Landscape features support natural pest control and farm income when pesticide application is reduced.

Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.

Impact of economic indicators on rice production: A machine learning approach in Sri Lanka.

Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic landscapes. This study delves into the complex interplay between economic indicators and rice production, aiming to uncover correlations and build prediction models using machine learning techniques. The dataset, spanning from 1960 to 2020, includes key economic variables such as GDP, inflation rate, manufacturing output, population, population growth rate, imports, arable land area, military expenditure, and rice production. The study's findings reveal the significant influence of economic factors on rice production in Sri Lanka. Machine learning models, including Linear Regression, Support Vector Machines, Ensemble methods, and Gaussian Process Regression, demonstrate strong predictive accuracy in forecasting rice production based on economic indicators. These results underscore the importance of economic indicators in shaping rice production outcomes and highlight the potential of machine learning in predicting agricultural trends. The study suggests avenues for future research, such as exploring regional variations and refining models based on ongoing data collection.

Factors affecting onion production: An empirical study in the Raya Kobo district, Amhara regional state, Ethiopia.

Onion is a vital vegetable crop in Ethiopia, with significant economic and health benefits. However, its production trend is not consistent, with periods of increase and decrease; and its productivity in the country falls far below its potential. As a result, farmers are not yet fully benefited from onion production. Thus, this study was initiated to identify the factors influencing onion production in the Raya Kobo District of Amhara Regional State of Ethiopia. Data was collected from 189 onion-producing farmers through household surveys, and both descriptive and econometric techniques were used for analysis. The study found significant variation in onion production among farmers, with lower levels compared to national and international averages. Factors such as gender, education level, experience, labor force, land size, access to extension services, irrigation water, land plough frequency, and fertilizer availability positively impact onion production. However, excessive fertilizer use was found to have a negative effect. The study also identified challenges faced by farmers, including input shortages, high costs, diseases, labor issues, soil infertility, and storage knowledge gaps. The study recommends policymakers and stakeholders to utilize these findings to develop effective policies and interventions that can enhance onion production, benefiting farmers and improving the overall onion production.

Narrowing yield gaps does not guarantee a living income from smallholder farming-an empirical study from western Kenya.

Crop yields in sub-Saharan Africa need to increase to keep pace with food demands from the burgeoning population. Smallholder farmers play an important role in national food self-sufficiency, yet many live in poverty. Investing in inputs to increase yields is therefore often not viable for them. To investigate how to unlock this paradox, whole-farm experiments can reveal which incentives could increase farm production while also increasing household income. In this study we investigated the impact of providing farmers with a US$ 100 input voucher each season, for five seasons in a row, on maize yields and overall farm-level production in two contrasting locations in terms of population density, Vihiga and Busia, in western Kenya. We compared the value of farmers' produce with the poverty line and the living income threshold. Crop yields were mainly limited by cash constraints and not by technological constraints as maize yield immediately increased from 16% to 40-50% of the water-limited yield with the provision of the voucher. In Vihiga, at best, one-third of the participating households reached the poverty line. In Busia half of the households reached the poverty line and one-third obtained a living income. This difference between locations was caused by larger farm areas in Busia. Although one third of the households increased the area farmed, mostly by renting land, this was not enough for them to obtain a living income. Our results provide empirical evidence of how a current smallholder farming system could improve its productivity and value of produce upon the introduction of an input voucher. We conclude that increasing yields of the currently most common crops cannot provide a living income for all households and additional institutional changes, such as alternative employment, are required to provide smallholder farmers a way out of poverty.

Crop switching can enhance environmental sustainability and farmer incomes in China.

