AN ANALYSIS OF some OF THE FACTORS AFFECTING CROP YIELDS ON TWENTY-SIX CENTRAL MlCHlGAN FARMS Thesis for the Degreé of M. S. MICHIGAN STATE COLLEGE . Robert Owen 'Kenworthy ' 195,4 .w HIIQUIIMWUIWII!!!(ll!(UIUIIIHIIWIHHM 0451 6749 This is to certify that the thesis entitled An Analysis of Some of the Factors Affecting Crop Yields on Twenty-Six Central Michigan Farms presented by Robert Owen Kemerflv has been accepted towards fulfillment ’ of the requirements for Master of m degree ingzimflinral Economics 7 Major professor Date {/Za/b’l'f 0—169 wm u. -rFQ-n..---‘” OVERDUE FINES: 25t per day per item RETURNING LIBRARY MATERIALS: Ptace in book return to ranove charge from circulatton records V- AN ANALYSIS OF SOME .OF THE FACTORS AFFECTING CROP YIELDS ON TWENTY-SIX CENTRAL HIGH IGAN FARIB by Robert OHen Kenworthy A THESIS Submitted to the School of Graduate Studies of Michigan State College of Agriculture and Applied Science in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Agricultural Economics 1994 A! ‘ .ri’alu. grill: ,vCITP Infield-a. 4.1!lJy- —- .~ ACIG‘IGILEDGMNT This study was conducted under the supervision of Dr. L. H. Brown, Professor in the Department of Agricultural Econom’cs at Michigan State _ College. Much appreciation is due Professor Brown for the time and effort he put forth in supervising this study. I also thank all other members of the Agricultural Economics Staff for their help in the study, especially Dr. Thomas K. Cowden who granted the assistantship without which the study and the writer's education could not have been continued. Special thanks goes to all my graduate student colleagues whose ideas have been used in this study. Special recognition is given Ivan F. Schneider of the Soil Seience Department at Michigan State College and Clarence Engberg of the Soil Conservation Service for their rating of soil types and pro- viding Land Use Maps. Much appreciation is due nw wife, Edna, not only for typing the manuscript but also for helping the continuation of aw education. Special credit is due the twenty six farmers who cooperated in the study by providing the data used for the problem. 532-3 1138-1 CHAPTER I II III TABLE OF CONTENT DECRHTION OF PROBIIEM . O 0 O O O O O O O O O O O O ObjeCtives Of Study 0 e e e e e e e e e e e e e e Malallocation of Resources Under Uncertain Condi- tions. 0 e e e e e e e e e e o e e e HYPOthGSBS e e e e o e e e e e e e e e Pmblems Encountered in Defining Terms Definition of Soil Quality Index . . . Definition of Productive Practice Index. NATUREOFDATAUSED........... CollectionofData.......... Dascription of Data. . . . . . . . . . Distribution of Land Quality . . . . . ANALYSISOFDATA............ Effect of Practices on Yields of Crops Grown on 50118 Of Similar Quality 9 o e e e e e e e e e 0 Yield Variation Within Productive Practice Groups Of 5011 Groups 0 e e e e e e e e e e e e e e e o Yields Calculated for Soil Quality Groups with Productive Practices Not Considered. . . . . . . Variation of Yield Within Soil Groups and Com- parison of Variation Between Soil Groups. . . . PAGE V) U1 U1 Cr to 17 17 22 2h 28 33 CHAPTER - PAGE Yield Index and Variation of Yield Between and withinSoilTypeGroups............. 36 Difference in Variation of Crop Yields for Various Crops Within Soil Groups and Productive Practice Groups..................... 39 Comparison of Variation of Yield Among Crops Be- WeenIndexGroups............... hO Comparison of Variation of Yield Betwaen Crepe on Soil'rypeGroups................ ho An Attempt to Fit a Yield Production Surface by Multiple Linear Regression . . . . . . . . . . . ’41 Calculation of Value of Products and Cost of Production................... 133 Calculation of Returns for Actual Yield Data .. . 0 “4 Calculation of Cost of Production of Crops . . . . 1:6 Cost for Drilling and Planting Using Different LevelsofPlantFood.............. ha Combining or Picking, Hauling and Binning. . . . . ’48 Interest on Investment and Taxes . . . . . . . . . 53 Equating of Marginal Cost and Marginal Value PI‘OdUCteeeeeeeeeeeeeoeeeeeee 53 CHAPTER PAGE Relevancy of Equating Marginal Cost and Marginal ValueProduct....o............. 56 The Average Farmer's Use of Fertilizer . . . . . . 61 IV SUMMARY AND CONCLUSIONS. 0 e e e e e e e e e e e e e 62 BIBLImR-APHOOOOOOOOOOOOOOOOOOOOOOOO 6? TABLE II III IV VI VIII XI XII XIII LIST OF TABLES Productivity Ratings for Individual Soil Types. . . Ratings for Slope Used in Determining Soil Quality 0 e e o e e e e e e e e e e e e e e e e 0 Ratings for Drainage Used in Determining Soil Quality 0 e e e o e e e e e e e e e e e e e e e o Computation of Soil Quality Index . . . . . . . . . Ratings for Various Amounts of Plant Food Added Per Acre Per Year 0 e e e e e e e e e e e e e e 0 Rating Given to Emma Maintenance Values As An Average for the Five Year Period on South Central Michigan Farms. 0 e e e e e e e e e e e 0 Rating Given to pH Values to Calculate Productive Practice IndflXe e e e e e e e e e e e e e e e e e Computation of Productive Practices Index . . . . . Sample Calculation for Determining Humus Mainten- ance for a Field for a Five Year Period . . . . . Distribution of 15,600 Acres in Soil Classes and Crop on Tuenty-Six Central Michigan Farms, 19h8 - 1952 e 0'. e e e e e e e e e e e e e e e 0 Percent of Land in Various Crops in Each Soil Class on Twenty-Six Central Michigan Farms, 19h8 ‘ 1952 e e o e e e e e e e e e e e e e e e 0 Yield Index of Wheat, Oats, Corn, Hay and Their Average Calculated for Soil Index and Productive Practice Groups Grown on the Sample of Central Nfichigan Farms. 0 e e e e e e e e e e e e e e e 0 Crop Yield Index for Wheat, Oats, Corn, Hay and Their Average for Soil Quality Groups and Productive Practice Groups for the Sample of Central Michigan Farms, 19h8 - 1952 e o e e e e 0 PAGE 10 12 15 16 20 21 23 25 26 TABLE XVIII XIX Standard Deviations for Yields of Wheat, Oats, Corn, and Hay Within Seil Quality and Pro- ductive Practice Groups for Sample of Central MichiganFarms, 191115-1952 e o e e e e e e e o e Coefficients of Variation (Percent) for Yields of Wheat, Oats, Corn and Hay for Soil Index Groups and Productive Practice Groups on the Sample of Central Michigan Farms, 19,48 - 1952 o e e e e e e T Values for Yields of Wheat, Oats, Corn and Has’ to Determine Significance Between Productive Practice Groups Within Soil Quality Groups from the Sample of Central Michigan Farms, 19h8 - 1952...‘OOOOOOOOOOIOOOOOOOOO Yield Index for Wheat, Oats, Corn and Hay and Their Average for Soil Quali Groups on Sample Of Central Michigan Fame, 19 8 '- 19520 e e e e 0 Standard Deviations for Yields of Wheat, Oats, Corn and Alfalfa and Their Average for Sail Quality Groups for Sample of Central Michigan Farms, 19118'1952000000eeeeeoeeeoeoe Coefficient of Variation of Cr0p Yield for Wheat, Oats, Corn and Alfalfa and Their Average for Soil Quality Groups on Sample of Cantral Michi- ganFarns,l9h8-l952.............. T Values for Crop Yields of Wheat, Oats, Corn and Alfalfa Hay and Their Average on Soil Quality Groups for Sample of Central Michigan Farms,l9h8-19S2................ Yield Index for Wheat, Oats, Corn, Alfalfa and Their Average for Soil Type Only on Sample of Central Michigan Farms, 19,48 '- 1952 e e e e e e e Coefficient of Variation for Yield Index on Wheat, Oats, Corn, Alfalfa and Their Average for Sail Type Groups on the Sample of Central Michigan Farms,l9h8-l952................ PAGE 29 31 32 33 35 36 37 38 TABLE HIII HIV XXVII HVIII XXII XXII T Values for Crop Yields of Wheat, Oats, Corn, Alfalfa and Their Average Between Soil Type Groups on, the Sample of Central Michigan Farms,l9h8-l952................ Yield Index Calculated by Linear Regression, DoolittleCheckSum.. e co cos. e ee e 00 Percent of Land in Five Crops Used to Determine Total Value Product of Yields for Sample of Central Michigan.Farms, 19h8 - 1952 e e e e e e 0 Sample Calculation of Total Value Product Per Acre of Land for Productive Practice 3.5 on Soil QualityC-roup3.5................ Actual Total Value Products for Some Points of the Soil Quality and Productive Practice Index. . . . Estimated Production Costs per Acre for Various Points of the Soil Quality and Productive PracticeIndexes................. Estimated Seed Cost for Corn, Oats, Wheat and For- age for 0.5 and 11.0 Productive Practice on 301 ' h.0 5011 Quality Index, 1918.8 - 1952 e e e e Hypothetical Assessed Value of Land for Various Soil Qualities for Central Michigan Farms . . . . Sample Calculation of Estimated Production Cost Per Acre of Land, Soil Quality Index 3.5 and Productive Practice Index 0.5 e e e e e e e o e e Crops of a rotation and Recommended Amounts and Analysis of Fertilizer for Brookston and Similar 5011331318800...eeoeeeeeeeeeee Craps of a Rotation and Recommended Amounts and Analysis of Fertilizer for Hillsdale, Fox and SimilarSoiISeries............... PAGE 39 A2 15 1:6 It? ’49 53 55 59 FIGURE LIST OF FIGURES Approximate Location of Sample of Farms on Which This Study 18 Based o e e e e e e e e e e e e e 0 Estimated Seed Cost Per Acre for Corn, Oats, Wheat and.Alfalfa for Levels of Productive Prac- tices e e e e e e e e e e e e e e e e e o e e e 0 Estimated Charge Per Acre for Drilling Grain and Planting Corn for Rates of Application of Plant FOOde e e e e e e e e e e e e e e e o e e e e e 0 Estimated Cost For Combining or Corn Picking and Hauling and Binning Cost Per Acre for Various Yield Indexes e e e e e e e e e e e e e e e e e 0 Estimated Land Value, Nermal and Assessed, for Determining Interest on Investment at Five Percent and Taxes Figured at Fifteen Mills Per Dollar . . Marginal Cost and Marginal Value Product for 3011 Quality Index 3.5 for Some Levels of Productive Practices USing Actual Yield Data and Estimated Production Cost . . . . . . . . . . . . . . . . e Marginal Value Product and.Marginal Cost for Sail Index 2.5 for Some Levels of Productive Practices Using Actual Yield Data and Estimated Production COSt. e e e e e e e e e e e e e e o e e e e o e 0 PAGE 18 51 52 57 S8 CHAPTER I DESCRIPTION OF THE PROBLEM Predicting crop yields is one of the more difficult problem farmers have when making plans for the future. The information available for such predictions is in the form of average yields for states, crop reporting districts or type of farming areas. Another guide used in planning is "good standard" crop yields such as 25 percent above averagel. This average varies from year to year for the same district or area. This year to year variation is primari- ly associated with weather conditions in the area during the growing season. Weather predictions for an entire growing season are dif- ficult to make and present a problem to farmers attempting to esti- nate crop yields. At some time during the process of farm planning an estimate of crop yields has to be made. This estimate, when based on the average yield for the state or area in which the farm is located, is not as accurate as is needed as a basis for a sound farm plan. The area or state average of crop yields is made up of yields from many different types of soil with a large range in cropping prac- tices used. A fairly accurate estimate of crop yields could be made for an individual farm if certain facts were known about the soil types on the far. and cropping practices used to raise crops. 1 "Farm and Home Flaming Part I, The Farm," Extension Ser- vice, mchigan State College, 191:8. 2 In this stuchr an attemt was made to devise a method to es- timate crop yields. The information used for this estimate is soil type, slope, drainage, plant food added, humus maintenance and pH. Actual yield data was taken from fields for which the above informa- tion has been recorded. Objectives of the Stuq To devise a method for estimating crop yields for soils of different productive capacity. To determine crop yields using vari- ous levels of practices on soils of different productive capacity. To study the amount of variation‘of crop yields on soil of different quality and the variation in yield as different levels of practices are used on soils of similar quality. To study the variation in yields betwaen crops to determine if am one crop varies more in its yield than an other crop. To determine the proportion of each quality of soil used for different crops. Another problem studied was the variation of crop yields. An attempt was made to determine the amount of variation of yield as practices varied. If variation in yield decreases as the prac- tices under which the. crop is grown are improved, the uncertainty associated with crop yield can be decreased. Wham farmers use average yields as estimates of future pro- duction, uncertainty appears. If he applies inputs for average production and weather conditions are favorable, he has applied too 3 few inputs. Conversely if weather conditions are unfavorable he has applied too many inputs. Crop insurance does not always solve the problem for if he insures for low yield and yield is high he has lost his premium. Failure to insure when yield is low results in a loss of compensation.2 Halallocation of Resources Under Uncertain Conditions ~With uncertain expectations the defects of resource allocation are of two types. 1. Using the expected mean of yield or price with these proving to be correct and, 2. using the expected mean of yield or price and these proving to be incorrect. If the mean of prices or yield is used and they are correct and plans in anticipation of these values are made, the allocation of resources would not be in terms of the equating of marginal cost and returns. The producer, under most circumstances, desires to limit the anticipated dispersion of profit or losses. This desire and his subjective value of risk leads the producer to allocate his resources, not with maximization of profit as a sole guide but with due consideration of maintaining a certain degree of safety. For example, a farmer would not add as much fertilizer to his corn as his resources would allow if he used all his resources for the single enterprise. This is due to the larger loss he may sue?