Farm-level Data Research Articles

Managing nitrogen environmental impacts to improve green technical efficiency in Philippines rice cultivation

The efficient use of nitrogen fertilisers is a global priority to optimise the economic and environmental outcomes of farming. This paper is the first to consider pollution in the form of nitrous oxide emissions and excess nitrogen to analyse technical efficiency (TE) in farming. This is done by extending the two-stage double bootstrap Data Envelopment Analysis to explicitly model nitrogen pollutants as undesirable outputs. We compared green TE (when undesirable pollutants are considered) and conventional TE (without pollutants) using a case study of 33 rice-producing provinces in the Philippines. Provinces in Mindanao, Luzon, and Visayas islands experienced improvements in green TE but stagnant conventional TE from 2006 to 2017. Although transplanting rice seedlings (rather than direct sowing of seeds) improved both green and conventional TE, seed quality was also identified as an important factor for green TE but not for conventional TE. Our analysis has implications for sustainable rice production and such analysis can be extended to other crops. To advance the effective green transformation of rice production, future research should analyse farm-level data to understand farmers’ decisions regarding seed quality, crop establishment method and nitrogen fertiliser application to devise comprehensive farm integrated management plans.

Farm Advisory Services and total factor productivity growth in the Irish dairy sector

AbstractThis paper investigates the impact of the engagement of individual farmers with Farm Advisory Services (FAS) on total factor productivity (TFP) growth, as a relevant indicator of competitiveness under the vision of sustainable intensification. Using farm-level data from the Irish dairy sector between 2008 and 2017, we estimate a random-coefficients stochastic frontier model and construct a TFP growth index, extending Orea (2002) such that the contribution of FAS becomes an additional component of the index. The results indicate that the main driver of TFP growth was technical change and efficiency gains; a negative scale effect slowed down TFP growth, but this impact was counteracted by the positive contribution of FAS to productivity growth.

Climate-smart agriculture: Greenhouse gas mitigation in climate-smart villages of Ghana

Climate-smart agriculture (CSA) is an approach that helps guide actions to transform agri-food systems towards green and climate-resilient practices and it remains prominent in food systems transformation in the light of increasing climate change impacts. Unfortunately, the quantification of the greenhouse gas (GHG) mitigation potential of CSA approaches is currently limited. Using the Cool Farm Tool (CFT), this paper quantifies the GHG mitigation of CSA based on farm-level experimental data. Individual interviews and focus group discussions were also conducted to identify farmers’ choices and willingness to adopt CSA practices. The study compared the GHG emission mitigation of CSA practices for two scenarios (baseline and mitigation). The study found that organic fertilizer input, residue incorporation, no-inorganic fertilizer and no-pesticide input reduced GHG emission intensity of sorghum (to 93.2 ± 25 kg CO2e GHG kg− 1 sorghum), rice (79.2 ± 22 kg CO2e GHG kg− 1 rice) and groundnut (69.7 ± 20 kg CO2e GHG kg− 1 groundnut) compared to the baseline. Lower GHG emission intensity was achieved with higher crop yield under CSA interventions. The study recommends that CSA promoters such as the Consultative Group for International Agriculture Research (CGIAR), Food and Agriculture Organization (FAO) and the World Bank focus on crop-specific CSA practices for higher GHG mitigation. CSA promoters such as the CGIAR, FAO and the World Bank should embrace participatory processes such as farmer schools to increase CSA uptake.

The Effects of Agricultural Socialized Services on Sustainable Agricultural Practice Adoption among Smallholder Farmers in China

In recent years, a growing body of literature has explored the determinants and impacts of sustainable agricultural technologies. However, little is known about the relationship between agricultural socialized services that have reshaped the smallholder agricultural system and promoted scale operation in rural China and environmentally friendly agricultural innovation adoption of the farm. Our study examines the effects of agricultural socialized services on the adoption of sustainable agricultural practices (SAPs). In this study, we capture the number of SAPs adopted, unlike most existing studies that analyze the dichotomous decision of agricultural technology adoption. We apply an endogenous-treatment Poisson regression model to analyze using a national representative farm-level survey data set with 1357 farm households from 132 villages in China. The results show that socialized service use has a significantly positive effect on the number of SAPs adopted. Our results suggest that agricultural socialized services can promote the adoption of sustainable agricultural technologies among smallholders, and thus help transform conventional agriculture into sustainable agriculture.