Achieving food-system sustainability is a multidimensional challenge. In China, a doubling of crop production since 1990 has compromised other dimensions of sustainability1,2. Although the country is promoting various interventions to enhance production efficiency and reduce environmental impacts3, there is little understanding of whether crop switching can achieve more sustainable cropping systems and whether coordinated action is needed to avoid tradeoffs. Here we combine high-resolution data on crop-specific yields, harvested areas, environmental footprints and farmer incomes to first quantify the current state of crop-production sustainability. Under varying levels of inter-ministerial and central coordination, we perform spatial optimizations that redistribute crops to meet a suite of agricultural sustainable development targets. With a siloed approach-in which each government ministry seeks to improve a single sustainability outcome in isolation-crop switching could realize large individual benefits but produce tradeoffs for other dimensions and between regions. In cases of central coordination-in which tradeoffs are prevented-we find marked co-benefits for environmental-impact reductions (blue water (-4.5% to -18.5%), green water (-4.4% to -9.5%), greenhouse gases (GHGs) (-1.7% to -7.7%), fertilizers (-5.2% to -10.9%), pesticides (-4.3% to -10.8%)) and increased farmer incomes (+2.9% to +7.5%). These outcomes of centrally coordinated crop switching can contribute substantially (23-40% across dimensions) towards China's 2030 agricultural sustainable development targets and potentially produce global resource savings. This integrated approach can inform feasible targeted agricultural interventions that achieve sustainability co-benefits across several dimensions.

Cost-effective mitigation of nitrogen pollution from global croplands.

Cropland is a main source of global nitrogen pollution1,2. Mitigating nitrogen pollution from global croplands is a grand challenge because of the nature of non-point-source pollution from millions of farms and the constraints to implementing pollution-reduction measures, such as lack of financial resources and limited nitrogen-management knowledge of farmers3. Here we synthesize 1,521 field observations worldwide and identify 11 key measures that can reduce nitrogen losses from croplands to air and water by 30-70%, while increasing crop yield and nitrogen use efficiency (NUE) by 10-30% and 10-80%, respectively. Overall, adoption of this package of measures on global croplands would allow the production of 17 ± 3 Tg (1012 g) more crop nitrogen (20% increase) with 22 ± 4 Tg less nitrogen fertilizer used (21% reduction) and 26 ± 5 Tg less nitrogen pollution (32% reduction) to the environment for the considered base year of 2015. These changes could gain a global societal benefit of 476 ± 123 billion US dollars (USD) for food supply, human health, ecosystems and climate, with net mitigation costs of only 19 ± 5 billion USD, of which 15 ± 4 billion USD fertilizer saving offsets 44% of the gross mitigation cost. To mitigate nitrogen pollution from croplands in the future, innovative policies such as a nitrogen credit system (NCS) could be implemented to select, incentivize and, where necessary, subsidize the adoption of these measures.

Perennial rice could be a 'game changer'.

Long-term study in China shows yields hold up and farmers save money and time.

Plot-level impacts of improved lentil varieties in Bangladesh.

The advent of improved lentil varieties (ILVs) in the mid-1990s solved the disease problem which almost halted lentil production in Bangladesh. Levels of adoption of ILVs have been documented in the literature, but little is known about their impacts. Applying an instrumental variables regression to data collected from a sample of 1,694 lentil plots and DNA fingerprinting for varietal identification, this study provides estimates of the plot-level impacts of adoption of ILVs in Bangladesh. Model results show that adoption of ILVs is associated with 14.3% (181.14 kg/ha) higher yields and 17.23% (US$169.44/ha) higher gross margins. Since 45% of lentil area is under ILVs, they generated over 8.77 tones (6%) more supply of lentils from domestic sources, saving the country US$8.22 million in imports in 2015 alone. By investing in the generation and scaling of ILVs, Bangladesh and other South Asian countries with similar agro-ecologies can increase production and decrease dependency on lentil imports.

Trade-offs between economic, environmental and social sustainability on farms using a latent class frontier efficiency model: Evidence for Spanish crop farms.

This article studies trade-offs of farms in terms of economic sustainability (proxied here by technical efficiency), environmental sustainability (proxied here by farmers' commitment towards the environment) and social sustainability (proxied here by farmers' contribution to on farm well-being and communities' well-being). We use the latent class stochastic frontier model and create classes based on three separating variables, representing farms' environmental sustainability and social sustainability. The application to a sample of Spanish crop farms shows that more environmentally sustainable farms are likely to have lower levels of technical efficiency. However, improvements in social concerns, both towards own farm and the larger community, may lead to improved technical efficiency levels. In general, our study provides evidence of trade-offs for farms between economic sustainability and environmental sustainability, but also between environmental sustainability and social sustainability.

