Adoption Of New Agricultural Technologies Research Articles

In Good Times and in Bad, in Sickness and in Health: The Continuous Rise in Adoption of Labour-Saving Agricultural Technologies in Myanmar

Agriculture is rapidly transforming in many low- and middle-income countries – most often driven by the adoption of new agricultural technologies – but changes remain poorly understood in fragile and conflict-affected states. We look at the case of Myanmar, a prime example of such a state. After decades of isolationism and economic stagnation, it opened its economy in the beginning of the 2010s, leading to rapid economic growth. But the COVID-19 health crisis and a military coup in the beginning of 2021 – leading to heightened conflicts, forced displacements, and increased migration – dramatically reversed that outlook. Based on large-scale farm surveys, we find that adoption of labour-saving agricultural technologies – measured by the use of mechanization, herbicides, and direct seeding of rice – increased rapidly over the economic growth period and that the increase surprisingly persisted during the crisis years, but at a slower rate. This uptake was lower, however, for households in the most conflict-affected areas, partly due to differential agricultural input availability. Smallholders and more remote farmers also participated less. This finding suggests an increasing labour productivity gap for remote and conflict-affected smallholders, with important implications for their welfare.

Guaranteed storage? Risk and credit constraints in the demand for postharvest technology

Abstract Uninsured risk is often cited to explain the lagging adoption of new agricultural technologies in low-income regions. However, insurance interventions suffer from poor take-up. We test whether bundling a new product–hermetic storage bags–with a warranty can serve as a viable alternative. We compare the warranty to a credit intervention and a control using an incentivized auction in rural Bangladesh. We find the warranty had no impact on demand. Providing the bags on credit significantly increased willingness-to-pay, and machine learning estimates indicate credit may have raised the demand for the most marginal farmers. Warranties failed to stimulate demand along any dimension.

Identification of returns to new technologies under distinctive econometric approaches

ABSTRACT This article uses distinctive econometric models to investigate returns to new technologies and whether adoption decisions can be explained by comparative advantage. I consider three models: static and dynamic panel models of homogeneous returns to fertilizer, as well as the correlated random coefficient model of heterogeneous returns. I discuss both the benefits of using each of the models and their interpretations. I then use data from cocoa farming in Ghana to identify the returns to fertilizer by means of these three models. The estimated average returns in different models are positive, high and strongly significant statistically. I also find evidence of heterogeneous returns to new technology based on comparative advantage. My overall results suggest that adoption of new agricultural technologies may not necessarily benefit all farmers, and the adoption decision may be crop-specific, context-specific or technology-specific.

Private Input Suppliers as Information Agents for Technology Adoption in Agriculture

Information frictions limit the adoption of new agricultural technologies in developing countries. Efforts to improve learning involve spreading information from government agents to farmers. We show that when compared to this government approach, informing private input suppliers in India about a new seed variety increases farmer-level adoption by over 50 percent. Suppliers become more proactive in informing potential customers and carrying the new variety. They induce increased adoption by those with higher returns from the technology. Being motivated by expanded sales offers the most likely motive for these results. (JEL D83, L14, L33, O13, O32, Q12, Q16)

Does the supply response of maize suffer from climate change in Bangladesh? Empirical evidence using ARDL approach

This study examines the effects of climate and non-climatic parameters on maize yield in Bangladesh from 1980 to 2020. The research used the autoregressive distributed lag-bounds (ARDL) method to determine the short run and long-run relationship between the variables, including CO2 emissions, average temperature, and average rainfall, overall population, agricultural technology, and energy consumption. By applying the Johansen and Juselius Cointegration (JJC) approach we confirmed the lon-run cointegration between the studied variables. The study found that all climate parameters negatively impacted maize yield in both the short and long run, while non-climatic factors, such as agricultural technology, had a positive impact. In addition, the population had a negative impact on maize yield, and energy consumption had a positive impact over the short run but a negative effect over the long run. The findings of the study recommend that several policy interventions can be implemented to improve maize productivity in Bangladesh. These include promoting the adoption of new agricultural technologies, mitigating climate change, sustainable land use practices, energy efficiency, and policies to support small farmers. These interventions can address the negative effects of climate change and other factors, as well as promote sustainable agriculture practices in the long run.

