operations, is a code for owned or custom hired machinery. Currently all operations have a number 2, for owned machinery. If you want to custom-hire an operation, Just change the two for a one. The machinery selection is set up for four types of tillage systems. Two tillage systems are used for the Yaqui Valley. More tillage systems could be added, but this will require a change in soubroutine READIN to recognize the new file names. The number of rotations in the files do not have to be exactly 5: you may include more or less rotations without conflict with the model. 179 F I L E '0 U T P U T' FAR! MACHIDERY SELECTION FOR YAOUI VALLEY 801 FARM PARAMETERS Farm area: 600. hectares Soil texture: Fine (clay) FIELD OPERATIONS Parcel 1: 300. Hectares of Wheat following Soybeans Combine Sept. 17 to Oct. 15 Disk plow Oct. 1 to Oct. 22 Offset harrow Oct. 15 to Nov. 12 Offset harrow Oct. 15 to Nov. 12 Land plane Nov. 5 to Nov. 19 Fertilizer spreader Nov. 19 to Dec. 3 Disk harrow Nov. 19 to Dec. 3 Wood frame Nov. 26 to Dec. 10 Grain drill Nov. 26 to Dec. 17 Furrower Nov. 26 to Dec. 17 Sprayer Jan. 8 to Jan. 29 Parcel 2: 300. Hectares of Soybeans following Wheat Combine April 16 to May 7 Offset harrow April 16 to April 30 Wood frame April 23 to May 7 Fertilizer spreader April 30 to May 14 Disk harrow April 30 to May 14 Furrower April 30 to May 28 Furrower April 30 to May 28 Row planter May 14 to June 4 Row cultivator June 11 to July 9 Row cultivator June 11 to July 9 Furrower July 9 to July 23 181 1608116 61516! OPTIMIZLIIOI: Machinery systoas union can coaplata all operations aithin tho given tiaa constrints. luabar oi aachinas, sit: and annual hours o1 uso ara givan for aach aachino. Systal Priaary Utility 8131 Dist Oiisat Ron Grain Ron Cost Tractor Tractor Coabine Plow liarroa iiarrou Pl sitar Dri ii Cultivator 21611. 1 96 316 3 12 191 3 6 111 1 5 95 2 3 127 2 3 229 1 6 111 1 1 111 2 6 137 21199. 3 119 361 2 11 681 3 6 111 3 6 116 1 1 216 2 1 212 1 6 111 1 1 97 2 6 137 21825. 3 138 318 2 53 619 3 6 111 3 7 91 1 5 177 2 1 181 1 6 111 i 6 78 2 6 137 26185. 1 96 316 3 85 161 3 6 111 1 5 95 2 3 127 2 3 229 1 i2 57 1 1 111 2 6 137 25131. 3 119 361 2 85 637 3 6 111 3 6 116 1 1 216 2 1 212 1 i2 57 1 1 97 2 6 137 2575i. 3 138 318 2 85 611 3 6 111 3 7 91 1 5 177 2 1 181 1 12 57 i 6 78 2 6 137 25661. 1 96 316 3 85 316 3 6 111 1 5 95 2 3 127. 2 3 229 i 12 57 1 1 111 1 12 137 21817. 3 119 361 2 85 166 3 6 111 3 6 116 i 1 216 2 1 212 1 12 57 1 1 97 1 12 137 25181. 3 138 318 2 85 131 3 6 111 3 7 91 1 5 177 2 1 181 1 i2 57 1 6 78 1 12 137 21753. 1 96 316 3 57 118 2 8 163 1 5 95 2 3 127 2 3 229 1 8 85 1 1 111 l 8 216 21166. 3 119 361 2 57 571 2 8 163 3 6 116 1 1 216 2 1 212 i 8 85 1 1 97 i 8 216 21527. 3 138 318 2 57 511 2 8 163 3 7 91 l 5 177 2 1 181 1 8 85 1 6 78 1 8 216 26765. 1 96 316 3 111 396 2 8 163 1 5 95 2 3 127 2 3 229 i 16 12 1 1 111 i 8 216 25781. 3 119 361 2 111 511 2 8 163 3 6 116 i 1 216 2 1 212 1 16 12 1 1 97 1 8 216 26181. 