Exploring the Impact of Farmer Field Schools on the Adoption of Sustainable Agricultural Practices and Farm Production: A Case of Pakistani Citrus Growers

In the wake of recent climate changes, extension services have become crucial drivers in disseminating information about the latest agriculture technologies and facilitating sustainable agricultural productivity. Pakistan’s traditional extension cannot yield the expected outcomes which corroborate the introduction of a participatory approach, mainly in farmers’ field schools. Using farm-level data from Punjab province, the current study examined the impact of farmers’ field schools (FFS) on adopting sustainable agriculture practices (SAPs) and citrus yield. The study employed recursive bivariate probit and propensity score matching to explore the objectives. The findings revealed that FFS participants had a higher SAPs adoption than non-participants, demonstrating the positive impact of FFS on the uptake of SAPs. Moreover, the treatment effect showed that FFS participants had a higher yield than the non-participants. The results suggest strengthening and enhancing FFS reach among citrus growers.

Associations between antimicrobial resistance in fecal Escherichia coli isolates and antimicrobial use in Canadian turkey flocks.

Antimicrobial resistance (AMR) in enteric bacteria continues to be detected in turkey flocks and retail products worldwide, including in Canada. However, studies assessing linkages between on-farm antimicrobial use (AMU) and the development of AMR are lacking. This study aims to identify AMU characteristics that impact the development of AMR in the indicator bacteria Escherichia coli in turkey flocks, building on the Canadian Integrated Program for Antimicrobial Resistance Surveillance methodology for farm-level AMU and AMR data integration. Two analytic approaches were used: (1) multivariable mixed-effects logistic regression models examined associations between AMU (any route, route-specific, and route-disease-specific indication) summarized as the number of defined daily doses in animals using Canadian standards ([nDDDvetCA]/1,000 kg-animal-days at risk) and AMR and (2) multivariable mixed-effects Poisson regression models studied the linkages between AMU and the number of classes to which an E. coli isolate was resistant (nCRE. coli). A total of 1,317 E. coli isolates from a network of 16 veterinarians and 334 turkey producers across the five major turkey-producing provinces in Canada between 2016 and 2019 were used. Analysis indicated that AMR emerged with the use of related antimicrobials (e.g., tetracycline use-tetracycline resistance), however, the use of unrelated antimicrobial classes was also impacting AMR (e.g., aminoglycosides/streptogramins use-tetracycline resistance). As for studying AMU-nCRE. coli linkages, the most robust association was between the parenteral aminoglycosides use and nCRE. coli, though in-feed uses of four unrelated classes (bacitracin, folate pathway inhibitors, streptogramins, and tetracyclines) appear to be important, indicating that ongoing uses of these classes may slow down the succession from multidrug-resistant to a more susceptible E. coli populations. The analysis of AMU (route and disease-specific)-AMR linkages complemented the above findings, suggesting that treatment of certain diseases (enteric, late-stage septicemic conditions, and colibacillosis) are influential in the development of resistance to certain antimicrobial classes. The highest variances were at the flock level indicating that stewardship actions should focus on flock-level infection prevention practices. This study added new insights to our understanding of AMU-AMR linkages in turkeys and is useful in informing AMU stewardship in the turkey sector. Enhanced surveillance using sequencing technologies are warranted to explain molecular-level determinants of AMR.