- tein if the price (or yield) expectations do not materialize. In 2 Heady, Earl 0-, Economics of A riculture Production and 32m 923, Puntice-Hmorf,-%m39 - uh}? -- 1; some cases expected yields do materialize and profits are lost be- cause marginal costs and returns are not equated. 0n the other hand, if the mean of prices (or yield) is used and it proves incorrect the malallocation of resources is even in greater error. It is obvious that under these conditions marginal cost and return cannot be equated. Also in this situation profit will not have been maximized.3 Motheses There is a relation betIreen crop yields, level of practices used and quality of soil on which the crops are grown. The variation of crop yields, within a year, is greater on soil of poor productivity than on soil of good productivity. I The variation of crop yields, within a year, is greater on soil of similar quality, when poor practices are used than when good practices are used. The amount of variation of yield is greater for corn and oats than for wheat and alfalfa within soil quality groups. It is proposed that a production surface can be constructed by a statistical method to predict yields of crops on various qual- ities of soil using different levels of practices. 3 Johnson, D. Gale, Forward Prices for Agriculture The Uni- versity of Chicago Press, C_——hicago, min, '9'1W,"pp". E3 - us. It is proposed that the value of product and cost of pro- duction can be computed and from this the most profitable level of practices for different soil qualities can'be found. Problems Encountered in Defining Terms An attempt has been made in this study to predict crop yields on the basis of soil quality and practices used in growing these crops. Soil quality and many of the practices are observed in quali- tative terms. It has been necessary to devise a schene for assigning numerical values to such qualitative terms for statistical manipula- tices. Another probla encountered was how to weigit these factors, both for soil quality and for productive practices. Definition of Soil Mt: Index Soil quality is defined in terms of the inherent capacity of the soil to produce. Three qualitative factors were considered in the construction of this index. They are soil type, slope and drainage - natural or artifical. Each of these three factors was rated from 0.0 to 11.0 depend- ing on its contribution to soil quality. (Zero denotes no contri- bution and 11.0 the highest possible.) These factors will be explained separately. 6 go}; 2123. This is probably the most important factor of the three qualitative factors for constructing the soil quality index. The ratings for soil type generally follow the soil class of the soil type which denotes the textureh of the soil. Low ratings are generally given soil types with soil classes of loanw sands and sandy loans.5 Higher ratings are given to soils with soil classes of loans and silt loams (Table I). §l£° The rating for slope has the same parameter as soil type. The slope ratings follow the designations of slope given by the Sail Conservation Service, (Table II). Fields which did not fall into one category were rated by averaging the approximate percentage of land in each category. For example, a field having half of the land in a six percent slope and half in a zero percent slope, would be given a rating of 3.5. Drainage. The ratings given drainage have the same parameters as the above two factors. This rating is not only more difficult to determine but also is more difficult to define. It probably is not as accurate as the rating for soil type and slope. This is due to 1* Texture refers to size of particles in the soil. The per- cent of sand, silt and clay determine the soil class name of a soil type. Miller, C. E. and Turk, L. 11., Fundamentals 31; Soil Science, John Wiley and Sons, Inc., New York, pp. 55 - HS. 5 The soil type name consists of two parts, soil series and soil class. Soil series identifies the area or place where the soil type was first found and mapped and soil class refers to the tax- ture of the soil. For example, in the soil Miami loam, Miami is the soil series, 1083: is the soil class. 8338 33m cemEeE .ooeodom dew mo nagging .mnopwnm coached... use nonaennom seeH hp cognac? .33 3am 9538.5 0.4 53 c3388 0.: 53 aim 35:8 «6 50A nmeosoo a.m .. 50A has sovnxoohm fin 53 hogan SE fiestas o.m 53 Hats mgm 53 £3.36 m.m 53 £88: m.m 33¢ eesmv 53 paces: m.m 53 338 Tm 53 3% 953m Tm 53 him take: m.m 53 .3338 o.m 53 aim 33a ad .33 35m 323 ham 53 2°28 are. 53 afieeomfiam m6 53 sea m.~ :3 56.33 m.w 53 85...... 8E message m.~ 53 seem semen mt. 53 team e833 m.~ 795 53 teem e32 a.“ 53 macaw .858 .3 53 35m cough a.“ 53 seam 32.3.5. 0.“ 53 seem has: ed. .83 seam woe o.m .33 aim edges o.~ .83 sense afieeoeofiem o.~ 53 seem season o3 33c 02:5 53 been e538 m3 765 seen 53 83:8 m3 33 sense. 33:8 m3 chem 53 533 N...” seem .53 8.38 HA seem .933 35% to 2.5 .33 team eases m6 seem e33 eases to eeem g3 “3.52 o5 seam E3 338 m6 eeem 553 Sega to oaks Hfiom o.: 3 1m o.m 0» H.N com on H.H o.H ca 0.0 waned News” *mmmwa .HHom. 585E gunman—.2...“ mom mozfiadm anaomm Han. TABLE II RATINGS FOR SLOPE USED IN DETERMINING SOIL QUALITY Rating 000 - 1.0 101 " 200 201 "' 300 3.1 - 14.0 Slope in percent over 18 12 - 18 6-12 0-6 the fact that difficulty was encountered when trying to define drain- age. TABLE III The ratings and definition for drainage are given in Table III. RATING FOR DRAINAGE USED IN DETERMINING SOIL QUALITY 0.0 " 1.0 101 "' 2.0 201 " 3.0 Be]. "' h.0 Explanation very wet the Poorly drains year around ed wet runs and areas ‘which always delay opera- tions until too late to put in crop at the proper time. Crop frequently drowns out completely Imperfectly"well drained drained wet naturally or runs that artifically frequently delay'till- age opera- tionse Crop production is frequent- ly'halpered by wet con- ditions 9 An attempt has been made to combine the three factors which determine soil quality into an "index of soil quality." This was done by calculating the cube root of the product of the three fac- tors, (Table IV). The product of the three factors was used rather than the am so that the factor with the lowest index was dominant in determining the index. For example, a field with very poor drain- age which could not be used for agricultural purposes would have a drainage factor of zero which would make the entire soil quality in- dex equal to zero, even though the sloPe factor and soil type factor were each estimated at four. Equal weight has been given each of the three factors used in calculating the soil quality index. This may or may not be the correct procedure to use in the construction of an index of this type. we of the alternatives considered when forndng this index was using only soil type as a measure of quality. Comparison of the soil quality index and type for estimating yield will be con- sidered in the statistical section of this study. Dafinition of Productive Practice Index This is the term used to describe the more important cultural practices used by farmers in producing craps. This index is based on three factors: plant food added, humus additive practices and pH. Other practices such as type of tillage, seed used, seed treat- ment and time of planting were omitted due to difficulty of measure- nnt and unavailability of this type of data. 10 neon 0.: 33on Fem ”a? a :83 n noeonoo m.m =33 2H. neuron—00 m. some? a a .33 beam 3m e333 .m 8E53 seam mam 3 snags m a. 23s m.m zoom: agmv 53 mace»: mum an is a .33 33 388 m o.m e33: seemammeeafifl Wm 53 beam 8:3 .m 53 2933 a. 50A Econ m.N om defies a swan 33.33 m w 53 been ms... 33qu m.