Determinants of teff row planting technology adoption on small farms yield in North Shewa zone, Amhara region, Ethiopia

Adoption of agricultural technology is an important avenue to increase agricultural productivity and thus improve the food security and livelihood of societies. To achieve this, it is quite important to understand the determinants of the adoption of new agricultural technologies. This study examined the determinants of teff row planting technology adoption on small farms’ yields in the North Shewa Zone, Amhara Region, Ethiopia. The study applied the quantitative research method. A sample of 796 agricultural households was considered, and the logit model was used to estimate the factors affecting the application of determinants of teff row planting technology adoption on small farms’ yield. According to the study, plot distance, active household member, number of oxen, extension service, access to credit, distance from market, marital status of household head, and distance from main road are the main factors influencing teff row planting technology adoption on small farm yield in North Shewa Zone, Amhara Region, Ethiopia. The findings suggests that expanding credit access, extension services, and market access to farm households are important to improving the application of teff row planting technology.

Comparative Study of the Agro-Innovation Adoption among Members and Non-Members of Agricultural Cooperatives in Nigeria

This study compares the level of awareness and adoption of innovative agricultural technologies among members and non-members of cooperative societies. This is to direct policies on the diffusion and adoption of agricultural technologies to facilitate increased food production as Nigeria’s economy strives for post-COVID-19 survival and recovery. A multistage technique was used to select a sample of 320 constituting 160 cooperative members and 160 non-cooperative members. Structured questionnaires were used to collect primary data, which was then analysed using both descriptive (Mean, standard deviation) and inferential (regression, ANOVA) statistics. The results suggest that awareness and adoption of new agricultural technologies are higher among members of cooperatives compared to non-members. This study advocates that cooperative societies are veritable vehicles for innovation diffusion. Some challenges of the farmers were explored, and the study recommended that new technologies should be introduced through cooperatives using Small Plots Adoption trial (SPAT) and increased deployment of extension workers to farmers. Furthermore, Cooperative farmers and non-cooperative farmers should be persuaded by the extension workers in ADP to attend agricultural exhibitions where the farm outputs of new technologies are displayed together with the outputs of the old technologies so that they can see the obvious difference and adopt the new technologies.

Interrelationship between the Use of New Agricultural Inputs and Socio-economic Factors

This paper deals with interrelationship between the use of new agricultural technology and socio-economic factors in Dhankuta municipality, eastern hills of Nepal. This area offers a lot of resources; here the researcher examines the role of socio-economic factors to diffuse new technology in this area too. Relevant data were obtained from both primary and secondary sources. Primary data were collected from the interview, key informant survey and field observation. For this, approximately 33 percent sample households (166hhs) were selected out of total 506 households from ward no. 3 of the municipality. Similarly, secondary data were gathered from various books, journals and official records. To identify the mutual relationship between these components, mathematical tools chi-square test and Karl Pearson's correlation were performed. The study reveals that there is a close relationship between the use of new agricultural inputs and socio-economic factors of the study area. The relationship seems highly significant between age, training, farm size, service of agriculture service center and membership of farmers in organization and adoption of new agricultural technologies however; the inter-connection with sex, ethnicity and education of the farmers reveals less significant among these factors. Nowadays, more than 78 percent (130hhs) farmers are using such inputs in the study area and the remarkable change in crop production can easily be seen due to the impact such innovations.

Observed time series trend analysis of climate variability and smallholder adoption of new agricultural technologies in west Shewa, Ethiopia

