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Abstract The total output value of mutton in Northwestern China has accounted for more than 60% of the total output value of animal husbandry over the years. It can be seen that the mutton industry in Northwest China not only plays a pivotal role in animal husbandry， but also plays an important role in Chinese agriculture. In this study， based on cost accounting theory， income-related theories and total factor productivity theory， using basic knowledge of statistics and economics， drawing on existing research results at home and abroad， and adopting a combination of qualitative analysis and quantitative analysis of SAS multiple stepwise regression， the changing trends of cost-benefit of mutton sheep breeding in Northwest agricultural and pastoral areas and influencing factors of production costs and production efficiency were investigated， aiming to provide reference for saving mutton sheep feeding material resources， reducing mutton sheep breeding costs， and improving mutton sheep breeding benefits.
Key words Lamb costs and benefits; Stepwise regression; Guizhou black goats; Selection and breeding thinking
Received： February 23， 2021 Accepted： May 3， 2021
Supported by Guizhou Agricultural Research Project （QKH[2019]2279）; Construction of Guizhou Breeding Livestock and Poultry Genetic Resources Testing Platform （QKZYD[2018]4015）; Scientific and Technological Innovation Talent Team of Major Livestock and Poultry Genome Big Data Analysis and Application Research in Guizhou Province （QKHPTRC[2019]5615）.
Qingmeng LONG （1973-）， female， P. R. China， senior veterinarian， master， devoted to research about livestock and poultry breeding management， disease prevention and control， molecular breeding， genetic resource collection， production preservation and development and utilization.
*Corresponding author. E-mail： [email protected].
The development of animal husbandry plays an important role in the realization of agricultural industrialization and the acceleration of the increase of farmers’ income in China. The seven provinces and cities in Northwest China are China’s five major pastoral areas， and they are also major beef and mutton producing provinces. However， since 2006， due to the decline in sheep stocks in Northwest China， the decline in mutton sheep production and the decrease in market supply， the price of mutton has been rising. However， problems such as high cost， low benefit， high risk， and contradiction between livestock and grass have become the main reasons for many farmers to withdraw from the breeding industry. The breeding industry faces the grim reality of slow growth of farmers’ income and low efficiency of livestock production[1]. Qingmeng LONG et al. Thinking on Breeding of Fecundity Genes in Guizhou Black Goats Through Cost-benefit Analysis of Mutton Sheep by SAS Multivariate Stepwise Regression
Table 1 Mutton production cost and profit list in 2017-2018
CityQuantity ofconcentratedfeed∥kgDepreciation offixed assetsper sheep （orone hundredsheep）∥yuanLabor priceper sheep （orone hundredsheep）∥yuanIndirect costper sheep （orone hundredsheep）∥yuanFee for greenand coarsefodder per sheep（or one hundredsheep）∥yuanWater feeper sheep（or onehundredsheep）∥yuanWater feeper sheep （orone hundredsheep）yuanFeed processingfee per sheep（or onehundredsheep）∥yuanMain productoutput persheep （orone hundredsheep）∥kgCost-profitratio persheep （orone hundredsheep）∥%Net profitper sheep（or onehundredsheep）∥yuan
Stepwise Regression Analysis
Matrix generation
The mutton production cost factors （11 factors） such as the quantity of concentrated feed were respectively represented by a matrix （x x x3， x4…x11）， where x1 represents quantity of concentrated feed and x2 represents depreciation of fixed assets per sheep （or one hundred sheep）， …x11 represents net profit per sheep （or one hundred sheep）.
Drawing
① Line charts were drawn to observe the changing trend of each production factor. In order to keep the data of each production factor at a uniform level， part of the data were converted， such as dividing labor price per sheep （or one hundred sheep） by 10， and dividing the net profit per sheep （or one hundred sheep） by 100， and then charts were drawn， as shown in Fig. 2. ② Pie charts were also drawn to observe national average proportions of mutton production factors， as shown in Fig. 3 and Fig 4.
It can be seen from Table 1 and Fig. 2 that the changing trends of concentrate cost， fee for green and coarse fodder and labor cost for raising a mutton sheep in the agricultural areas of the 7 provinces were consistent with the changing trends of the consumption of various expense items， indicating that the consumption of each expense item had a greater impact on the production cost than the price of each expense item， and the prices of various expense items or labor cost were on the increase.