Developing production and financial benchmarks for marine aquaculture from farm data

Benchmarking programs for crop and livestock farms have been used by farmers to identify ways to improve farm efficiencies. This study developed a set of benchmarks for oyster, mussel, and seaweed farming in Maine (USA). Farm-level survey data were used to calculate benchmarking metrics for each farm respondent. Results showed the importance of disaggregating benchmarking metrics by production scale, gear type, and whether farms were initial startup (defined in this study as <5 years in business) or established (>5 years in business) farms. The initial analysis of cost structures on individual farms provided useful information from which to identify key categories for disaggregation. Identification of the most important cost inputs further points to which benchmarks will be of greatest value for different groups of farms. Results for oyster farms showed that startup costs per oyster harvested were lowest ($0.20/oyster) on established bottom culture farms as compared to $0.96/oyster for established suspended oyster farms, and highest ($1.75/oyster) on startup oyster farms. Profits (Net Farm Income) per oyster were greatest on established bottom oyster farms followed by established suspended oyster farms, but were negative on average, for startup farms. Per-hectare, however, profits were greater on established suspended than bottom culture oyster farms. Labor efficiencies were also greatest for established suspended oyster farms (65 oysters/hour of labor), followed by established bottom culture oyster farms (55 oysters/hour of labor), with the lowest labor efficiency (44 oysters/hour of labor) for startup oyster farms. Given the inherent variability among aquaculture farms, adequate numbers of observations of participating farmers are necessary within each production scale/gear type and startup/established categories for benchmarks to be of value. For emerging sectors of aquaculture, benchmarking metrics can be useful for navigating the critical startup period, but obtaining sufficient numbers of observations is a challenge. Benchmarking metrics for established farm businesses provide guidance on the levels of production and economic performance necessary to be successful. Overall, benchmark values are most useful when applied in a holistic fashion that takes into consideration the performance of the farm across all production, revenue, expense, and efficiency categories (labor, capital, and financial).

Effects of Environment on Productive Performance of Holstein-Friesian Dairy Cows in Three Agro-Ecological Regions of Zimbabwe

The level of performance in any livestock production enterprise is a function of genetic and non-genetic factors and their interaction. For the purpose of agricultural production decisions, Zimbabwe was divided into five agro-ecological zones (AEZ) according to rainfall intensity, distribution and length of rainy season. Commercial dairy production, based on specialist dairy breeds such as Holstein, Holstein-Friesian and Jersey, is confined to AEZ I, II, III and IV. The performance of these breeds in contrasting AEZ has not been determined. In this study, farm level data of 7562 Holstein-Friesian cows calving in the period 2003-2011 was used to compare milk yield and milk components across three contrasting AEZ of Zimbabwe. A Generalized Linear Model (GLM) was fitted to investigate the fixed effects of year, season and AEZ and random effects of days in milk (DIM) on milk production and component traits. The factors herd, agro-ecological zone, year and season had significant (P

Is ICE freezing US agriculture? Farm-level adjustment to increased local immigration enforcement

We study the impact of US immigration enforcement through a locally-implemented program known as 287(g) on agriculture using confidential farm-level data and farm census data. We address the endogeneity of program participation by using pre-program county jail occupancy as an instrument. We provide evidence that the agricultural sector experienced limited endogenous technical change in response to the negative labor supply shock caused by increased immigration enforcement. Fuel expenses increased, consistent with predictions of an increase in automated technology by models of endogenous technical change. However, a corresponding decline in agricultural acres and employment and an increase in labor expenditure suggests capital-labor substitution was insufficient to fully offset the impact of the shock.

Impact of migrant and returning farmer professionalization on food production diversity

Since the 2000s, there has been an increasing number of returning and migrant farmers across China. In 2012, China initiated a program for fostering professional farmers, which has caused greater changes for farmers and led to an agricultural shift towards commercial production. Migration has been recognized as a crucial factor affecting the diversity of agricultural production. However, scant attention has been paid to how different types of farmers influence agricultural diversification. Therefore, this study examines the influence of migrant farmers, returning farmers, and local non-migrant farmers on food production diversity. This study collected farm-level data on food production and farmers’ characteristics and applied a negative binomial regression model to estimate the impacts of different types of farmers on agricultural development. The results show that farms operated by migrant farmers had a significantly lower level of food production diversity while farms operated by returning farmers had no significant difference in food production diversity, using farms operated by local non-migrant farmers as the reference category. The variation in agricultural production diversity lies in differences in food production purposes, agricultural and market skills, and various risk-related capacities among the different types of farmers. Farm-level production specialization does not necessarily reduce food diversity and agrobiodiversity at the rural community and regional level.