~. .qrmeeem bah 53 53 M.“ 338 sees... 33.: .N been .33 H 53 53 a.“ 30 e5 3.3 g .3 deeming beam . neon ens; o.~ henna mm .m m Nos“. 0 :33 been .309 o.~ nausea . 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Mama? 0 N a 53 @5m .H pcoHoHHom m 3a 53 .H m m 5 fig 9:55 :33 m4 m 023an has“ auqq .H can oawonno m @313 an” m.H Damon Sow—don w...” :8 gm 2..de «.H .933 5%“ 28m . o Ham m .983 SE 3% hogan a 95m 56 33.5 Eon a 93m .0 z o E s“ 2 «20.30 . Easnvfiém m o 30:: 23m Snow ham :5 25. 4.0 «Huang 0 . 509 can 63.83 9309 08385 H .n . 0.0 .Hopowb 1w 0...” 3. H6395 . no: QM . m com 3 a...” m hOH . . ON 50A pd” cm 3 H o 0.: 3 Hon um 0 $535 MHEDO .HHom ho ona tan—RH Ema; mm . mm . 68m a Egg .3325 Go? no.3? Iaoo an? F woken £3: a.“ ”33038“ mono gauge.“ 38 «83230 mmwdflp an 30: 53:25 goflflfi no 3 -8.“ :5 3E 92. $3,an Ends” do: @836 398.203 £30me 0 I 0 ”been?" «A I o 333““ 1800 950 9598 3.52609.“ mono 653. .8093 pm 993 5“ van 3 33” 03 H3 15.. 933.9390 95 32 mama: 52: 393 Una an?" pm: @3593 hflhoom Eugen we .. «a 930.3 .235 pot bob .3033 m." .35 0.: 3 HA. oom onH-w Hll Com 3. Had OJ” 09. 0.0 338 'l‘l ml! Ill 4" ii” IH‘ 3? *NMQZH Edna Ham .5 20HBH 392. A mg 583.5 Ammv macaw 2.5.33.0 .30 3h 12 Plant Food. The ratings for this index have the same para- meters as that or the soil index. Ratings for various amounts of plant food added are given in Table V. TABLE V RATING FOR VARIOUS AMOUNTS OF PLANT FOOD ADDED PER ACRE PER YEAR * -: “—— ‘_— Code for Plant Food Added Pounds Pounds Rating Plant Food Rating Plant Food 0 0 2.1 105 0.1 5 2.2 110 0.2 10 2.3 115 0.3 15 2.8 120 0.h 20 2.5 125 0.5 25 2.6 130 0.6 ‘ 30 2.7 135 0.7 35 2.8 180 0.8 ho 2.9 1&5 0.9 us 3.0 150 1.0 50 3.1 155 1.1 55 3.2 160 1.2 60 3.3 165 103 65 30h 170 1.h 70 3.5 175 1.5 75 3.6 180 1.6 80 3.7 185 1.7 85 3.8 190 1.8 90 3.9 195 1.9 95 h.o 200 2.0 100 13 Humus Maintenance. For the calculation of humus maintenance, (hie Extension Bulletin 1756 was used. Crops were rated with plus or minus values depending on whether they added to or depleted the soil. For example row crops, grains and annual grasses have a de- pleting effect on the soil so negative values were given these crops. Slope was also considered in this Bulletin. The steeper the slope the greater was the depletion. The soil building crops, alfalfa, clover and perennial grasses were given positive. ratings. Fertili- ser, seam and green manure were also given positive ratings. In the calculation of humus maintename in this study, the additive practice, manure per ton was changed from 0.15 to 0.30. This was done because in (bio Extension Bulletin 175, the main con- sideration for manure being added was for plant food. In this index (humus naintenance) it is assumed that the humus added by manure is acre important than the plant food added. 810pe was omitted in the calculation of humus maintenance in this study because it was in- cluded in the soil quality index. Various values of humus maintenance and their rating are given in Table VI. A sample calculation of the hulns mutenance index is given in Table II. 5 Salter, 11.11., Lewis, R. D. and Slipher, J. 1., "Our Heri- ttao, the Soil,” Ohio Extension 301161211: 175, April 1936. 5011 depleting crops are given a negative value and soil building crops ”9 817811 a positive value. These values are added over the five 7031' Period which give the value of humus maintenance. TABLE VI Rating 0.0 0.1 0.2 0.3 0.1. 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.1: 1.5 1.6 1.7 1.8 1.9 2.0 Value " 9e0 .. 8,65 - 8.30 ' 7095 ' 7.60 ' 7025 - 6e90 ’ 6055 - 6020 - 5.85 - 5.50 - 5.15 - h.80 "' 140,45 "' 14.10 - 3.75 ' Beho - 3.05 - 2.70 "' 2035 - 2.0 Rating Value 2e]. " 1065 2.2 ' 1030 203 - 0e95 20h - 0060 205 " 0.25 2.6 ,1 0.10 2.7 f 0.115 2.8 ,1 0.80 2.9 ,4 1.15 3.0 ,6 1.50 3.1 l 1.85 3.2 ,t 2.20 3.3 K 2.55 3.h 5 2.90 3.5 l 3.25 3.6 f 3.60 3.7 r‘ 3.95 3.8 ,l 3.05 3.9 ,4 h.65 h.0 / 5.0 or more n.0, were given pH values from 14.5 to 7.5, Table VII. RATING GIVEN T0 HUMUS MAINTENANCE VALUES as AN AVERAGE OF THE FIVE YEAR PERIOD 0N SOUTH CENTRAL MICHIGAN FARM, 19h8 - 1952 Soil Aciditz 5232' For the factor pH, ratings from 0.0 to The productive practice index was calculated by taking the cube root of the pro- duct of the three individual factors - plant food added, humus maintenance and pH. index. Table VIII shows the entire productive practice TABLE VII RATING GIVEN TO pH VALUES USED TO CALCULATE PRODUCTIVE PRACTICE INDEX pH pH Rating value Rating value 0 h.50 2.1 6.07 0.1 h.57 2.2 6.15 0.2 h.65 2.3 6.22 0.3 h.72 2.h 6.30 0.h h.80 2.5 6.37 0.5 h.87 2.6 6.h5 0.6 h.95 2.7 6.52 0.7 5.02 2.8 6.60 0.8 5.10 2.9 6067 0.9 5.17 3.0 6.75 1.0 5.25 3.1 6.82 1.1 5.32 3.2 6.90 1.2 5.h0 3.3 6.97 1.3 5.h7 3.h 7.05 1011 5055 3.5 7el2 1.5 5.62 3.6 7.20 1.6 5.70 3.7 7.27 1.7 5.7? 3.8 7.35 1.8 5.85 3.9 7.h2 109 5092 heo 7.50 2.0 6.00 .om.o 3 3.0 son.“ someone was 33. you .9356 .ooflomam 35308 one am 5" “Samson.“ 3a 0.... out 03:80 was 35.39am.“ Hmaoaoesoo no savanna 053608 on» .agozom .83 3.23. .mfin “~3ng "83:09 -nm cane ..Haom one .ownsanom nee: ..< .e .nonnaam on. .n .m .nannq ..: .m .nopanm_snne nopnmn<_*n mm . mm . flak/m. a News.“ oeapowam wcfigonoa. m; on as an 09.02 ho o.m x 3 SA a. boom 95.3 no monsom once .3 CON 0.... Hma bosom 0.953 new 83$an To 3 do me om; x 3 $4 .. coon 8.8.3 mo 356m 03 3 8H bonus 0.85.: an. Canasta 0.6 3 :.m we o.m I 3 md.m .. soon 65% mo .253 8H 8 am cocoa cheque one no» apnea m.m 3. m1. ma om.m .. 0.... o.m .- soon 9:on no 356a om on 0 teens masses use nonafiom HoPQH mm Anny $30.30th 33983 35m 33 ones you memo.» obs...“ Ho omoho>¢ page too.“ 95.8 $3 0.: 3 H.m Com 0» H.N Oow 09 H...” o...“ 3. 