Results and Analysis
The program ran for seven steps， at each of which was gradually introduced a variable， and the model was continuously optimized， striving to achieve the significance of each variable introduced. In step 3， x1 was introduced， but it was removed in step 6， indicating that x1 （the amount of concentrate） was not the optimal variable. During the seven-step operation， the F value was constantly adjusted. For example， the F value of x8 （feed processing fee per sheep （or one hundred sheep）） was 20.19 in the second step， and the final optimization result was 72.17. The running results are shown in Table 2. Model building
The predicted values of the independent variables are shown in Table 3. It can be seen that the regression relationship between the dependent variable mutton production cost and profit y and various production factor was：
YMutton production cost and profit=-4.38 X2（Depreciation offixed assets per sheep （or onehundred sheep））+1.90 X4（Indirect cost per sheep （or one hundred sheep））-0.23 X5（Fee forgreen and coarse fodder per sheep （or one hundred sheep））+5.28 X8 （Feed processing fee per sheep（or one hundred sheep））+11.52 X10 （Cost-profit ratio per sheep （or one hundred sheep））
It can be seen from the regression equation that the coefficients of x x8 and x10 were relatively large， indicating that the production factors in the mutton production process， such as depreciation of fixed assets per sheep （or one hundred sheep）， feed processing fee per sheep （or one hundred sheep） and cost-profit ratio per sheep （or one hundred sheep） had greater impacts on the profit of mutton. It can be seen from Table 1 that for production efficiency of mutton sheep breeding in Heilongjiang and Hebei pastoral areas， the mutton price， material and service costs and labor cost per one or one hundred sheep， had greater impacts on the net profit of mutton per sheep or one hundred sheep than the consumption of material and service costs of mutton per sheep or one hundred sheep. The increase in the net profit due to the increase in the price of material and service costs was greater than the increase due to the increase in the consumption of mutton material and services.
proc stepwise;
model y=x1-x10;
run;
Table 2 Summary table of stepwise regression results
Analysis stepIntroduced variableF valuePr>FConclusionNote
Step1x10 （Cost-profit ratio per sheep （or one hundred sheep））343.16<0.001Extremely significantAs shown in Fig. 5
Step2x8 （Feed processing fee per sheep （or one hundred sheep））20.190.006Extremely significantAs shown in Fig. 6
Step3x1 （Quantity of concentrated feed）6.490.025 6SignificantAs shown in Fig. 7
Step4x4 （Indirect cost per sheep （or one hundred sheep））9.570.010 2SignificantAs shown in Fig. 8
Step5x2 （Depreciation of fixed assets per sheep （or one hundred sheep））4.560.058 5SignificantAs shown in Fig. 9
Step6Remove x1---As shown in Fig. 10
Step7x5 （Fee for green and coarse fodder per sheep （or one hundred sheep））4.270.065 7SignificantAs shown in Fig. 11 Total resultsx2 （Depreciation of fixed assets per sheep （or one hundred sheep） （yuan））31.090.000 2Extremely significantAs shown in Fig. 12
x4 （Indirect cost per sheep （or one hundred sheep））28.380.000 3Extremely significant
x5 （Fee for green and coarse fodder per sheep （or one hundred sheep））4.270.065 7Significant
x8 （Feed processing fee per sheep （or one hundred sheep））72.17<0.000 1Extremely significant
x10 （Cost-profit ratio per sheep （or one hundred sheep））2 495.86<0.000 1Extremely significant
Significance level of stepwise regression： α=0.15.
The exploration and breeding of fecundity genes in Guizhou black goats requires a certain population， while the breeding of Guizhou black goats suffers from problems such as high cost， low benefit， high risk， conflicts between livestock and grass， and severe practical impacts of slow growth and low production efficiency of livestock products， leading to insufficient populations for the exploration and breeding of fecundity genes in Guizhou black goats. Therefore， systematically and comprehensively understanding the production factors of mutton and analyzing the in-depth influencing factors that affect the total cost and net profit of mutton can provide theoretical guidance for the breeding of Guizhou black goats， and provide breeding populations for the exploration and breeding of fecundity genes in Guizhou black goats. Furthermore， it can provide a scientific basis for Guizhou Province to consolidate the results of poverty alleviation and vigorously develop the mountain ecological mutton sheep industry and for Guizhou mutton sheep breeding enterprises to improve the effective breeding cost and economic benefit estimates， and has important guiding significance to promotion of rural revitalization.