Assessing the link between farming systems and biodiversity in agricultural landscapes: Insights from Galicia (Spain)

Agriculture is a major driver of change with manifold impacts on biodiversity and ecosystem services. As social-ecological systems, agricultural landscapes result from the intertwined interaction between farmers and nature, and contribute to several ecosystem services key to human well-being. The social-ecological outcomes of farmlands ultimately reflect the management practices of the dominant farming systems (FS) at the landscape level. However, data-driven research linking agricultural management and biodiversity is still scarce, a knowledge gap limiting our understanding on the impacts of different farming systems on biodiversity at the landscape level.This research contributes to fill this knowledge gap, by being among the few explicitly exploring the relationship between FS and patterns of biodiversity at the landscape level, using as illustrative case the region of Galicia, northwest Spain. Using data from agricultural policies paying agencies, and protected species and habitats data, the following research questions were pursued: (1) Can farm-level data be used to map and characterize different FS at the landscape-level? and, (2) Is the occurrence of specific FS linked with higher levels of biodiversity?Results allowed the identification and characterization of seven different FS distributed across Galicia, which dominance allowed to identify seven landscape types. Moreover, besides depicting the dominance of cattle-based farming systems in Galicia, results showed a gradient of management from the most intensive located in coastal lowlands (west) towards less intensive mountain areas (east). Such gradient of decreasing management intensity matched a gradient of increasing nature value of farmlands, reflected as higher habitat diversity and richness for some of the targeted taxonomic groups.To our knowledge, this research is among the few explicitly addressing the relationship between FS and biodiversity at the landscape level. By highlighting potential links (positive or negative) between specific landscape types and habitats and/or species richness across targeted taxonomic groups, these results constitute a preliminary assessment of the agricultural practices promoting species and habitat richness. Further scrutinizing this assessment can support the identification of farm-level indicators that can be then translated into the design of policies (biodiversity or agriculture-related) fostering biodiversity at several scales of decision making.

Profiling User Needs for Weather and Climate Information in Fostering Drought Risk Preparedness in Central-Southern Nigeria

Weather and climate information trigger early action and facilitate better disaster preparedness. Decision-driven and people-centered weather and climate information are pivotal for the effective uptake. The challenge of early responses in preparing for drought hazard is growing in the dry savannah of tropical sub-Saharan African countries. This paper analyzed user needs for weather and climate information in fostering drought risk preparedness in Central-Southern Nigeria. Stratified, snowball, and simple random samplings were used to obtain a sample of 397 respondents across the agro-ecological zones of Edo State. Structured questionnaire was used to collect farm-level household data across communities. Eight focus group discussions and 11 key informants' interviews were conducted, targeting contact farmers and other agricultural stakeholders in selected key economic sectors of Edo State, Central-Southern Nigeria. Results show that non-users of weather and climate information are more than users in the savannah area. Heckman probit results explained that male gender, farmers' experience, income, and persistent incidence of erratic rainfall have more propensity to facilitate use of WCI in taking critical decisions while group membership or associations and distance of meteorological station prevent stakeholders from developing interest in using WCI for drought preparedness and response. Multi-criteria decision-making indicated that rainfall amount, onset and cessation rainfall dates, and rainfall distributions are the most useful WCI needed by end users in their decision response plan in agriculture; rainfall intensity, rainfall cessation date, rainfall distributions, and length of dry season are ranked as the most useful WCI for water resource management while heat intensity, rainstorms, and drought alerts were ranked as most appropriate for users in the disaster risk reduction in fostering resilience toward anticipated future drought hazard. Subseasonal-to-seasonal (S2S) and medium (4–10 days) timescales information are the most highly rated to facilitate resource planning for efficient utilization and management in all the economic sectors. The users' most preferred delivery method of receiving WCI are mobile telephone, radio, agricultural extension officers, farmers' groups, and contact farmers/specialist for efficiency and convenient criteria in enhancing users' decision capacity to uptake WCI. There is a need for a policy drive to build synergy that will make WCI forecasting systems include impact-based forecast estimates and response advisory across a wide range of natural hazards. A seamless collaborative effort in bringing scientific outputs and users' needs together will increase the utility of WCI through systematic efforts. NiMet should improve on its engagement with the stakeholders, the agricultural extension and planning office, water management authorities, and disaster risk reduction and emergency response personnel as partner institutions. These policy actions would provide a robust collaborative framework for co-producing useable WCI based on user needs in managing decision points against extreme events and mainstream preparedness into existing decision-making apparatus of rural communities in Central-Southern Nigeria.