0.0 33% uses: Ugomno 93.0mm *HNQZH Eon—”905E EBODQOE ho ZOHHRBDESD HHH> £648 CHAPTER II NATURE OF DATA USED Collection of Data Twenty-six farms in the counties of Ingham, Eaton, Barry, Clinton, Shiawassee, Genessee, Ionia and Livingston were selected for the study (Figure 1). An effort was made to include as many soil types as pos- sible and the sample was limited to farms on which dairying was the Iain enterprise. . All the data available were taken from the Farm Account Re- cords before the field work was started. The farm operators were interviewed for additional information regarding their practices to supplement material from the farm records. Il'he data needed for this study were collected on individual fields rather than farms in their entirety or by soil type. It was assumed that this was where farmere' problems lie when considering soil nanagenent and land use decisions. Questions were in the direct- ion of What should be done with particular fields?” The data were not taken on particular soil types because most fields on farms in the area studied have more than one soil type. Due to the complexity of the data needed for this study s. purposive sample of farms was chosen. The farms included were those on which records had been kept in cooperation with the Department of Agricfltural Economics for the years 191.8 - 1952. These had maps of their ferns in their Fern Account Books showing the crops grown on 07. O" 35' “o ”- 4-0 W' 97‘ IRON DICKINSON ‘ 4.4 D h‘ (NOR/N ‘1" V- CRAWF'D OSCODA ALCONA M15540!!! £03604". OGEMAW [0360 . "WORD ARENAC an escrow cum: rum/N NEMYGO MICOSTA ISABELLA MIDLAND TUSCOLA JANILAC MON 7 CALM GRAIIOT SA GIMW mvr . GENES“ “Pf" 0mm ION/A. amrafi e 5mg. . O o O 1 . ° ° I ° ‘ walla ALLEGAII unr , E'ATON mama ummr’u O O 41' j 1. Approximate location ofsalpleoffarns " .' '- on which this study VAN sum: mum. away» JACKSON WASHTEIMIV mm was based. 49" ‘7- suosmv 4mm: ”11.130445115me manna: or . 00 07° 33' 0-1219 19 each field over the five year period. Crop yields for each field must have been recorded in order to determine the yield per acre. Relatively few farm account cooperators record data in the detail needed for this study. Soil type and slope of each field were taken from land use naps prepared by the Soil Conservation Service. Drainage was de- terndned by impaction of each field by the writer and discussion with the farm operator. The amount of plant food added per acre was determined by the amount and analysis of fertilizer added each year over the five year period plus 25 pounds of plant food1 per ton of manure applied. The total pounds of plant food applied per acre was determined and di- vided by five to obtain the annual average for the fieldz. The value for humus maintenance was determined by adding the values given for crops in Ohio Extension Bulletin 175, plus 0.3 for each ton of nannre per acre plus the value of green manure crop plowed down. See Table II for a sample calculation. 1 Miller, 0. 3., Turk, .L. 11., Fundamentals 9;; Soil Science New York, John Wiley and Sons, Inc.,. p. 219. ”m the average a an of manure contains about 25 pounds of plant mtrients. (Ten pounds Nitrogen, five pounds Phosphorus and ten pounds Potassium)" 2 For example 11' for a five year period'600 pounds of h-16-16, 200 pounds of 10-10-10 and twalve tons of manure per acre were added, the total pounds of plant food added is 576 and the average for the fig. year period is 115 pounds per acre. This is rated at 2.3, Is V. TABLE IX SAMPLE CALCULATION FOR DETERMNING HUMUS MAINTENANCE FOR A FIELD OVER A FIVE YEAR PERICD} Humus Green Humus Manure Humus Crop maintenance manure maintenance ton per maintenance grown value crop value acre value com "' 200 Alfalfa )‘ 2.5 10 300 Oats "' 1.0 plowed Wheat - 1.0 down Alfalfa first year i 2.5 Alfalfa second year ’4 0.5 *‘Value of humus depletion equals - 11.0 and value of humus added equals 8.5. The humus maintenance value for the field is 7‘ h.5. This is rated at 3.9, Table VI. The pH for each field was determined by test with a Soiltecx kit3 and line application for the five year period was recorded. Description of Data The distribution of the acreage and percent of total land used for each crop in each soil group included in the study is given in Table I. On these farms nearly 57 percent of the land was in the 3.1 - h.0 soil quality group. Nearly 1th percent of the total land 3 This is an indicator solution with two indicators, (Aurin and Brena Cresol green) dissolved in Ethyl alcohol and distilled water. The solution is slightly acid. 21 poem Ao>OHo one msfiooom unseen .pwonnxosm .aoHHem possum eonsaonHaa madam new noenhom .mpomm nsmsm moenaosas «mmH .. SS .95..“ Banana Afi§%§§ may. CHAPTER III ANALYSIS OF DATA Effect of Practices on Yields of Crops Grown on Soils of Similar Quality The yield index1 for the main crops grown was calculated for groups of productive practices for each soil group, Table XII. Due to the lack of data for the productive practice groups 3.1 - 14.0 and 0.0 - 1.0, the fields were divided into two groups according to pro- ductive practices (2.1 - h.0 and 0.0 - 2.0) and the yield index was calculated, Table XIII. There were small differences in the yield of wheat, especially when similar practices were used on the 130 top soil groups. Yield of wheat dropped sharply when grown on soil type 1.1 - 2.0. Considering the difference in yield of wheat grown on fields in the top soil group, it can be seen that good practices increase. yield thirteen index points over the lower group. On the 2.1 - 3.0 soil group good practices increased the yield six index points over the poor practices. This may indicate that more response was derived from good practices on good soil than from good practices on soil - 1 Yield index was calculated on a yearly basis to reduce the variability of the index due to different weather conditions for each year. The average for each year for each crop was found and set equal to 100. The index was calculated by dividing the individ- ual observations by the average and multiplying the result by 100. 25 00 H0 S 8 :m :m a 2. 00H 8: 0d .92 26 no.3 HH< OH m 5 HM om mm mm mm moH Hmm mm uaogwahomno Ho none—.52 mm «0 R mm a 3:” :NH «0. m9” :0: :0: as: flash: 0: :0 d. mm mm «0 05 8 2: m3 E00 00 a: 00 me 00 m0 8 R :2 m3 mfi 38 mm m0. mm 8H mm RH we :0 m3 SH 000;: used 33» i 020 0.: 0.0 0.m 0.: 04 0.“ 02m 0.: 0.: 0.“ 0A 0.: 0.: 0.0 0.m 0.: 3 B 8 3 3 8 e 8. 3. 8 3 3 3 8 3 3 8. 0.0 H.H H.“ H.m 0.0 :.H H.~ H.m 0.0 H.H a.“ H.m 0.0 H.H H.~ H.m NoocH 333nm NoncH 338nm 03an 00300.5 Moog” 3320.3 04 .. 0.0 0.0 .. H.H 0.m .. dm 0.: .. dm usefi :00 «m3 .. 0:3 .25 23:60: go .6 g a; 20 3.05 0.5008 323% EBBSE 9: EH flow 8a HHH Eda Beanie ”0554 Emma 05 a £80 .840 .53: e0 Hem SE» 26 3 5m .8 3 mm SH 398 HHs omens: om pm om mHH HOH HOH «HHwHH< hm mm 40H «HH shoe 2. I t. :8 mm 00H 33 8 cm «OH mm mOH as on: $05 33» 080 o.« I 0.0 0.: I H.m o.m I 0.0 0.4 I H.N o.N I 0.0 0.: I H.N H85” 0033.8 Moog 333nm , H38” oofiomnm Cow I H.H Com. I How 004 I Hem ROUGH Hdom «me: u 0:3 is: 243080: 3200 m0 0.53 ea mom $005 8H8?