References
[1] HUANG YL. Analysis of benefits and costs of Xinjiang meat[D]. Urumchi： Xinjiang Agricultural University， 2014. （in Chinese）
[2] PENG H， DU H， RAN XQ， et al. Study on molecular detection technology of polled intersex syndrome loci in Guizhou black goats[J]. Heilongjiang Animal Science and Veterinary Medicine， 2020， （21）： 87-91. （in Chinese）
[3] LI LJ， ZHOU DR， HUANG YZ， et al. Estimation of genetic parameters of growth traits in Guizhou black goats by different animal models[J]. Heilongjiang Animal Science and Veterinary Medicine， 2020， （17）： 61-64， 68. （in Chinese）
[4] ZHENG ZG， XU J. Examples of regression analysis （5th edition）[M]. Beijing： China Machine Press， 2013. （in Chinese）
[5] HE XQ， LIU WQ. Application of regression analysis[M]. Beijing： China Renmin University Press， 2015. （in Chinese）
[6] CONG HP. Sports statistics （3rd edition）[M]. Beijing： Higher Education Press， 2018. （in Chinese）
[7] BUREAU OF STATISTICS. National agricultural product cost-benefit data compilation[M]. 2020. （in Chinese）
Key words Lamb costs and benefits; Stepwise regression; Guizhou black goats; Selection and breeding thinking
Received： February 23， 2021 Accepted： May 3， 2021
Supported by Guizhou Agricultural Research Project （QKH[2019]2279）; Construction of Guizhou Breeding Livestock and Poultry Genetic Resources Testing Platform （QKZYD[2018]4015）; Scientific and Technological Innovation Talent Team of Major Livestock and Poultry Genome Big Data Analysis and Application Research in Guizhou Province （QKHPTRC[2019]5615）.
Qingmeng LONG （1973-）， female， P. R. China， senior veterinarian， master， devoted to research about livestock and poultry breeding management， disease prevention and control， molecular breeding， genetic resource collection， production preservation and development and utilization.
*Corresponding author. E-mail： [email protected].
The development of animal husbandry plays an important role in the realization of agricultural industrialization and the acceleration of the increase of farmers’ income in China. The seven provinces and cities in Northwest China are China’s five major pastoral areas， and they are also major beef and mutton producing provinces. However， since 2006， due to the decline in sheep stocks in Northwest China， the decline in mutton sheep production and the decrease in market supply， the price of mutton has been rising. However， problems such as high cost， low benefit， high risk， and contradiction between livestock and grass have become the main reasons for many farmers to withdraw from the breeding industry. The breeding industry faces the grim reality of slow growth of farmers’ income and low efficiency of livestock production[1]. Qingmeng LONG et al. Thinking on Breeding of Fecundity Genes in Guizhou Black Goats Through Cost-benefit Analysis of Mutton Sheep by SAS Multivariate Stepwise Regression
Table 1 Mutton production cost and profit list in 2017-2018
CityQuantity ofconcentratedfeed∥kgDepreciation offixed assetsper sheep （orone hundredsheep）∥yuanLabor priceper sheep （orone hundredsheep）∥yuanIndirect costper sheep （orone hundredsheep）∥yuanFee for greenand coarsefodder per sheep（or one hundredsheep）∥yuanWater feeper sheep（or onehundredsheep）∥yuanWater feeper sheep （orone hundredsheep）yuanFeed processingfee per sheep（or onehundredsheep）∥yuanMain productoutput persheep （orone hundredsheep）∥kgCost-profitratio persheep （orone hundredsheep）∥%Net profitper sheep（or onehundredsheep）∥yuan
Stepwise Regression Analysis
Matrix generation
The mutton production cost factors （11 factors） such as the quantity of concentrated feed were respectively represented by a matrix （x x x3， x4…x11）， where x1 represents quantity of concentrated feed and x2 represents depreciation of fixed assets per sheep （or one hundred sheep）， …x11 represents net profit per sheep （or one hundred sheep）.
Drawing
① Line charts were drawn to observe the changing trend of each production factor. In order to keep the data of each production factor at a uniform level， part of the data were converted， such as dividing labor price per sheep （or one hundred sheep） by 10， and dividing the net profit per sheep （or one hundred sheep） by 100， and then charts were drawn， as shown in Fig. 2. ② Pie charts were also drawn to observe national average proportions of mutton production factors， as shown in Fig. 3 and Fig 4.
It can be seen from Table 1 and Fig. 2 that the changing trends of concentrate cost， fee for green and coarse fodder and labor cost for raising a mutton sheep in the agricultural areas of the 7 provinces were consistent with the changing trends of the consumption of various expense items， indicating that the consumption of each expense item had a greater impact on the production cost than the price of each expense item， and the prices of various expense items or labor cost were on the increase.