Structural change in agriculture and farmers' social contacts: Insights from a Swiss mountain region

CONTEXTFarm numbers are steadily declining in Europe and globally while farms become larger and more intensive. Driven in part by worsening macroeconomic conditions, these structural changes and the associated rationalization of agricultural supply chains have affected social relations in rural areas. In turn, farmers' social contacts influence farming decisions. Social and structural changes are thus interconnected, and they affect the resilience of rural areas through their influence on environmental, social, and economic capital. OBJECTIVEWe examine the connection between farm structures and farmers' social contacts in the UNESCO Biosphere Reserve Entlebuch (UBE), a mountain region in central Switzerland with a strong presence of family farms, and explore the implications of social and structural change for rural resilience. METHODSWe conduct a survey of N = 102 farming households and combine it with farm-level agricultural census data and interviews with key stakeholders (N = 13) to analyze farmers' current social contacts and their changes since the year 2000. We use regression and cluster analyses to examine the relationship between (changes in) social contacts and farm-level characteristics. RESULTS AND CONCLUSIONSFarmers in the UBE have a high, but decreasing frequency of contacts with family, friends, and colleagues and lower, but increasing frequency of commercial and administrative contacts. Workloads have increased by 6% in five years, driven by farm-level expansion of agricultural area (+5%)—including expanding ecological compensation areas—and intensification in managed areas (+3%), leading to parallel processes of intensification and extensification. Since most of these family farms do not hire workers, growing workloads directly impinge on farmers' free time, affecting informal contacts most. Farm managers in larger and more intensive farms have more frequent and more diverse, but also more rapidly declining, social contacts. Our results point to a net loss in social capital as social contacts become less frequent and shift from local and informal to regional and national professional contacts. SIGNIFICANCEA 17% decline in farm numbers in 15 years reflects the vulnerability of farms in this region. Growing financial strain, workloads, time pressure and the associated erosion of informal contacts contribute to this vulnerability. Policymakers from local to national should recognize the contribution of farmers' diverse social networks towards rural resilience and seek options to maintain and enhance such networks. Beyond direct interventions that foster social capital, policymakers should more rigorously consider the short- and long-term interconnections and tradeoffs between different forms of capital.

Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia †

Avian pathogenic E. coli (APEC) can cause avian colibacillosis, an economically important disease that contributes to bird mortality and the high costs associated with prevention and treatment. Little is known about APEC in the context of Australian conditions. The current study aimed to estimate the prevalence of APEC and determine the risk factors associated with cloacal carriage of APEC among commercial healthy meat chickens in Queensland. Cloacal swabs were collected at slaughter from 400 healthy meat chickens (ten per farm) originating from 40 farms. A total of 2200 E. coli isolates were selected from cultured swabs and screened for the presence of five APEC-associated virulence genes (VGs). Farm-level data were collected using a questionnaire. Binominal general linear models were used to identify farm-level risk factors associated with bird-level APEC prevalence. Thirty-four per cent of the cultured E. coli isolates (n = 751) were classified as APEC, with all farms testing positive for APEC, and the overall bird-level prevalence of APEC was 63.0%. Higher APEC within-farm bird-level prevalence was positively associated with the usage of well water as a source of drinking water (OR = 6.2, 95% CI: 2.3, 16.5, p &lt; 0.001); not having shower facilities available for farm visitors (OR = 3.6, 95% CI: 1.8, 7.1, p &lt; 0.001); distances greater than 20 m between the car park and the poultry shed (OR = 2.2, 95% CI: 1.4, 3.4, p = 0.001); not applying water line disinfection after each flock cycle (OR = 2.2, 95% CI: 1.4, 3.5, p = 0.001); the presence of wild birds within 50 m of the poultry shed (OR = 2.3, 95% CI: 1.4, 3.7, p = 0.001). Chlorine combined with automatic drinking water filtration reduced within-farm bird-level APEC prevalence (OR = 0.07, 95% CI: 0.02, 0.34, p = 0.001). This study identified a number of important factors associated with APEC and showed that improving biosecurity and water treatments might reduce the prevalence of APEC. The notable high APEC prevalence on all farms requires further epidemiological investigations.

Coping Strategies of Smallholder Coffee Farmers under the COVID-19 Impact in Indonesia

COVID-19 significantly impacts coffee production, which smallholders dominate. Unaddressed impacts will affect coffee production sustainability. However, smallholders face some constraints. This study aims to determine the impact of COVID-19 from the perspective of Arabica and Robusta farmers in Indonesia, examine technical recommendations as coping strategies, and develop an institutional model to accelerate implementation. We analyzed the divergences in the perceptions of different categories and clusters using farm-level data. Descriptive statistics, Mann–Whitney analysis, cluster analysis, and crosstab analysis were used to explore the facts. Immediate effects of COVID-19 were observed through a decline in household income, impacting the allocation of farming costs, which influences productivity related to the intensity of cultivation, particularly in purchasing and fertilization decisions. It was explored by the study that coffee livestock integration is an important strategy to improve farmers’ livelihood to mitigate the impact. The innovation sharing model complements this technical recommendation as institutional recommendations, including innovation sharing elements and processes. Four farmer clusters have been identified based on the adoption spectrum and farmer conditions. The intervention provides innovation-sharing elements for farmers who have not adopted integration. Where integration was partially completed, reusing waste is recommended by completing innovation elements and improving the sharing process.

HOW DO WESTERN EUROPEAN FARMS BEHAVE AND RESPOND TO CLIMATE CHANGE? A SIMULTANEOUS IRRIGATION-CROP DECISION MODEL

Most farm adaptations are reactive actions that run the risk of locking farm systems into suboptimal long-term trajectories. This is especially the case with regard to water management as water scarcity will be aggravated by climate change. This paper looks into farm irrigation choices in combination with crop choices because a proper crop choice has the potential to reduce water requirements. It proposes an extended Ricardian model to capture multiple adaptation decisions explicitly. The new simultaneous irrigation-crop farm decision model uses spatially detailed farm-level data of over 18,000 European farms on irrigation and seven different crop choices. The analysis shows that larger farmers and farmers in less water-scarce regions that use irrigation are more sensitive to temperature increases than rain-fed agriculture. This might be explained by the fact that these farmers do not experience the real cost of water scarcity because of which they take less efficient decisions.

Smallholder sheep farmers’ perception of production constraints and competitiveness strategies in South Africa

Sheep production in South Africa has experienced some growth though very slow, and as such production cannot meet demand in the local market. This study aimed to determine the factor influencing the competitiveness of smallholder sheep farmers’ and constraints faced by sheep farmers in South Africa. A farm-level cross-sectional data of 217 smallholder livestock farmers in South Africa were used to identify the factors influencing the competitiveness of smallholder sheep farmers in South Africa. The Porter's Diamond Model Framework was used to measure the competitiveness of sheep production in the study areas and principal component analysis was applied to assess the constraints faced by sheep farmers. The study results found that smallholder sheep farmers in the study area are faced with numerous production constraints, which inhibit their productivity and competitiveness. The most severe constraints include marketing, stock theft, lack of capital, diseases and parasite, and high feed cost. The study suggest that smallholder sheep farmers in the study areas can be competitive and experience growth through the creation of agribusiness enabling environments by promoting policies and strategies that will boost investments in sheep production across the value chain.