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India.

Productivity growth in smallholder agriculture is an important driver of rural economic development and poverty reduction. However, smallholder farmers often have limited access to information, which can be a serious constraint for increasing productivity. One potential mechanism to reduce information constraints is the public agricultural extension service, but its effectiveness has often been low in the past. Digital technologies could enhance the effectiveness of extension by reducing outreach costs and helping to better tailor the information to farmers' individual needs and conditions. Using primary data from India, this study analyses the association between digital extension services and smallholder agricultural performance. The digital extension services that some of the farmers use provide personalized information on the types of crops to grow, the types and quantities of inputs to use, and other methods of cultivation. Problems of selection bias in the impact evaluation are reduced through propensity score matching (PSM) combined with estimates of farmers' willingness to pay for digital extension. Results show that use of personalized digital extension services is positively and significantly associated with input intensity, production diversity, crop productivity, and crop income.

Econometric ridge regression models of risk-sensitive sunflower yield / Modelos economométricos de regressão de rendimento de girassol sensível ao risco

The article considers econometric ridge regression models of the risk-sensitive sunflower yield on the example of an export-oriented agricultural crop. In particular, we have proved that despite the functional mulcollinearity of the predictors in the sunflower yield model with respect to risk caused by the algorithm peculiarities of the hierarchy analysis methods, the ridge regression procedure makes it possible to obtain its complete specification and provide biased but stable estimates of the forecast parameters in the case of uncertain input variables. It has been substantiated that the rational value of the displacement parameters is expedient to be established using a graphical interpretation of the ridge wake as the border of fast and slow fluctuations in the estimates of the ridge regression coefficients. Econometric models were calculated using SPSS Statistics, Mathcad and FAR-AREA 4.0 software. The empirical basis for forecast calculations was the assessment of trends in sunflower production in all categories of farms in the Rostov region of Russia for the period of 2008-2018. The calculation results of econometric models made it possible to develop three author's scenarios for the sunflower production in the region, namely, inertial, moderate, and optimistic ones that consider the export-oriented strategy of the agro-industrial complex.(AU)

O artigo considera modelos econométricos de regressão de rendimento de girassol sensível ao risco sobre o exemplo de uma cultura agrícola orientada para a exportação. Em particular, provamos que apesar da multicolinearidade funcional dos preditores no modelo de rendimento de girassol com relação ao risco causado pelas peculiaridades dos algoritmos dos métodos de análise hierárquica, o procedimento de regressão de cristas permite obter sua especificação completa e fornecer estimativas tendenciosas, mas estáveis dos parâmetros de previsão no caso de variáveis de entrada incertas. Foi comprovado que o valor racional dos parâmetros de deslocamento é conveniente de ser estabelecido usando uma interpretação gráfica da esteira da crista como fronteira das flutuações rápidas e lentas nas estimativas dos coeficientes de regressão da crista. Os modelos econométricos foram calculados usando o software SPSS Statistics, Mathcad e FAR-AREA 4.0. A base empírica para os cálculos de previsão foi a avaliação das tendências da produção de girassol em todas as categorias de fazendas na região de Rostov na Rússia para o período de 2008-2018. Os resultados dos cálculos dos modelos econométricos permitiram desenvolver três cenários de autor para a produção de girassol na região, a saber, os cenários inercial, moderado e otimista que consideram a estratégia orientada à exportação do complexo agroindustrial.(AU)

Assessment of crop damage by rodent pests from experimental barley crop fields in Farta District, South Gondar, Ethiopia.