3 138 318 2 111 518 2 8 163 3 7 91 1 5 177 2 1 181 1 i6 12 1 6 78 1 , 8 216 26321. 1 96 316 3 85 161 2 12 118 1 5 95 2 3 127 2 3 229 1 12 57 1 1 111 2 6 137 25569. 3 119 361 2 85 637 2 12 118 3 6 116 i 1 216 2 1 212 1 12 57 1 1 97 2 6 137 25889. 3 138 318 2 85 611 2 12 118 3 7 91 1 5 177 2 1 181 1 12 57 i 6 78 2 6 137 25813. 1 96 316 3 85 316 2 12 118 1 5 95 2 3 127 2 3 229 1 12 57 1 1 111 1 12 137 21985. 3 119 361 2 85 166 2 12 118 3 6 116 i 1 216 2 1 212 1 12 57 1 1 97 1 12 137 25321. 3 138 318 2 85 131 2 12 118 3 7 91 1 5 177 2 1 181 l 12 57 1 6 78 1 12 137 181 mam-em SELECTED: Least cost system of machines thich cm emulate all operations within the given time constraints. Machine Size m Lise Cost Fuel use (h) (3) (Liters) Prism-y tractor 119.3 kw 3 $4.9 1952. 11407. Utility tractor 57.3 kw 2 574.2 1426. 8921. Cdiine 8.0 row 2 163.0 3742. 5866. Fertilizer spreade- 12.2 meter 1 87.3 67. Lfl'id plate 4.3 meter 2 72.8 243. Did: plow 6.0 dis: 3 106.1 183. Disk have: 4.7 meter 1 206.2 261. Offset hm'row 4.1 matu‘ 2 212.3 232. Wood fr-a 3.7 meter 2 159.2 28. Grain chill 4.9 meter 1 98.0 324. Row platter 8.0 now 1 5.5 207. PM 8.0 row 1 3115.7 187. Sprayer 16.0 row 1 47.0 67. Row cultivator 8.0 row 1 2%.5 154. WT w: (a) (Miactae) Machinc-y 13129.13 21.72 Fuel 5135.47 8.56 Ldoor 847.82 1.41 Timeliness 5153.67 8.59 Gusto work 0.00 0.00 Total 24166.04 40.28 182 Parcol no. iiarvast Crop letod Crop MACHIIE SCHEDULE: Ihaat Soybaans Soybeans imaat 2 love-bar Octobe- 16 23 31 7 11 21 28 1 11 18 25 2 9 16 23 31 3 11 17 21 1 8 i5 22 29 5 12 i9 26 Soptaabor iiactaros oi nori comiatod during not of July Juno llav 1pm Ps'coi Io. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 62 36121 79 1 1 1 1 1 1 1 2 216 93 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Coabine 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1299 1 1 1211 88 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Fortiiizor 2 spreader Land piano 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1216 93 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 93 73133 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1181119 1 1162137 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1131 harrou 1 1131 plan 2 Mint harr i 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 31368211 1 1 1 1 2 216 93 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1218 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1211 88 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Hood iralo i 2 Grain drill i 1 1 1 1211 95 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 lion plantar 1 2 2 2 Cultivator 1 1 1133271191 F urrouor 1 1 1 1 1 1 1211 99 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Spravor 1213213193 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 113 F I L E C 1 I 1 l L tractor 53. .111 2.11 .75 .17 Coabine 2.5 .71 .75 1 11. 37.1 1.2 1.2 1.2 1. 1211. .12 2.1 .75 .11 1.9 Cotton plcter 2.5 .75 .75 1 7. 1. 17. 17. 17. 1. 2111. .12 2.1 .75 .11 6.5 Sell Prop Sprayer 6.1 .65 .71 1 61. 