“ EBBoE 024E005 35400 flow mom Hog: HE: ea ha .280 .840 .55: mos Enfi a some HHHN H.549 27 without a high inherent capacity to produce. Comparison cannot be made on soil group 1.1 - 2.0 due to lack of data. For cats the response on the top soil group to good ”practices over poor practices gave a yield increase of eleven index points. In soil group 2.1 - 3.0 the increase of good practices over poor was only seven points. This also bears out the fact that the response to good practices on good soil was larger than the response to good practices on the 2.1 - 3.0 soil group. There was also a larger dif- ference between yield of cats on similar practice groups of soil groups 3.1 - 14.0 and 2.1 - 3.0 than there was for wheat. For corn the response to good practices on the tap soil group was eight index points. In soil group 2.1 - 3.0 the good practice group had a lower yield index than the 0.0 - 2.0 practice group. No explanation can be made for this. The effect of good practices show- ed more response on good soil than it did on soil group 2.1 - 3.0. For alfalfa the effect of good practices on soil group 3.1 - h.0 shows no increase in yield over that of 0.0 - 2.0 productive practices. However, for soil group 2.1 - 3.0 good practices showed an increase of thirty-eight yield index points over that or 0.0 - 2.0. This large increase in yield and the lack of increase in yield in soil group 3.1 - 14.0 may be due to the difference in the number of cuttings of hay taken from the fields. A great deal of reliability should not be placed on the large increase in yield in group 2.1 - ' 3.0 or lack of yield increase in group 3.1 - h.0. Also the lack of ability in measuring hay yields accurately was another factor. 28 The average of all crops shows a general decrease in yield index as soil quality goes lower and as poor practices are used. Yield Variation Within Productive Practice Groups of Soil Greys In order to determine the variation about the mean of yield index within productive practice groups for each soil group, the standard deviation2 was calculated for the yields that are presented in Table XIII. This shows the mean of all the individual variations about the mean of the yield index and is presented in Table XIV. For soil group 3.1 - h.0 the standard deviations were larger for all crOps for the poor practices, the greatest difference being for cats. For soil group 2.1 - 3.0 the standard deviation was larger only for alfalfa in practice group 0.0 - 2.0 when comparing productive practice groups. Using the standard deviation to compare the amount of varia- tion in productive practice groups did not give a completely ac- curate comparison due to different means in each group. For a. more accurate comparison of the amount of variation of yield for productive practice indexes of a soil group, the coefficient 2 Simpson, George and Kafka, Fritz, Basic Statistics, w. w. Norton Company, Inc., New York, p. 199. Formula used as s :J’f—xz T where 12 a squared deviation from mean and N 8 number of observations. I\ n 29 m©.ma ::.om om.~m m:.mm :~.mm oo.mm wHHoHH< ow.wm madm mm.mm mmém goo as.m~ em.m~ me.me m~.am . ee.~m name m:.m «JAN 23mm mméh mm.mm pooch :Ofipwwbon osmocwpm noun o.m I 0.0 0.: I H.N o.~ I 0.0 0.: I H.N o.m I 0.0 0.: I H.N NoooH ooapoenm woosH evapooam NoocH oofiaoenm o.m I H.H o.m I H.N 0.: I H.m KoUGH HHom «m3 .. Sea .053 zeoEoE ago no means mom .285 8:058 EBDBE a: 5.23 don SE. a; a: .280 .25 5%: .6 8E me 98:58 gem >HN.HAm¢ wm om >4 om mm mm cmaomaa mm :4 mm mw choc um mm Hm mm on once a: mm mm on an on on: pceoaom rillllla mono ocw I 0.0 0.: I H.N o.« I 0.0 0.4 I How Oem I 0.0 0.: I Hem steam evaporam NoosH cospownm KoosH deepens; Oem I H.H Ocm I Hem 0.: I H.m Moan HHom «mad I wash .mzmem zeonoH: nemazmo no seesaw are 20 nieces mcHaoemn msHaopeomm nze mesons xmnzH qum noe_nam nze .zmco .meeo .aemm3,no nnann men Anamommav‘zOHaeHmee no mBZMHeHaemoo bunmqmds 32 Significant differences (Table XVI) were found for yields of 'wheat, cats and the average of all crops'when.the two groups of pro- dnetive practices in soil group 3.1 - h.0 were compared. In soil group 2.1 - 3.0 significant differences in yields of alfalfa and the average of all crops were found when comparing the yields of the two productive practices. TABEEIXVI T VALUES FOR IIELDS OF“WHEAT, OATS, CORN AND HE! TO DETERMINE SIGNIFICANCE BETWEEN PRODUCTIV'E PRACTICE GROUPS WITHIN son. QUALITY GROUPS FROM THE SAMPLE OF CENTRAL MICHIGAN Finis, l9h8 - 1952 Soil Index 3.1 " II.O 201 " 300 Practice Indexes Practice Indexes 2.1 " h.0 and 0.0 " 2.0 2.1 - 1‘00 and 000 - 2.0 Crop t t Wheat 2.63* .76 Cats 1.99* .99 Corn 1.77 - .55 Alfalfa h.h6* Average 2.93* 3.20* *Significant difference at 95 percent level 33 Yields Calculated for Soil Quality Groups with Productive Practices Not Considered Analysis of yields for different soil quality groups was undertaken to determine differences between and variation within soil quality groups. The yield index (Table XVII) was calculated for each soil quality group. TABLE XVII IIELD INDEX FOR WHEAT, oars, ccaN AND HAY AND THEIR AVERAGE FOR SOIL QUALITY GROUPS ON SAMPLE OF CENTRAL MICHIGAN FARMS, 19w - 1952 I J Soil Index fl 3.1 " heo 2e]. " 3.0 Is]. " 200 0.0 " 1.0 Crop Yield Index Wheat 100 98 Cats 106 102 70 Corn 109 85 Alfalfa hay 103 100 58 Average all crops 105 96 65 L4; For wheat in the two top soil quality index groups there was only two yield index points difference. Oat yields between these ‘hIo soil groups also have small differences with a sharp decrease in yield for soil group 1.1 - 2.0. Corn yields betvmen the two soil groups had the greatest difference in yield index. Alfalfa hay yield difference was small for the top two soil quality groups 3h with a sharp decrease in yield for soil group 1.1 - 2.0. The average yield of all crops showed a decrease as soil quality decreased. Variation of Yield Within Soil __Grroups and Comparison of Variation Be- tween Soil Groups In order to determine variation of yield within soil groups the standard deviation was calculated for crops by soil groups (Table XVIII). Standard deviations were larger for corn, alfalfa and average of all crops for soil groups 2.1 - 3.0 when compared to soil group 3.1 - h.o. TABLE XVIII STANDARD DEVIATIONS FOR FIELDS OF WHEAT, OATS, CORN AND ALFALFA AND THEIR AVERAGE FOR SOIL. QUALITY GROUPS FOR SAMPLE OF CENTRAL MICHIGAN FARMS l9h8 - 1952 Soil Index 3.1 - 11.0 2.1 " 3.0 1.1 "' 2.0 0.0 "' 1.0 Crop Standard Deviation Wheat 27.00 20.97 Oats 3h.33 32.76 Corn 33.75 3h.28 Alfalfa 29.142 110.87 Average 31.19 314.27 35 For a comparison of variation of yield between soil quality groups, the coefficient of variation was calculated for yields on soil quality groups (Table XII). The coefficient of variation was larger at 2.1 - 3.0 for corn, alfalfa and average of all crops when compared with soil group 3.1 - h.o. This means that yields in this group had a larger variation than when grown on soil quality group 3.1 - 1:00. TABLE XIX COEFFICIENT OF VARIATION OF CROP YIELD FCB WHEAT, OATS, CORN, AND ALFALFA AND THEIR AVERAGE FOR SOIL QUALITY GROUPS ON SAMPLE OF CENTRAL MICHIGAN FARMS, 19h8 - 