This study was conducted in Farta district, south Gondar from 2019 to 2020 cropping years to identify rodent pest species and estimate damage caused on barley crops. Four independent barley crop fields (40 x 40 m each) were sampled randomly to estimate the loss. Two were located near Alemsaga Priority State Forest and the other two were away from the forest. Four (2 x 2 m) rodent exclusion plots were established at 10 m interval as control units in each selected experimental barley fields using fine wire mesh. Rodent pest species were collected using both Sherman and snap traps throughout the different crop growing stages. The damaged and undamaged barley tillers by pest rodents were counted on five 1 x 1 m randomly sampled quadrats for each selected experimental fields. Variations on pest rodent population between cropping years and sites were analyzed using Chi square test. The mean crop damages between cropping years and experimental field sites were analyzed using two way ANOVA. Arvicanthis abyssinicus, Mastomys natalensis, Arvicanthis dembeensis, Mus musculus, Lophuromys simensis, Tachyoryctes splendens and Hystrix cristata were identified as pest rodents in the study area. A total of 968 individual rodents (427 in 2019 and 541 in 2020) were trapped during the study period. There was a statistical variation (χ2 = 13.42, df = 1 and P<0.05) between trapped individuals of the two successive years. The crop fields near the forest were more vulnerable than away from the forest during both cropping years. Statistical variations was observed on mean crop losses between cropping years and experimental barley crop sites. The highest crop damage was seen at maturity stage and the lowest during sowing in all experimental plots and cropping years. The percentage of barley yield loss due to rodent pests was 21.7 kg ha-1. The monetary value of this yield loss was equivalent to 4875 Birr (121.9 US$ h-1). Alemsaga Forest as shelter and conservation strategies like free of farmland from livestock and terracing for soil conservation have great role for the high rodent pest populations in the study area. Field sanitation, trapping and using restricted rodenticides like zinc phosphide are the possible recommendation to local farmers against rodent pests.

Agricultural cooperatives participating in vegetable supply chain integration: A case study of a trinity cooperative in China.

Supply chain integration plays an important role in the development of the vegetable industry in terms of vegetable quality, vegetable safety, and vegetable security in rural China. This paper explores how agricultural cooperatives integrate the vegetable supply chain by taking a trinity cooperative as an example in China. It explains the translation concatenation of supply chain integration for this cooperative by constructing actor networks in four development stages, including the seed stage, start-up stage, development stage, and mature stage. The findings show that supply chain integration in production cooperation, supply & sales cooperation, and credit cooperation is a useful trinity cooperative model of supply chain integration for investigating vegetable supply chain integration through internal integration and external integration. This paper suggests that cooperatives in the vegetable supply chain should facilitate close coordination among different shareholders and further improve the efficiency of supply chain integration. The government should provide training opportunities and funding to encourage cooperatives to participate in supply chain integration within the vegetable industry.

Welfare impacts of smallholder farmers' participation in multiple output markets: Empirical evidence from Tanzania.

A relatively large body of literature has documented the welfare effects of smallholder farmers' participation in single-commodity output markets. However, limited empirical evidence is available when smallholder farmers participate in multiple-commodities output markets. We tried to fill this gap in the literature by estimating the impacts of smallholder farmers' contemporaneous participation in both maize and legume markets vis-à-vis in only maize or legume markets using household-level data from Tanzania. Applying a multinomial endogenous switching regression model that allows controlling for observed and unobserved heterogeneity associated with market participation in single-commodity and multiple-commodity markets, results showed that smallholder farmers' participation in both single-and multiple-commodity markets was positively and significantly associated with household income and food security. Moreover, the greatest benefits were obtained when farmers participated in multiple-commodity markets, suggesting the importance of policies promoting diversification in crop income sources to increase welfare and food security. Our findings also signal the complementary-rather than substitute-nature of accessing multiple-commodity markets for enhancing household livelihoods under a specialization strategy. Finally, important policy implications are suggested, from promoting and supporting public infrastructure investments to expanding road networks to reduce transportation costs, especially in remote communities, to enhance smallholder farmer access to profitable maize and legume markets in Tanzania.