1.1 1.1 1.1 1.1 1. 16. .11 1.3 .71 .91 1.1 Stalk cutter 3.1 .75 .1 2 7. 1.1 5. 5. 5. 1. 59. .26 1.6 .71 .91 1.1 Cultipacker 3.1 .7 .75 1 12. 1.1 2.5 2.5 2.5 1. 31. .22 2.2 .7 .91 1.1 Subsoiler 3.1 .71 .75 1 11. 1.1 9.1 11.1 13.7 ~27. 79. .31 1.1 .71 .91 2.3 Fertilizer spreader 5.1 .65 .712 11. 11.1 1.1 1.1 1.1 1. 11. .95 1.3 .71 .91 1.7 Land plane 1.1 .75 .75 1 12. 12.1 3. 3.5 1. 2311. 11. .11 1.7 .71 .91 1.3 Disk plou 1.1 .75 .11 1 7. 1.1 1.3 11.5 12.6 -319. 275. .13 1.1 .71 .91 3.1 Disk harron 1.5 .11 .15 1 12. 1. 7.1 1.1 1.6 1. 112. .11 1.7 .71 .91 1 2 Offset harron 1.1 . .11 1 12. 1. 7.1 1.1 1.6 1. 112. .11 1.7 .71 .91 1.2 Hood {raae 1.1 .75 .11 2 11. 1. 3. 3. 3. 1. 11. .11 1.7 .71 .91 1.1 Grain drill 6.1 .61 .65 2 12. 1.1 3.1 3.1 3.1 -251. 161. .51 2.1 .71 .91 1 1 Ron planter 5.5 .61 .65 2 11. 1.1 3.2 3.2 3.2 1. 11. .51 2.1 .71 .91 1 1 Furrouer 5.1 .75 .11 2 11. 1.1 2. 2.5 3.1 1. 27. .22 2.2 .71 .91 1.9 Sprayer 5.1 .61 .65 2 37. 1.1 1.1 1.1 1.1 1. 16. .11 1.3 .71 .91 1.1 Ron cultivator 3.7 .75 .11 2 11. 1.1 2.2 2.6 3.1 1. 39. .22 2.2 .71 .91 1.7 Furrouer 5.1 .75 .11 2 11. 1.1 2. 2.5 3.1 1. 27. .22 2.2 .71 .91 1.9 Ollset harron 1.1 .75 .11 1 12. 1. 7.1 1.1 1.6 1. 112. .11 1.7 .71 .91 1.2 Ron cultivator 3.5 .11 .15 2 Econoalc paraeeters .17 1.3 .11 .1 .1 .1 .1 .1 .11 .1 5 Yhflfll VALLEY 111 11. 91. 91. 61. 61. 51. 51. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 61. 51. 51. 11. 36. 36. 26. 11. 12. 11. 31. 31. 16. 16. 12. 59. 69. 19. 19. 79. 71. 66. 66. 66. 66. 66. 17. 91. 91. 91. 66. 91. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 61. 51. 12. 11. 13. 22. 7. 11. 11. 29. 1. 36. 33. 31. 12. 73. 92. 91. 91. 91. 71. 71. 71. 71. 71. 67. 73. 91. 15. 73. 15. 92. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 61. 51. 12. 11. 9. 16. 6. 33 31. 17. 7. 17. 11. 33. 26. 52. 17. 91. 51. 71. 62. 66. 71. 66. 71. 63. 110.11 VALLEY, 711 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 12. 11. 52. 55. 55. 51. 61. 65. 62. 53. 56. 67. 67. 69. 69. 66. 61. 62. 62. 62. 62. 62. 61. 61. 61. 61. 61. 61. 61. 61. 61. 25. 11. 1. 1. 1. 1. 91. 91. 91. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 69. 59. 62. 27. 31. 31. 31. 16. 71. 11. 13. 67. 39. 51. 55. 73. 92. 91. 91. 91. 71. 71. 71. 71. 71. 71. 91. 91. 97. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 69. 59. 61. 27. 19. 22. 26. 12. 55. 11. 11. 31. 31. 13. 51. 95. 91. 91. 91. 97. 71. 71. 71. 71. 71. 69. 11111 VILLEY, 518 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 13. 11. 51. 61. 61. 63. 65. 61. 11. 65. 69. 69. 69. 75. 75. 71. 69. 69. 69. 67. 61. 61. 63. 63. 63. 63. 63. 63. 62. 61. 61. 29. 21. 1. 1. 1. 1. 91. 91. 91. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 71. 71. 71. 51. 31. 12. 11. 51. 91. 17. 63. 92. 56. 56. 56. 91. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 91. 91. 91. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 71. 71. 56. 56. 56. 71. 71. 71. 71. 71. 71. 71. 71. 71. 71. 69. 51. 35. 11. 16. 51. 91. 