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Frontiers of Agricultural Science and Engineering

ISSN 2095-7505

ISSN 2095-977X(Online)

CN 10-1204/S

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Front. Agr. Sci. Eng.    2023, Vol. 10 Issue (1) : 31-47    https://doi.org/10.15302/J-FASE-2023482
RESEARCH ARTICLE
IMPACTS OF TECHNICAL ENVIRONMENT ON THE ADOPTION OF ORGANIC FERTILIZERS AND BIOPESTICIDES AMONG FARMERS: EVIDENCE FROM HEILONGJIANG PROVINCE, CHINA
Haoyue YANG1, Ting MENG1(), Wojciech J. FLORKOWSKI2
1. Academy of Global Food Economics and Policy (AGFEP); Beijing Food Safety and Strategy Research Base; College of Economics and Management, China Agricultural University, Beijing 100083, China
2. Department of Agricultural Economics, University of Georgia, Griffin, GA 30223, USA
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Abstract

● Farmer adoption of organic fertilizer and biopesticides was found to be positively correlated.

● The technical environment had a significant positive impact on farmers’ adoption of organic fertilizers and biopesticides.

● Technology training and local accessibility to new agricultural technologies enhanced both the adoption of organic fertilizers and biopesticides.

● Exchanging information about production techniques with others generally increased the likelihood of adopting organic fertilizers by 6%.