This study was aimed at analyzing time-series trends and variability analysis of observed rainfall and temperature records from 16 stations during the 1985–2015 period. Besides, it focused on the smallholders’ perceptions, including the analysis of their response strategies to both observed and perceived climate variability and its determinants. Both purposive and random sampling procedures were used. Mixed methods (quantitative and qualitative) of the research were used. The sample household survey method was used to collect primary data from smallholder farmers, while key informant interviews were used to gather qualitative data from the experts. A semi-structured questionnaire was used to collect quantitative data, whereas a discussion guide checklist was used to gather qualitative data. A total of 397 respondents and 24 key informants were used as sources of primary data. In addition, visits to the National Meteorology Agency of Ethiopia were made to collect recorded climate data. Descriptive statistics and econometric models were used to analyze quantitative data, whereas thematic categorization was used to analyze and report qualitative data. The results show that both the summer and annual rainfall have an increasing trend but are not statistically significant. With regards to variability, low to moderate levels of variability were recorded according to the seasons and annual rainfall. The result of the Mann-Kendall test shows that the mean minimum temperature was raised by 0.05 °C while the maximum temperature rose by 0.03 °C/30 years. The monthly maximum temperature also shows an increasing trend, with the lowest record during August (22.05 °C) and the highest in March (26.49 °C. Besides, smallholder farmers’ perceptions were in accordance with recorded station data. In response to both observed and perceived climate variability and its extremes, smallholder farmers in the study area were striving to adopt different adaptation strategies. Rain variability, frequency of extension contact, years of farming experience, access to institutions and infrastructure, wealth status, market access, and the number of active labor force within the household all hampered smallholder farmers' efforts to implement potential measures. In contrast, the high prices of chemicals and improved seed, access to credit services, land size, and limited access to accurate and timely early warning information all negatively and significantly influenced the adaptation decisions of smallholder farmers in the area. Therefore, the impacts of abnormal trends or shifts in observed rainfall and temperature patterns, along with socio-economic, technological, and behavioral factors, call for policymakers to set strategies that will enable smallholders to improve their livelihoods, ensure food security, and build resilience in the face of climatic extremes.

The Impact of Social Capital on Farmers’ Willingness to Adopt New Agricultural Technologies: Empirical Evidence from China

Based on the microdata of 11,547 farmers from the China Labor Dynamics Survey (CLDS) database in 2017, an ordered multi-classification logistic model was constructed to empirically test the impact of social capital (i.e., social networks, social participation, and social trust) on farmers’ willingness to adopt agricultural technology. The moderating effect of demographic changes (i.e., the number of instances of hukou migration) on social capital and farmers’ willingness to adopt new agricultural technology was further investigated. The results show that the following: (1) Social trust has a significant positive impact on farmers’ willingness to adopt new agricultural technologies, while social participation has no significant impact on farmers’ willingness to adopt new technologies. (2) Social networks influence farmers’ technology adoption behavior differently, e.g., the scope of relatives’ wedding gifts has a significant and positive influence on farmers’ technology adoption behavior, while the scope of non-relatives’ wedding gifts has no significant influence on farmers’ technology adoption behavior. (3) Demographic change plays a moderating role in the impact of social capital on farmers’ willingness to adopt new agricultural technologies. In other words, the greater the number of instances of hukou migration, the less the promoting effect of social capital on farmers’ willingness to adopt agricultural technology. (4) In the eastern and central regions of China, social capital has a significant positive impact on farmers’ adoption of new agricultural technologies. In the western region of China, social capital has a significant negative impact on farmers’ adoption of new agricultural technology. In the northeast region of China, social capital has no significant impact on farmers’ adoption of new agricultural technologies. Social capital and population changes are important factors that affect farmers’ willingness to adopt new agricultural technologies. Therefore, attention should be paid to cultivating and promoting farmers’ social capital to improve farmers’ willingness to adopt new agricultural technologies.

Examining the transfer of knowledge and training to smallholders in India: Direct and spillover effects of agricultural advisory services in an emerging economy

We evaluate a large-scale model of agricultural advisory services, known as Krishi Vigyan Kendra (KVK) or Farm Science Centers, introduced by the Government of India to facilitate smallholder adoption of new agricultural technologies. The study first evaluates the impact of frontline demonstrations and capacity-building programs conducted by KVKs and aimed at promoting a new wheat variety (HD-2967); it then examines gains in the speed of diffusion at the district level. The study’s second objective is to estimate the spillover effects of KVKs through social networks. The study identifies network beneficiaries based on a “networks within sample” approach. The study uses a matched difference-in-differences approach and sample of 1496 wheat farmers in Uttar Pradesh, India. The finding shows that frontline demonstrations and capacity-building programs positively impact the adoption of HD-2967. The magnitude of the impacts is larger for KVK beneficiaries, but substantial gains also arise for network beneficiaries. The study underscores the importance of frequently conducting interventions to influence adoption on aggregate at the district level. From a policy perspective, the study offers new insights for strengthening outreach and extension services designed to facilitate the transfer of agricultural knowledge and information, emphasizing frontline demonstrations, capacity-building programs, and spillovers in extending the scope of KVKs.