17. 63. 71. 11. 56. 56. 91. 91. 91. 91. 91. 71. 71. 71. 71. 71. 71. 184 F I L E C O N V E N 1 HHEAT-SOYBEAN 2 HHEAT-SOYBEAN-COTTON 3 HHEAT-HHEAT 4 HHEAT-HHEAT-SOYBEAN 5 HHEAT-HHEAT-SOYBEAN-COTTON 0 1 HHEAT-SOYBEAN 2 5 3 1 38 41 2 9 40 42 11 42 43 11 44 45 8 45 46 7 47 48 10 47 48 12 48 49 13 48 50 15 48 50 16 2 4 0 0 0 3 5 1 16 18 11 16 17 12 17 18 7 18 19 10 ‘18 19 15 18 19 15 20 21 14 20 22 17 24 25 17 26 27 18 28 29 0 0 0 0 0 0 2 HHEAT-SOYBEAN-COTTON QIDNJNlohJMIOAJMIDRD OthDNlMIDNJMfDRJN 3 30 36 40 42 42 43 43 44 44 45 46 47 47 48 10 47 48 12 48 49 13 49 50 15 49 50 16 3 4 0 0 0 .5... ‘1m"‘1018“3fl19 QAJNthJNfDAJMIDRJM-* 11‘ .IJ- .. a.‘ ‘40“09‘13 GOVO‘GQW-‘gfl 41 43 44 a 46 7 47 1o 47 12 47 13 49 15 49 16 5 o o 2 3 116 9 ‘ 1 ¢ OOO‘IO‘UIJM‘ OMNNMNNMNI’OMM GNNNNMMMNMMNNMN 1 3 42 44 45 47 48 4a 48 so so 6 o GNMMMMMNMMMM 185 F". Wt‘mL-ufi 4 3 1 9 11 11 8 7 10 12 13 15 16 0 0 3 17 19 22 23 23 24 24 25 26 27 43 44 44 45 46 47 47 48 47 48 2 4 0 0 0 0 OMNMMNMMMNNM 186 MEAT-HEAT-SOYBEAN 3 1 9 11 11 8 7 10 12 13 15 16 0 3 1 11 12 7 10 15 15 14 17 17 18 0 38 41 2 42 43 43 44 44 45 46 47 47 48 47 48 48 49 49 50 49 50 2 4 0 0 5 16 17 17 18 17 18 18 19 18 19 19 20 20 21 20 22 24 25 26 27 28 29 0 0 GMMMMMNMMMNN ONNNMMNMMND 187 3 3 1 17 18 9 22 23 11 23 24 11 24 25 8 28 29 7 43 44 10 44 45 12 46 47 13 47 48 15 47 48 16 3 4 0 0 0 0 0 0 5 "HEAT-HHEAT-SOYBEAN-COTTON GIDADMIDRJMIURJMUDRD 4 7 3 2 30 36 4 40 42 9 42 43 1 43 44 1 44 45 8 46 47 7 47 48 10 47 48 12 48 49 13 49 50 15 49 50 4 0 QIORDMIORJNIDhJNIDRJM 4 ~o4>m~ea~m.unaa OIOAJNIDRJMIDBJMIDRJNIDAJ 3 16 0 0 5 16 17 17 18 17 18 18 19 18 19 19 20 20 21 20 22 24 25 26 27 17 19 23 24 24 25 43 44 44 45 45 47 47 48 2 3 0 0 0 0 OMMMMMMMMNMN ONNNMMMMMNMN 188 189 F I L E C 0 N S E R 1 HHEAT-SOYBEAN 2 HHEAT-SOYBEAN-COTTON 3 “HEAT-“HEAT 4 HHEAT-HHEAT-SOYBEAN 5 “HEAT-“HEAT-SOYBEAN-COTTON 0 1 HHEAT-SOYBEAN 2 5 3 1 38 41 2 11 42 43 8 44 45 7 45 46 10 46 47 13 47 49 15 47 49 16 2 3 O'DAJNIURJNID .A a N G N .8 ONNMNNNNN 3 7 3 2 30 36 4 40 42 1 42 43 8 44 45 7 45 46 10 46 47 13 47 49 15 47 49 16 2 3 0 0 0 GIUNJMIDAJMIDAJN 3 15 15 14 17 17 20 20 24 25 18 18 19 19 21 22 25 26 000 000 HEAT-”EAT 3 1 6 42 44 45 46 47 1 8 43 45 46 47 49 49 QMMMNMMNM ONNMMMNNMMMN OMMMMNNNM QMMMNNMNN 190 191 4 HHEAT-HHEAT-SOYBEAN 3 5 3 1 38 41 2 11 42 43 8 44 45 7 45 46 10 46 47 13 47 49 15 47 49 16 2 3 0 0 0 3 5 1 16 18 11 17 18 7 18 19 15 18 19 15 20 21 14 20 22 17 24 25 17 25 26 0 0 0 3 3 1 17 19 11 24 25 8 26 27 7 46 48 10 48 49 13 49 50 15 49 50 16 4 5 0 0 0 0 0 0 5 HHEAT-HHEAT-SOYBEAN-COTTON QIUAJNIDAJMID O'DNJNIDAJMIUAJ {DAJNIOflJNIDflDM 4 7 3 2 30 36 4 40 42 1 42 43 8 44 45 7 45 46 10 46 47 13 47 49 15 47 49 16 2 3 0 0 0 OIURJNFONDMIDhDM 1 16 18 11 17 18 7 18 19 15 18 19 18 20 21 14 20 22 20 26 27 1 17 19 8 26 27 10 48 49 13 49 50 15 49 50 16 4 5 0 0 0 0 0 0 GIDNJMIONJNIDAJMIDNJ OIDHJMIDRDMIORJ canantonJMlonam 192 REFERENCES Aaerlcan Soclety of Agricultural Englneers. 1983. 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