Excessive application of mineral fertilizers and synthetic pesticides poses a substantial threat to the soil and water environment and food security. Organic fertilizer and biopesticides have gradually become essential technology for reducing mineral fertilizer and pesticide inputs. In the process, the technical environment is critical for promoting farmer behavior related to the adoption of organic fertilizer and biopesticides. This paper analyzes the influence of the technical environment on farmer behavior related to the adoption of organic fertilizer and biopesticides based on a survey of 1282 farmers in Heilongjiang Province, China, using the bivariate probit model. The results indicate that (1) farmer behavior related to the adoption applying organic fertilizer and biopesticides were positively correlated; (2) the technical environment had a significant positive impact on farmer behavior related to the adoption of organic fertilizer and biopesticides; and (3) the technical environment had a heterogeneous effect across different groups of farmers. This research provides insights useful for promoting organic fertilizer and biopesticides to farmers. It can be helpful to bundle relevant environmental technologies, conduct technology training for farmers and strengthen the construction of rural information networks.
Keywords biopesticides      green production      organic fertilizer      technical environment     
Corresponding Author(s): Ting MENG   
Just Accepted Date: 10 February 2023   Online First Date: 13 March 2023    Issue Date: 03 April 2023
 Cite this article:   
Haoyue YANG,Ting MENG,Wojciech J. FLORKOWSKI. IMPACTS OF TECHNICAL ENVIRONMENT ON THE ADOPTION OF ORGANIC FERTILIZERS AND BIOPESTICIDES AMONG FARMERS: EVIDENCE FROM HEILONGJIANG PROVINCE, CHINA[J]. Front. Agr. Sci. Eng. , 2023, 10(1): 31-47.
 URL:  
https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2023482
https://academic.hep.com.cn/fase/EN/Y2023/V10/I1/31
Fig.1  Agricultural technology adoption behavior.
Fig.2  Mechanisms of technical environment influence on farmer adoption of technology.
Variable typeVariable nameDefinitionMeanSt. Dev
Dependent variablesOrganic fertilizerDo you use organic fertilizer in your actual production: Yes = 1, No = 00.2720.445
BiopesticidesDo you use biopesticides in your actual production; Yes = 1, No = 00.1210.326
Technical environment
Policy environmentTrainingHousehold members have been trained in agricultural technology; Yes = 1, No = 00.3000.458
InformationnetworkCooperativesDoes your family participate in professional farmer cooperatives; Yes = 1, No = 00.2080.406
AccessibilityLocal accessibility to new agricultural technologies; Yes = 1, No = 00.4720.499
ExchangeRegularly exchange information about production techniques with others; Yes = 1, No = 00.8100.392
Control variables
FarmlandPlanting areaBased on the actual area of cultivated land operated (ha)14.2838.57
Number of plotsActual number of operated plots (block)6.7266.532
Land qualityLow = 1, lower = 2, medium = 3, higher = 4, high = 53.230.815
WorkforceLaborersNumber of persons2.0770.722
AgeIn years48.44510.735
EducationIn years7.9232.607
Intrinsic cognitiveSoil degradation perceptionHow do you view the current soil degradation problem: soil is not degrading = 1, degradation is not serious = 2, degradation is somewhat serious = 3, degradation is serious = 4, degradation is very serious = 52.8781.156
Land protection perceptionIs it necessary to protect farm land: not at all necessary = 1, not necessary = 2, necessary = 3, very necessary = 4, extremely necessary = 53.3671.076
Environmental improvement perceptionCereal-bean rotation useful in improving farm land quality and reduced pesticide and fertilizer input use: not at all useful = 1, not useful = 2, useful = 3, very useful = 4, exceptionally useful = 53.431.006
Family characteristicsFamily income in 201710,000–30,000 yuan = 1, otherwise = 00.2300.422
30,001–50,000 yuan = 1, otherwise = 00.2180.413
50,001–100,000 yuan = 1, otherwise = 00.2110.408
100,001 or more yuan = 1, otherwise = 00.2520.434
Share of agricultural incomePercentage of total household income from agriculture; 90% or more = 1, otherwise = 00.7190.450
Share of total household income from agriculture; 50%–90% = 1, other = 00.2070.406
Number of family membersActual number of family members (persons)3.5061.223
Householder characteristicsVillage leadership statusHousehold head currently a village leader; Yes = 1, No = 00.1560.363
Years of farmingActual years of farming by the household head (years)29.77610.785