Reduced pests, improved grain quality and greater total income: benefits of intercropping rice with Pontederia cordata.

BACKGROUND: Intercropping, which is growing two or more different crops in the same field simultaneously, is an effective traditional agricultural practice for productivity, resource utilization, and pest control. However, study on intercropping in paddy fields is limited. So in this study, field experiments of 2 years/four seasons (early and late seasons in 2016 and 2017) were conducted to examine the effects of rice-Pontederia cordata intercropping on rice plant growth, pest control, yield, income, and grain quality. RESULTS: We found rice-P. cordata intercropping significantly decreased the occurrence of rice diseases and pests, with a 22.0-45.9% reduction in sheath blight and a 33.8-34.4% reduction in leaf folders. The mean land equivalent ratio (LER) (1.09) result indicates that intercropping rice and P. cordata generated positive yield effects. In addition, due to the economic profit from the replacement stripe of P. cordata in the rice paddy field, intercropping rice with P. cordata could greatly enhance farmer income. The average total income of rice intercropped with P. cordata was 2.5-fold higher than that of rice monoculture. Furthermore, intercropping significantly improved grain quality compared with the rice monoculture. It significantly increased the milled rice rate and whole milled rice rate by 11.2% and 12.8%, respectively, but decreased the chalky rice rate by 30.9-39.8% and chalkiness degree by 32.2%. CONCLUSIONS: We suggest that rice-P. cordata intercropping provides an environmentally effective way to control rice diseases and pests, results in higher overall productivity and total income, and improves grain quality. © 2021 Society of Chemical Industry.

Potassium nutrient response in the rice-wheat cropping system in different agro-ecozones of Nepal.

Most of the soils of Nepal had a higher potassium (K, expressed as K2O) level inherently. Later in 1976, the Government of Nepal has recommended K fertilizer rate at 30 kg K2O ha-1 in rice-wheat cropping systems. However, those crops began showing K deficiency symptoms in recent decades, which could be due to a large portion of soils with depleted K level or the insufficient input of K fertilizer for crop production. This study explored a limitation of K nutrient in the crops by establishing field trials from 2009-2014 at three agro-ecozones i.e., inner-Terai (2009-2010), high-Hills (2011-2012), and Terai (2012-2014) in Nepal. Seven rates of K fertilizer at 0, 15, 30, 45, 60, 75, and 90 kg K2O ha-1 were replicated four times in a randomized complete block design, where crop yields and yield-attributing parameters of rice-wheat cropping system were recorded. Results revealed that an increase in K rates from 45 to 75 kg K2O ha-1 under inner-Terai and Terai conditions and 45 to 60 kg ha-1 under high-Hills conditions produced significantly higher grain yields compared to the recommended K dose. Economically, the optimum rate of K fertilizer should not exceed 68 kg K2O ha-1 for rice in all agro-ecozones, or 73 kg K2O ha-1 for wheat in inner-Terai and 60 kg K2O ha-1 for wheat in high-Hills and Terai. Our findings suggest to increase potassium application in between 1.5 to 2.5 times of the current K fertilizer rate in rice-wheat cropping system of Nepal that need to be tested further in different locations and crop varieties.

Impact of transnational land acquisitions on local food security and dietary diversity.

Foreign investors have acquired approximately 90 million hectares of land for agriculture over the past two decades. The effects of these investments on local food security remain unknown. While additional cropland and intensified agriculture could potentially increase crop production, preferential targeting of prime agricultural land and transitions toward export-bound crops might affect local access to nutritious foods. We test these hypotheses in a global systematic analysis of the food security implications of existing land concessions. We combine agricultural, remote sensing, and household survey data (available in 11 sub-Saharan African countries) with georeferenced information on 160 land acquisitions in 39 countries. We find that the intended changes in cultivated crop types generally imply transitions toward energy-rich, but nutrient-poor, crops that are predominantly destined for export markets. Specific impacts on food production and access vary substantially across regions. Deals likely have little effect on food security in eastern Europe and Latin America, where they predominantly occur within agricultural areas with current export-oriented crops, and where agriculture would have both expanded and intensified regardless of the land deals. This contrasts with Asia and sub-Saharan Africa, where deals are associated with both an expansion and intensification (in Asia) of crop production. Deals in these regions also shift production away from local staples and coincide with a gradually decreasing dietary diversity among the surveyed households in sub-Saharan Africa. Together, these findings point to a paradox, where land deals can simultaneously increase crop production and threaten local food security.