Climate risk perceptions and perceived yield loss increases agricultural technology adoption in the polder areas of Bangladesh

The effects of climate change are likely to increase the frequency of flood, drought, and salinity events in the coastal areas of Bangladesh, posing many challenges for agrarian communities. Sustainable intensification in the form of improved agricultural management practices and new technologies may help farmers cope with stress and adapt to changing conditions. In this study, we explore how climate change perceptions of agricultural risk affect adaptation to climate change through technology adoption in a unique landscape: the polders of Bangladesh. In 2016, a survey was conducted in 1003 households living on these artificial, leveed islands facing the Bay of Bengal. We analyzed the responses from polder residents to construct a climate risk index which quantifies climate risk perception in this highly vulnerable agrarian landscape. We analyzed how polder demographics influence their perceptions about climatic change using seemingly unrelated regression (SUR). Further, by using three bivariate probit regression models, we estimated how the perception of climate risk drives the differential adoption of new agricultural technologies. Our findings show that farmers perceive polder agriculture as highly vulnerable to four environmental change factors: flooding, drought, salinity, and pest infestation. The SUR model suggests that farmer demographics, community group memberships, and access to different inputs and services strongly influence climatic risk perceptions. Findings also suggest that polder farmers with higher risk perceptions have a higher propensity to adopt both chemical and mechanical adaptation strategies. Cost, however, limits the ability of farmers to adopt improved technologies, suggesting an opportunity for institution-led approaches.

Adoption and income effects of new agricultural technology on family farms in China.

Family farms are the main force that promotes the direct application of new agricultural technology to production. So what are the factors that affect the adoption of new agricultural technology by family farms, and can the adoption of new technology increase the operating income of family farms? Using cross-sectional data from 847 family farms, this study examines the determinants and impacts of multiple new agricultural technologies adoption on family farms’ income in China. To account for selection bias from both observable and unobservable factors, an endogenous switching regression model is employed to evaluate the effects of new agricultural technology on family farms’ income. The empirical results show that the adoption of new agricultural technology is affected by the endowment of farmers and the characteristics of family farms. After controlling for the selection bias, the adoption of new agricultural technologies has a positive and significant impact on family farms’ income. And the impact on the non-adopter family farms is much larger than adopter family farms. Heterogeneity analysis indicates that family farms with a larger area of arable land earn more from the adoption of new technologies than small farms. In all types of technology investigated, the new methods of pest control and the new chemical fertilizer technology have a relatively large impact on family farms’ income, while the new mechanical technology has the least impact on family farms’ income. The adoption of new technologies by family farms is more important for promoting the progress of agricultural science and technology. Therefore, it is necessary to take effective measures to overcome the obstacles to the adoption of new agricultural technologies and pay more attention to the use of new agricultural technologies to improve agricultural production efficiency.

Determinants and Impact of the Adoption of Bangladesh Agricultural Research Institute Developed Maize Sheller in Mymensingh District of Bangladesh