Precision agriculture adoption and technical efficiency: An analysis of sugarcane farms in Brazil

• Precision agriculture technologies (PATs) are at the core of Agriculture 4.0. • We analyzed the impacts of PATs adoption on sugarcane farms performance. • Selectivity correction SPFs and metafrontier production function were applied. • Adoption of PATs reduces managerial and technological gaps in sugarcane farming. • Farmer schooling, farm size and technical assistance affect the adoption of PATs. Precision Agriculture Technologies (PATs) are at the core of the fourth revolution in farming technology, also called Agriculture 4.0. This study evaluates the determinants of PATs adoption and its impacts on technical efficiency (TE) and technology gap ratio (TGR) of sugarcane farms in the state of São Paulo, Brazil. A selectivity correction model for stochastic frontiers is combined with a metafrontier production function approach to estimate the role of a set of determinants of PATs adoption and its impacts on TE and TGR. In person interviews with 131 sugarcane farmers provided cross-sectional farm level data from the 2018/19 crop year. The estimates of a sample selection equation showed that farming size, farmer's schooling and technical assistance positively affect PATs adoption by sugarcane farmers. Estimates of stochastic production frontiers (SPFs) and metafrontier revealed that the average of the TE and TGR scores of adopters are higher than those of non-adopters. The managerial gaps (TE) between adopters and non-adopters are considerably wider than their technology gaps (TGR). The adoption of PATs subsidizes farmers decision-making process which increased the efficiency in inputs use, an important issue for economic and environmental sustainability in sugarcane farming.

Does risk management affect productivity of organic rice farmers in India? Evidence from a semiparametric production model

This study analyzes the effects of farmers’ risk on productivity where the production function is generalized to be specific to risk variables. This resulted in a semiparametric smooth-coefficient (SPSC) production function. The novelty of the SPSC approach is that it can explain the direct and indirect channels through which risk can affect productivity. The study uses several measures of risk, including attitudes toward risk, perceptions of risk, and risk management skills of farmers. It then shows how these risk-related variables affect productivity both directly and indirectly via the inputs. Using 2015 farm-level data from organic basmati rice (OBR) smallholders in India, the study finds that OBR farmers with high degrees of risk aversion had lower productivity than less risk-averse or risk-neutral OBR farmers. Additionally, OBR farmers who were most concerned about production risks (i.e., weather and pest risks) had higher productivity than their counterparts. Finally, the study reveals that OBR farmers can reduce production costs by increasing farm size.

Implications of Farmer’s Adaptation Strategies to Climate Change in Agricultural Sector of Gujarat: Experience from Farm Level Data

This study examined the farmer’s perception on climate change and adaptation strategies to mitigate the adverse effect of climate change in the agricultural sector of Gujarat. It used farm level information of 400 farmers who were purposely selected from 8 districts. Thereupon, linear, non-linear and log-linear production function models were used to examine the impact of climate change, farmer’s adaptation strategies and technological change on agricultural production in Gujarat. The descriptive and empirical results specify that adaptation strategies (i.e., change in showing time of crops, mixed cropping pattern, irrigation facilities, application of green and organic fertilizer, hybrid varieties of seeds, dampening of seed before planting, climate tolerate crops, organic farming and technology) have a positive impact on agricultural production. Thus, farmer’s adaptation strategies are useful to mitigate the negative impact of climate change in the agricultural sector. Maximum temperature and minimum temperature, precipitation and rainfall have a negative impact on agricultural production. However, the impact of these factors seemed positive in the agricultural sector when farmers apply aforementioned adaptation strategies in cultivation. Family size, education level of farmers, annual income of farmers, arable land, irrigated area, cost of technology, appropriate technology and financial support from government have a positive contribution to increase agricultural production in Gujarat.