1952 5011 Index 3.1 - h.o 2.1 - 3.0 1.1 - 2.0 Crop ' Percent Wheat 27 21 Cats 32 32 Corn 31 hO Alfalfa 29 141 Average 30 36 For determining sigrrificant difference in yield be’meen soil quality group a "t" test was used (Table XX). Differences in yield of the two top soil groups were found to be significant for corn and average of all crops. For the two bottom soil quality groups 36 TABLE XX T VALUES FOR CROP YIELDS OF MIEAT, OATS, CORN AND ALFALFA HAY AND THEIR AVERAGE ON SOIL QUALITY GROUPS FOR SAMPLE OF CENTRAL MICHIGAN FARMS, l9h8 - 1952 Soil Index 301 " 14.0 and 201 " 3.0 2.1 " 3.0 and 1.1 "' 2.0 Crop t t Wheat .h2 Cats .75 10.52* Corn ‘ 7.9h* Alfalfa .63 3.h8% Average h.2u* 3.22* *Significant at 95 percent level significant differences in yield were found for cats, alfalfa and average of all crops. Yield Index and Variation of Yield Between and‘Within Soil Type Groups An inspection of the data indicates that a yield.index based on soil type alone could be made that compares favorably with the index based on the three factors of soil quality. Iield.index (Table III) when calculated for soil type and compared with yield index calculated with the soil quality index 37 TABLE XXI IIELD INDEX FOR WHEAT, OATS, CORN, ALFALFA AND THEIR AVERAGE FOR SOIL TIRE ONLY ON SAMPLE OF CENTRAL MICHIGAN FARMS, 19h8 - 1952 Soil Index 301 " (4.0 2.1 " 3.0 101 "' 2.0 0.0 "' 1.0 Crop <:IEield Index ‘Hheat 103 88 98 Cats 110 8b 76 Corn 118 93 8h Alfalfa 96 97 92 Average 107 91 87 (Table XVII) showed greater differences in yield between groups when calculated.using soil type alone. For'wheat (Table XXI) there were fifteen.yield index points difference between the two top soil groups and in Table XVII there are only two index points difference in yield. For soil 1.1 - 2.0 (Table XXI) the yield index was ten index points higher than that for soil groups 2.1 - 3.0. These larger differences hold true when comparing yield ins dax for soil quality and soil type index fer all crops except alfalfa. 38 Coefficient of variations (Table XXII) shows variation gener- ally increasing as soil type index goes lower, except in soil type group 0.0 - 1.0 where the number of observations was very small. TABLE XXII COEFFICIENT OF VARIATION FOR YIELD INDEX ON ‘WHEAT, OATS, CORN, ALFALFA AND THEIR AVERAGE FOR SOIL TYPE GROUPS ON THE SAMPLE OF CENTRAL MICHIGAN FARMS, 19hO - 1952 Crop Wheat Oats Corn Alfalfa h” Afirage Soil Index 3.1 "' (400 2.1 " 3.0 101 'I' 2.0 0.0 "' 1.0 Percent 23 35 21 31 30 3h 25 3O 32 A9 35 3h 39 26 28 33 38 26 When the "t" values were calculated for differences of yield using soil type only, (Table XXIII) and compared with Table XX which are "t" values for differences of yield using Soil Quality Index, it can readily be seen that there is more significant differences in yield when the index of soil type only is used. This may substantiate the fact that slope and drainage do not need to be included in the soil quality index. 39 TABLE.XXIII T VALUES FOR CROP YIELDS 0F WHEAT, OATS, CORN, ALFALFA AND THEIR AVERAGE BETWEEN SOIL TYPE GROUPS ON THE SAMPLE OF CENTRAL MICHIGAN FARMS, 19h8 - 1952 T Soil Index 3.1 "' h.0 201 "' 300 1.1 "’ 2.0 and A and and 2.1 "' 3.0 101 " 2.0 0.0 " 100 Crop t t t Wheat 3.08* 1.26 Oats h.51* 1.31 .28 com (4033* 1.18 Alfalfa "' e18 e 71 13.3% Average 6906* 1.61 2019* -— _. *Significant difference at 95 Percent level However, the principal difficulty in omitting slope and drainage was in the case of an occasional field where either of these factors may cause a definite limitation to crop production. Difference in Variation of Crop fields; for Various CrOps Within Soil Groups and Productive Practice Groups Smaller differences in yield (Table XIII) were obtained for wheat between similar practice groups for soil groups 2.1 - 3.0 and 3.1 - h.O than were obtained between these same groups for oats and corn. Alfalfa does not follow a pattern of reduction of yield which is probably due to differences in the number of cuttings taken. ho Coefficients of variation (Table XV) are generally smaller for wheat and alfalfa than are the coefficients of variation for corn and oats when compared in the same soil quality and productive practice groups. Variation about the averages for wheat and alfalfa are generally smaller than the variations about the averages for corn and oats within individual practice and soil groups. Congarison of Variation of Yield AmonLCrops Between Soil Qualijz Ajfxfiex Grpigls Smaller yield index differences are noted (Table XVII) for wheat and alfalfa than for corn and oats between index groups 2.1 - 3.0 and 3.1 - t.o. V Smaller coefficients (Table XIX) of variation are found for wheat and alfalfa in soil index group 3.1 - h.0 than is found for corn and oats. However, in soil index group 2.1 - 3.0 wheat yield variation is the smallest and alfalfa yield variation is the largest. The alfalfa yield variation again may be due to different number of cuttings. Comparison of Variation ofEYield Befleen Crops on Soil Type Sana Wheat and alfalfa yield indexes (Table XXI) show smaller dif- ferences between soil type groups than do those of corn and oats. It was noted that the yield index for wheat was higher for soil type 1.1 - 2.0 than for 2.1 - 3.0. No logical conclusion can be drawn. 11 I _._._'_ .' If I hl No definite conclusion can be drawn from the coefficients of variation (Table XXII) except that the variations between soil type groups for alfalfa yield over all the soil type groups are more uni- form than any of the other crops. An Attempt to Fit a Yield Production Surface by Multiple Linear Reggession The formula to calculate the indexes for the production surface was y = a / b2 xz ,4 by]? / bus where x a productive practices index and a : soil index. The method used for calculation was the Doolittle check sum.5 The resultant coefficients were: b2 : - 0.26592 b3 2 / 2.18U13 b1, : ,l ho.666142 a = - 29.03 and the "y" values (yield index) for various points on the surface are given in Table XXIV. This calculation was based on the actual yield data collected for this study for corn only. The formula used to calculate yield in- dex was purposely designed to Show decreasing marginal and increasing total returns to productive practices for the soils of low inherent productive capacity. For the soils of high inherent productive 5 Ezekiel, Mordecai, Methods of Correlation Anal sis Second editzgii, .1321; Wiley and Sons, EEJ,‘ REIT—Tor , TM,'—zl—8‘pp. 9 - 203 and "' e .iry. h2 l1||| mm.