Results and Analysis
The program ran for seven steps， at each of which was gradually introduced a variable， and the model was continuously optimized， striving to achieve the significance of each variable introduced. In step 3， x1 was introduced， but it was removed in step 6， indicating that x1 （the amount of concentrate） was not the optimal variable. During the seven-step operation， the F value was constantly adjusted. For example， the F value of x8 （feed processing fee per sheep （or one hundred sheep）） was 20.19 in the second step， and the final optimization result was 72.17. The running results are shown in Table 2. Model building
The predicted values of the independent variables are shown in Table 3. It can be seen that the regression relationship between the dependent variable mutton production cost and profit y and various production factor was：
YMutton production cost and profit=-4.38 X2（Depreciation offixed assets per sheep （or onehundred sheep））+1.90 X4（Indirect cost per sheep （or one hundred sheep））-0.23 X5（Fee forgreen and coarse fodder per sheep （or one hundred sheep））+5.28 X8 （Feed processing fee per sheep（or one hundred sheep））+11.52 X10 （Cost-profit ratio per sheep （or one hundred sheep））
It can be seen from the regression equation that the coefficients of x x8 and x10 were relatively large， indicating that the production factors in the mutton production process， such as depreciation of fixed assets per sheep （or one hundred sheep）， feed processing fee per sheep （or one hundred sheep） and cost-profit ratio per sheep （or one hundred sheep） had greater impacts on the profit of mutton. It can be seen from Table 1 that for production efficiency of mutton sheep breeding in Heilongjiang and Hebei pastoral areas， the mutton price， material and service costs and labor cost per one or one hundred sheep， had greater impacts on the net profit of mutton per sheep or one hundred sheep than the consumption of material and service costs of mutton per sheep or one hundred sheep. The increase in the net profit due to the increase in the price of material and service costs was greater than the increase due to the increase in the consumption of mutton material and services.
proc stepwise;
model y=x1-x10;
run;
Table 2 Summary table of stepwise regression results
Analysis stepIntroduced variableF valuePr>FConclusionNote
Step1x10 （Cost-profit ratio per sheep （or one hundred sheep））343.16<0.001Extremely significantAs shown in Fig. 5
Step2x8 （Feed processing fee per sheep （or one hundred sheep））20.190.006Extremely significantAs shown in Fig. 6
Step3x1 （Quantity of concentrated feed）6.490.025 6SignificantAs shown in Fig. 7
Step4x4 （Indirect cost per sheep （or one hundred sheep））9.570.010 2SignificantAs shown in Fig. 8
Step5x2 （Depreciation of fixed assets per sheep （or one hundred sheep））4.560.058 5SignificantAs shown in Fig. 9
Step6Remove x1---As shown in Fig. 10
Step7x5 （Fee for green and coarse fodder per sheep （or one hundred sheep））4.270.065 7SignificantAs shown in Fig. 11 Total resultsx2 （Depreciation of fixed assets per sheep （or one hundred sheep） （yuan））31.090.000 2Extremely significantAs shown in Fig. 12
x4 （Indirect cost per sheep （or one hundred sheep））28.380.000 3Extremely significant
x5 （Fee for green and coarse fodder per sheep （or one hundred sheep））4.270.065 7Significant
x8 （Feed processing fee per sheep （or one hundred sheep））72.17<0.000 1Extremely significant
x10 （Cost-profit ratio per sheep （or one hundred sheep））2 495.86<0.000 1Extremely significant
Significance level of stepwise regression： α=0.15.
The exploration and breeding of fecundity genes in Guizhou black goats requires a certain population， while the breeding of Guizhou black goats suffers from problems such as high cost， low benefit， high risk， conflicts between livestock and grass， and severe practical impacts of slow growth and low production efficiency of livestock products， leading to insufficient populations for the exploration and breeding of fecundity genes in Guizhou black goats. Therefore， systematically and comprehensively understanding the production factors of mutton and analyzing the in-depth influencing factors that affect the total cost and net profit of mutton can provide theoretical guidance for the breeding of Guizhou black goats， and provide breeding populations for the exploration and breeding of fecundity genes in Guizhou black goats. Furthermore， it can provide a scientific basis for Guizhou Province to consolidate the results of poverty alleviation and vigorously develop the mountain ecological mutton sheep industry and for Guizhou mutton sheep breeding enterprises to improve the effective breeding cost and economic benefit estimates， and has important guiding significance to promotion of rural revitalization.
References
[1] HUANG YL. Analysis of benefits and costs of Xinjiang meat[D]. Urumchi： Xinjiang Agricultural University， 2014. （in Chinese）
[2] PENG H， DU H， RAN XQ， et al. Study on molecular detection technology of polled intersex syndrome loci in Guizhou black goats[J]. Heilongjiang Animal Science and Veterinary Medicine， 2020， （21）： 87-91. （in Chinese）
[3] LI LJ， ZHOU DR， HUANG YZ， et al. Estimation of genetic parameters of growth traits in Guizhou black goats by different animal models[J]. Heilongjiang Animal Science and Veterinary Medicine， 2020， （17）： 61-64， 68. （in Chinese）
[4] ZHENG ZG， XU J. Examples of regression analysis （5th edition）[M]. Beijing： China Machine Press， 2013. （in Chinese）
[5] HE XQ， LIU WQ. Application of regression analysis[M]. Beijing： China Renmin University Press， 2015. （in Chinese）
[6] CONG HP. Sports statistics （3rd edition）[M]. Beijing： Higher Education Press， 2018. （in Chinese）
[7] BUREAU OF STATISTICS. National agricultural product cost-benefit data compilation[M]. 2020. （in Chinese）