Interactive Web-based Data Visualization and Analysis Tool for Synthetizing on-farm Research Networks Data.

The on-farm research network concept enables a group of farmers to test new agricultural management practices under local conditions with support from local researchers or agronomists. Different on-farm trials based on the same experimental design are conducted over several years and sites to test the effectiveness of different innovative management practices aimed at increasing crop productivity and profitability. As a larger amount of historical trial data are being accumulated, data of all the trials require analyses and summarization. Summaries of on-farm trials are usually presented to farmers as individual field reports, which are not optimal for the dissemination of results and decision making. A more practical communication method is needed to enhance result communication and decision making. R Shiny is a new rapidly developing technology for turning R data analyses into interactive web applications. For the first time for on-farm research networks, we developed and launched an interactive web tool called ISOFAST using R Shiny. ISOFAST simultaneously reports all trial results about the same management practice to simplify interpretation of multi-site and multi-year summaries. We used a random-effects model to synthetize treatment differences at both the individual trial and network levels and generate new knowledge for farmers and agronomists. The friendly interface enables users to explore trial summaries, access model outputs, and perform economic analysis at their fingertips. This paper describes a case-study to illustrate how to use the tool and make agronomic management decisions based on the on-farm trial data. We also provided technical details and guidance for developing a similar interactive visualization tool customized for on-farm research network. ISOFAST is currently available at https://analytics.iasoybeans.com/cool-apps/ISOFAST/.

Assessing whether the best land is cultivated first: A quantile analysis.

Classical land rent theories imply that the best land is cultivated first. This principle forms the basis of many land-use studies, but empirical evidence remains limited, especially on a global scale. In this paper, we estimate the effects of agricultural suitability and market accessibility on the spatial allocation of cultivated areas at a 30 arc-min resolution in 15 world regions. Our results show that both determinants often have a significant positive effect on the cropland fraction, but with large variations in strength across regions. Based on a quantile analysis, we find that agricultural suitability is the dominant driver of cropland allocation in North America, Middle East and North Africa and Eastern Europe, whereas market accessibility shows a stronger effect in other regions, such as Western Africa. In some regions, such as South and Central America, both determinants have a limited effect on cropland fraction. Comparison of high versus low quantile regression coefficients shows that, in most regions, densely cropped areas are more sensitive to agricultural suitability and market accessibility than sparsely cropped areas.

Postharvest practices, challenges and opportunities for grain producers in Arequipa, Peru.

Little is known about the major issues leading to postharvest losses in Peru, which are estimated to be 15-27%. We surveyed 503 farmers from the lowlands and Andean regions of Arequipa to learn more about the major grains produced and issues encountered during drying and storage. Rice, common bean, and quinoa were the most grown crops in the lowlands while starchy maize was the most cultivated crop in the highlands. Most farmers (90%) dried their crops in-field directly on the ground, which exposes them to rodents, birds, and insect pests. The majority of farmers (92%) used subjective methods to assess grain moisture content. About 77% of farmers identified insects as a major challenge during storage but only 44% said they used preventive measures such as the application of insecticides. Among farmers who stored grain, the main reason was for household consumption (61%); while among those who did not store, the main reason was the need for immediate cash at harvest (75%). Farmers who experienced insect problems, who stored seed or grain for sale, who stored longer, or farmers from the lowlands were more likely to apply insecticides on their stored products. These findings provide an opportunity for researchers, development organizations, and government agencies to improve postharvest handling and storage in Arequipa by disseminating drying technologies, moisture assessment tools and hermetic storage solutions among farmers.