Adoption of new agricultural technologies is always at the center of policy interest in Bangladesh as it generates higher farm productivity and income for the farmers. Despite the visible benefits of many of the new agricultural technologies, including farm machinery and management practices, farmers either do not adopt them or it takes a long time to begin the adoption process and scaling up. The study was carried out to determine the impacts of adoption of Bangladesh Agricultural Research Institute (BARI) maize sheller on productivity and farm income in Mymensigh district. Primary data were collected from 41 adopters and 79 non-adopters of BARI maize sheller. Propensity score matching method was used to assess the impacts of BARI maize sheller adoption. It was found that the rate of adoption of BARI maize sheller was 26.73% at farm level. Probit model showed that experience in maize cultivation of the farmer and training enhanced the adoption of BARI maize sheller and family size had negative effect on adoption of BARI maize sheller. BARI maize sheller adoption on average increased maize productivity and farm income by 327.08 kg/ha and 34 to 65% respectively for adopters compared to non-adopters. Policy implications included more investment in training facilities from public agencies to sustain and increase the productivity and income of maize farmers. Modifying the training approach could provide opportunity to young maize farmers to increase their know-how. Various government and non-government organizations working in Bangladesh including Mymensingh district need to promote a rapid uptake and scaling up of BARI maize sheller.

Impact of farmer field schools on agricultural technology extension—evidence from greenhouse vegetable farms in China

ABSTRACT Agricultural extension is a key instrument to bridge the gap between new technologies and farmers. As a popular extension approach, farmer field schools (FFS) usually improve farmers’ knowledge and crop productivity. This study aims to quantify the heterogeneous impact of FFS on the cognition and adoption of multiple new agricultural technologies. In this study, we apply Tobit models to estimate the impact of FFS on technology extension regarding farmers’ cognition and adoption rates of different technologies, using data collected for 274 tomato and cucumber farm households in Beijing, China. We find that the FFS programmesignificantly increased farmers’ cognition and adoption of new agricultural technologies. We also find that the effects of FFS on extension vary in different categories of new technology. Particularly, we find that the extension of facility technologies is difficult, and new varieties are easy to disseminate but difficult to adopt by farmers. We conclude that FFS is an important channel for the extension of new agricultural technologies. At the same time, attention should be paid to the design of the FFS programme, adjusting to the attribute of different technologies.

Determinants of Adoption of New Agricultural Technologies by Cooperative Farmers in Nigeria

Globally, advanced technologies are invented or discovered for the improvement of farming activities. In Nigeria, such technologies are gradually being available from research institutes and imported technologies. The low outputs of farms suggest that these technologies seem not to be highly adopted in Nigeria and the factors that determine the adoption of these technologies are yet to be explored. The study examined the socio-economic and institutional determinants of the adoption of new agricultural technologies by cooperative farmers in Nigeria. A descriptive survey research design was adopted. Multistage random sampling technique was used to select three hundred and twenty farmers (160 individual farmers and 160 co-operative farmers), statistically derived using the Taro Yamane formula. The data used for this study were sourced from primary data. Descriptive and inferential statistics were deployed in the analysis of data. Findings revealed that sex, marital status, farm size and annual farm income socio-economic are the socioeconomic factors affecting the adoption of new agricultural technologies while the frequency of contact with extension agents is the key institutional factor affecting the adoption of agricultural technologies. Recommendations made include that extension services should be improved by the Agricultural Development Programme. There should be at least two extension agents to each community who should visit the farms regularly and expose the farmers to the latest agricultural technologies through Small Plots Adoption Trials (SPATS) and On-Farm Adaptive Research. The extension service workers in ADP should enjoin individual farmers to form effective groups (Co-operative Societies) for easy diffusion of the agricultural technological innovations.

A farming system typology for the adoption of new technology in Bangladesh

AbstractOver the last three decades, few studies have been conducted to tackle the complexity and heterogeneity of Bangladesh farming systems. We address these research gaps with a new survey. Accordingly, a survey was conducted in North‐Western Bangladesh to understand how socio‐economic traits influence technology adoption and to identify and characterize key farm types. The survey was based on farm household characteristics, farm structure, farming practices and livestock as well as the economic performance of the farm. Principal component analysis (PCA) and cluster analysis (CA) were used to establish the different farm typologies, and the data set based on 27 variables was carefully analysed. The findings confirmed that the key variables that significantly affect the adoption of new agricultural technologies relate to age, farming experience, level of education of the household head, income, access to markets, land ownership, the proportion of hired labour, savings, food self‐sufficiency and income from off‐farm activities. Four main farm types were identified in the study area based on resource endowment and livelihood orientation. These are (1) well‐resourced farmers entirely dependent on agriculture and less reliant on off‐farm activities; (2) moderately resourced households, which are headed by an older male with greater farming experience and which are engaged in both on‐farm and off‐farm activities; (3) resource‐constrained households with cattle as the main livestock and with income generated by the sale of livestock products; and (4) severely resource‐constrained households which are headed by young farmers/men and where income is generated by off‐farm activities. These four farm categories represent the heterogeneity of farms in North‐West Bangladesh, and it is hoped that the development of this farm household typology will help particularly the extension service, to set up appropriate extension advice that will benefit the farming community.