~I 4w.ou mm.ms mo.ms Hm.mm No.2m H:.:m no.4m m.o m.H mm.me ea.na an.sa mm.na em.eHH cm.naa an.naa «H.4HH limeO “0H Mew Mom MOO meH {Ill mew Mom HoocH deepened woosH cospomnm m.a m.m acesH nuanced anon “coca cHoHM Rana odes» ll _SSn momma maeeanoonw.onmnmmcmm mem2Hq_am omeaasoaae anzH ngmH» saauflmamae A 143 capacity it was intended that yields Show increasing total returns I and then decreasing total returns as productive practices were imp proved and increased. ComparisOn of the actual yield index data (Table XII) and yield index data calculated according to the formula used (Table XXIV) shows large discrepancies at similar soil quality and productive practice levels. The difference of yield index between the soil groups for the theoretical index was much larger than the difference between soil groups of the actual data. Also the difference in.yield due to pro- ductive practices within soil groups was smaller in the theoretical index than in the actual index. These small responses due to pro- ductive practices within soil groups was due to the lack Of‘weight given the productive practices in designing the formula. Calculation of Value of Products and Cost of Production In order to determine the most profitable level of practices to use on the soil quality groups it is necessary to calculate the value of the crops produced on these soil groups using the various levels of practices. Also the cost of producing these crops has to be known. These costs include all costs of production such as seed bed preparation, fertilizer, labor, harvesting and hauling. Taxes and interest on investment are also included in these costs. Calculation of’Returns for_hctua1 Yield.Data The value per acre of the crops grown on various soil quality groups was calculated. This was done by using the same percent of ‘ land for each crop as'was found in the study, Table XXV. The yield used fer this calculationnwas the actual yield of each crop in each productive practice group for each soil group, Table XII. A sample -calculation of the method.used is given in Table XXVI. This‘was calculated by finding the product of the yield index and average yield to give the yield for the crops. This yield was multiplied by the price per'bushel or ten to find value per acre. This value was mul- tiplied by the percent of the land used for‘this crop to give the actual value. The sum.of the actual values was found which is the total value produCt per acre. The values of the total product for TABLE XXV PERCENT OF LAND IN FIVE CROPS USED TO DETERMINE TOTAL VlLUE PRODUCT OF YIELDS FOR SAMPLESOF CENTRAL MICHIGAN FARMS, 19h5 - 19 2 ========================flI================================== Soil Quality class 000 - 1.0 101 ‘ 200 2.1 - 3.0 301 ‘ h.0 Crop Percent Corn 6 22 25 23 Cats 18 15 16 18 Wheat 8 6 16 13 Bay 31 27 19 2h Pasture 37 30 2h 22 Total 100 100 a 100 100 II UT... . a." hS «new nod ends» up cowadapflss done one as coma mo psmonomk heave wasp cw gnome huaawsa Haom manp_no sebum done we assayed Hospo¢** pass nod magma mesa» chow and onfih access mm.m: eo.m so.HH we.m pa.~ oa.oa finance osawp Hdfipo¢ «N am ma ma mm asses” Mo psoonom oo.mm 00.0; ow.oo mm.as me.mm *Amumflflonv snow use osfiw> oo.OH m.m oo.o~ m.m oo.~ a.mm om. a.am om.H H.~m . annaaaonv vac: oaofiw nod coanm HOH HOH . oaa MHH NHH Hound UHmfiH m.m m.m 4.0m «.m; o.Hm 33h omdho>4 once you osHe> fleece onspmwm awe pawns memo shoe mono mom macaw MHQZH.HBHA A4909 ho 20H94ADUHNH mnmda to the data taken are given in Table XXVII. No values are given for soil 0.5 or 1.5 because data for these indexes were not complete. TABLE XXVII ACTUAL TOTAL VALUE PRODUCTS FOR SOME POINTS OF THE SOIL QUALITY AND PRODUCTIVE PRACTICE INDEX Soil Quality 3.5 2.5 1.5 0.5 Total Value Product Per Acre Productive practice (Dollars) (Dollars) (Dollars) (Dallars) 3.5 h8.9§ h6.9h 265” h8.l9 h6.90 1.5 h7.67 h6.56 Calculation of Cost of Production of Crops In farm.planning cost of production is not only important from the standpoint of figuring returns but also is important in determin- ing future capital requirements. Estimated production cost are given in.Table XXVIII. These costs were figured only for the soil qualities and productive practice levels appearing in this Table. h? TABLE XXVIII ESTIMATED PRODUCTION COSTS* PER ACRE FOR VARIOUS POINTS OF THE SOIL QUALITY AND PRODUCTIVE PRACTICE INDEXES Soil Quality 3.5 2.5 1.5 0.5 no t ive Production Costs practice (Dollars) (Dollars) (Dollars) (Dollars) 3.5 h8.oo h2.hh 36.20 30.7u 2.5 h2.57 36.92 30.55 2h.72 1.5 36.90 30.55 2h.73 18.53 0 05 31.12 2,4072 18 e53 12.57 *Includes plowing, fitting, planting, cultivating, harvesting and hauling, seed, fertilizer, interest on investment and taxes. Costs were determined for corn, oats, wheat, hay and pasture for the same proportion as found in the study. Plowing. All costs involving machine operation were figured on a custom rate basis using information from Extension Folder 161.6 Bates varied with soil type based on soil quality index. It was assumed that the cost of plowing was greater on heavy7 soils than on light soils. 6 Very, Karl A., "Rates for Customfwork in Michigan“, 1952 and 1953, Michigan State College Cooperative Extension Service. 7 Soils containing clay. h8 Fitting. This operation consists of seed bed preparation after plowing was completed. The cost of this operation was assumed to be equal for all types of soil. §9_e_c_i_ Egg}; The seed costs were estimated for the practices indexes of 0.5 and 11.0 (Table XXIX). Costs for practices bemeen these points were interpolated, (Figure 2). These costs were cal- culated using the percent of land used for each crop in each soil quality index category. Cost for Drilling and Planting Using Different Levels of Plant Food The differences in cost for drilling and planting as plant food is increased is one mainly of increased labor. This is shown graphically in Figure 3. The cost was estimated from Extension Bulletin 1618 and cost increased as more plant food was added. Combinig or Pickinggflauling and Binning These rates were taken from Extension Bulletin 161. It was assumed that the farmers' cost was increased for harvesting, hauling and binning per acre as yield increases. The increase in the rates are shown graphically in Figure h. The rates used varied from four to five dollars for combining and one dollar to one dollar and a half for hauling and binning depending on yield. 8 Vary, Karl A., pp. 3312. h9 .moao ca used no poached one chow and pace mo suspend .cOprHsonosa .o.: a H.m mecca hpaawsv HHom :H used mo accused aes¢o«* .oofiofim 2,305.5 ae.m Hence mm. :m 00.: om.o cocoon m nmmno mm. m." m. .0 oo.m Bongo. v N amonz ma. ma om.m oo.H eaommsn m memo mm. mm ~0.H 00.0H menace m\H m egos 0.: ooapomam c>fipoeooam 11wm.m Hence om. am 00.: om.o modded w modem we. ma mm.m oo.m massage ms.H neon: om. ma oo.m oo.H maenmon w mpmo mm. mm mw.H oo.oH season 5 shoe Antwaaonv «aneflaonv anneaaonv sashes scone open access once mono nee pace as used use pmoo use use open He scooped nmoo comm wcfioomm m.o «m3 n 33 .EEH Hengec qum 0.3.: H.« 20 mOHeoaea msHaoenomm 0.: 22¢ m.o 8m seamen a: seam: .88 .560 mom $8 amen Basques NHNN_MAmHpHso so. mN.H am H useHm new HHHHQ m4.m om.: am M van 0H.“ 00.: am H seHm AmanHonv AmamHHonv «anon sashes somampoo ocwH msowewnodo Hespo< nod pmoo no scooped no noeesz m.o “HQZH QQHBodmm m>HHoDnOmm 32¢ m.m MHQZH HBHH