Tab.1  Definitions and descriptive statistics of variables related to organic fertilizer and biopesticide adoption
AdoptionTechnical training Cooperative Technology access Technical exchange
AttendedNever attended AttendedNever attended EasyNot easy FrequentlyInfrequently
Org. fertilizer (%)38.822.3 35.625.0 34.920.4 30.015.2
Biopesticide (%)18.59.4 17.210.7 16.08.6 13.08.2
Tab.2  Adoption of organic fertilizer and biopesticides in different technical environments
ItemOrganic fertilizer Biopesticides
CoefficientStd. Err.Marginal effects CoefficientStd. Err.Marginal effects
Technical environment
Training0.209**0.0960.025 0.270**0.1100.013
Cooperatives0.0750.1000.008 0.1000.1140.005
Accessibility0.248***0.0850.034 0.277***0.1000.012
Exchange0.265**0.1160.062 0.0450.133?0.009
Control variables
Area0.019*0.0100.004 0.0110.0070.000
Plots0.0010.0060.001 ?0.0030.006?0.000
Land quality0.0560.0480.006 0.0800.0600.004
Laborers?0.0970.061?0.032 0.0690.0730.010
Age?0.0000.007?0.001 0.0040.0070.000
Education0.043**0.0180.010 0.0110.022?0.001
Soil degradation perception?0.0100.037?0.002 ?0.0070.043?0.000
Land protection perception0.096**0.0440.024 0.0010.051?0.005
Environmental improvement perception0.0540.0440.005 0.0850.0510.005
Income (× 103 yuan)
10–300.2780.1760.041 0.2060.2000.007
30–500.425**0.1760.084 0.1210.211?0.007
50–1000.692***0.1760.138 0.3060.210?0.005
> 1000.584***0.1760.107 0.3030.211?0.001
Share of ≥ 90% agricultural income 50%–90%0.1530.0970.047 ?0.0610.116?0.012
?0.0090.1500.040 ?0.468**0.213?0.029
No. of family members?0.0150.034?0.002 ?0.0210.037?0.001
Leadership?0.202*0.114?0.029 ?0.2160.138?0.009
Years of farming?0.0030.0050.000 ?0.0030.006?0.000
Constant?2.200*** ?2.416***
Observations1282
ρ0.589***
Wald test of ρ = 0chi2(1) = 97.4, Prob > chi2 = 0.00
Tab.3  Bivariate probit model regression results of decision to adopt organic fertilizer and biopesticides
ItemSmall-scale farmers Large-scale farmers
Organic fertilizer BiopesticidesOrganic fertilizer Biopesticides
Coef.Marginal effectsCoef.Marginal effectsCoef.Marginal effectsCoef.Marginal effects
Technical environment
Training0.1860.011 0.309**0.018 0.287**0.049 0.283*0.010
Cooperatives?0.030?0.0210.1570.0150.1500.0210.1820.008
Accessibility0.272**0.0340.257*0.0090.237**0.0310.309**0.014
Exchange0.432***0.0620.321*0.0070.1010.059?0.266?0.027
Control variableYESYESYESYES
Prob > chi2 = 0.00, ρ = 0.715***Prob > chi2 = 0.00, ρ = 0.490***
Tab.4  Regression model results for households with different farming scales
ItemFarmers with high agriculture income share Farmers with low agriculture income share
Organic fertilizer BiopesticidesOrganic fertilizer Biopesticides
Coef.Marginal effectCoef.Marginal effectCoef.Marginal effectCoef.Marginal effect
Technical environment
Training0.320*0.012 0.668***0.023 0.1710.027 0.1370.005
Cooperatives0.1830.0430.046?0.0030.037?0.0060.1470.012
Accessibility0.473***0.0820.393*0.0050.199*0.0230.252**0.014
Exchange0.542**0.151?0.081?0.0200.242*0.0420.1610.003
Control variableYESYESYESYES
Prob > chi2 = 0.00, ρ = 0.716***Prob > chi2 = 0.00, ρ = 0.542***
Tab.5  Regression model results for households with different dependence on farm income measured by farm income share
ItemOrganic fertilizer Biopesticides
Coef.Std. Err.Marginal effects Coef.Std. Err.Marginal effects
Technical environent
Training0.215**?2.2600.065 0.279**?2.5100.053
Cooperatives0.072?0.7200.0220.096?0.8400.018
Accessibility0.249***?2.9400.0750.262***?2.5900.050
Exchange0.261**?2.2700.0790.048?0.3600.009
Control variable
Area0.019*?1.7900.0060.011?1.5300.002
Plots0.001?0.2200.000?0.004?0.600?0.001
Land quality0.050?1.0300.0150.071?1.2100.014
Laborers?0.093?1.520?0.0280.064?0.8900.012
Age0.000?0.0200.0000.005?0.7100.001
Education0.042**?2.2900.0130.013?0.5700.002
Soil degradation perception?0.006?0.170?0.0020.005?0.1100.001
Land protection perception0.097**?2.1800.029?0.003?0.060?0.001
Environmental improvement perception0.050?1.1400.0150.071?1.3500.014
Income (× 103 yuan)
10–300.302*?1.7000.0740.238?1.1800.040
30–500.433**?2.4200.1120.142?0.6700.022
50–1000.702***?3.9200.1990.304?1.4400.053
> 1000.598***?3.3400.1640.333?1.5700.059
Share of ≥ 90% agricultural income 50%?90%0.155?1.6000.048?0.038?0.330?0.007
0.0000.0000.000?0.437**?2.060?0.067
No. of family members?0.014?0.400?0.004?0.022?0.570?0.004
Leadership?0.203*?1.770?0.061?0.202?1.440?0.039
Years of farming?0.003?0.570?0.001?0.003?0.520?0.001
Constant?2.221***?2.447***
Wald chi2125.37***55.30***
Prob > chi20.00 0.00
Tab.6  Robustness test
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