The impact of rural-urban migration experience on fertilizer use: Evidence from rice production in China

While a growing number of rural migrants return to engage in agriculture, little attention has been attached to the impact of rural-urban migration experience on fertilizer use. From a theoretical perspective, rural-urban migration experience could affect fertilizer use through remittance, adoption of new agricultural technologies, and improved management philosophy. Using a cross-sectional survey dataset covering 1122 rice-producing farm households in China, this study examines the impact of rural-urban migration experience on fertilizer use in rice production. The treatment effects model and instrumental variable method are employed to account for the self-selection bias and endogeneity of rural-urban migration experience. The survey shows that the heads of 261 farm households had rural-urban migration experience. The econometric results illustrate that rural-urban migration experience is conducive to reducing fertilizer use in rice production. The neglect of self-selection bias and endogeneity of rural-urban migration experience would produce biased and inconsistent results. Moreover, there is a positive impact of rice-fertilizer price ratio on fertilizer use, and the adoption of hybrid rice variety and participation in technology training activities could reduce fertilizer use in rice production.

Grain Legumes Production in Ethiopia: A Review of Adoption, Opportunities, Constraints and Emphases for Future Interventions

Accelerating agricultural growth remains one of the most urgent goal of Ethiopia as the agricultural sector is the backbone of the Ethiopian economy. The adoption of new agricultural technologies and improved practices are particularly important in increasing agricultural production. This comprises strengthening legumes adoption and production as it contributes to better food security and more sustainable farming systems. Grain legumes are necessary elements of crop production in Ethiopia. The adoption and use of legume crops have been advocated for enhanced nutrition and preserving soil resources. Different improved varieties and legume production technologies have been made available to farmers through various sectors and projects in the country. Various policy measures and initiatives have also been made in improving the adoption, technology generation and contribution of legumes to the various system. Despite their contribution and considerable initiatives, over-all level of adoption and use of legume production is still low. A wide array of technical, economic, social, and institutional factors has been found to encounter the adoption, use and production of legumes along with their value-chain. However, there are still various opportunities that different grain legumes are to be adopted and promoted to increase production and productivity. Essential interventions, innovative approaches, increased production packages and improved technologies and market access should be emphasized and integrated to strengthen grain legumes adoption and production.

Biosafety Regulatory Reviews and Leeway to Operate: Case Studies From Sub-Sahara Africa.

While modern biotechnology and, specifically, genetic modification are subject of debate in many parts of the world, an increasing number of countries in Sub-Sahara Africa are making important strides towards authorizing general releases of genetically modified (GM) crop varieties for use by farmers and agribusinesses. Obviously, the documented economic and environmental benefits from planting GM crops—based on a track record of over two decades—are a major driver in the decision-making process. Another key factor is the increasing alignment of biosafety regulatory policies with progressive agricultural and rural development policies in Africa, resulting in—compared to past experiences—greater emphasis on anticipated benefits rather than risks in biosafety regulatory reviews. In several cases, this has led to expedited reviews of GM crop release applications, either for confined field trials or general environmental release, taking experiences and data from other countries into account. Such regulatory approaches hold promise as the pipeline of relevant, pro-poor GM crop applications is expanding as are the opportunities provided by novel plant breeding techniques. This review article analyses the shifting policy context in select African economies, resulting in adoption of new agricultural technology, and novel regulatory approaches used in biosafety decision-making. Case studies will be presented for Ghana, Kenya, Malawi, Nigeria and Uganda to analyze challenges, distill lessons learned and to present general policy recommendations for emerging economies.