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Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low- and middle-income countries, crop yields have traditionally been assessed based on farmer-reported production and land areas in household/farm surveys, occasionally by objective crop cuts for a sub-section of a farmer’s plot, and rarely using full-plot harvests. In parallel, satellite data continue to improve in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study evaluates ground- and satellite-based approaches to estimating crop yields and yield responsiveness to inputs, using data on maize from Eastern Uganda. Using unique, simultaneous ground data on yields based on farmer reporting, sub-plot crop cutting, and full-plot harvests across hundreds of smallholder plots, we document large discrepancies among the ground-based measures, particularly among yields based on farmer-reporting versus sub-plot or full-plot crop cutting. Compared to yield measures based on either farmer-reporting or sub-plot crop cutting, satellite-based yield measures explain as much or more variation in yields based on (gold-standard) full-plot crop cuts. Further, estimates of the association between maize yield and various production factors (e.g., fertilizer, soil quality) are similar across crop cut- and satellite-based yield measures, with the use of the latter at times leading to more significant results due to larger sample sizes. Overall, the results suggest a substantial role for satellite-based yield estimation in measuring and understanding agricultural productivity in the developing world.

This study evaluates the labor response of rural households participating in the Grain-for-Green program in China, the largest payments for ecosystem services program in the developing world. Using a panel data set that we designed and implemented, we find that the participating households are increasingly shifting their labor endowment from on-farm work to the off-farm labor market. However, the effects vary depending on the initial level of human and physical capital. The results support the view that one reason why the participants are more likely to find off-farm employment is because the program is relaxing households' liquidity constraints.

The Indonesian government committed to restoring over 2 million ha of degraded peatland by the end of 2020, mainly to reduce peat fires and greenhouse gas emissions. Although it is unlikely the government will meet this target, restoration projects are still underway. One restoration strategy involves blocking peatland drainage canals, but the consequences of this for smallholder farmers whose livelihoods are dependent on agriculture are unclear. This paper investigates perceived impacts of canal blocks on smallholder farmers and identifies factors that affect their willingness to accept canal blocks on their land. We use data from 181 household questionnaires collected in 2018 across three villages in Jambi province, Sumatra. We found that the majority of respondents would accept canal blocks on their farms, perceiving that the blocks would have no impact on yields or farm access, and would decrease fire risk. Respondents who would not accept blocks on their farms were more likely to use canals to access their farms and perceive that canal blocks would decrease yields. The majority of farmers unwilling to accept canal blocks did not change their mind when provided with an option of a block that would allow boat travel. Our results improve understanding of why some smallholders may be unwilling to engage with peatland restoration. Further research is needed to understand the impact of canal blocks on smallholders’ yields. Engaging with stakeholders from the outset to understand farmers’ concerns, and perceptions is key if the government is to succeed in meeting its peatland restoration target and to ensure that the costs and benefits of restoration are evenly shared between local stakeholders and other actors.

Scientific data concerning climate change are critical for designing mitigation and adaptation strategies. Equally important is how stakeholders perceive climate change because perceptions influence decision-making. In this paper, we employ spatially-delineated primary surveys to evaluate weather perception biases among corn and soybean farmers located on western frontier of the U.S. Corn Belt where substantial loss of grassland has been documented. We characterize farmers’ perception biases by measuring the gap between survey-based perception reports for three distinct weather indicators (i.e., temperature, precipitation and drought) and corresponding meteorological evidence. About 70% farmers in our sample misperceive past weather changes. Three-fourths of these misperceiving farmers over-estimate local temperatures and drought frequency and 40% of them under-estimate precipitation trends relative to past records. We further find evidence that farmers’ weather change perceptions are systematically biased in a manner that would justify past land use decisions. Particularly, higher cropping incidence on previously protected grasslands effected more farmers to under-perceive drier conditions and over-perceive wetter conditions. Our investigation of perception biases across distinct weather indicators with a reference to past economic decisions enriches the understanding of climate change perceptions and related policies.

Purpose The purpose of this paper is to investigate the impact of mechanization services on farm productivity in Northern China from an empirical perspective, with the aim to identify the underlying market and institutional barriers. Design/methodology/approach The authors apply the regression method with the control of village fixed effects to examining the relationship between capital–labor ratio, mechanization service ratio and farm productivity, using the panel data collected in 2013 and 2015 by CCAP. Findings Mechanization services improve farm productivity through substituting labor, but it may generate a less positive impact on farms who do not have self-owned capital equipment. Originality/value It is the first study to investigate how mechanization services affect farm productivity for grain producers in Northern China.

This paper investigates the effects of crop genetic diversity on farm productivity and production risk in the highlands of Ethiopia. Using a moment-based approach, the analysis uses a stochastic production function capturing mean, variance, and skewness effects. Welfare implications of diversity are evaluated using a certainty equivalent, measured as expected income minus a risk premium (reflecting the cost of risk). We find that the effect of diversity on skewness dominates its effect on variance, meaning that diversity reduces the cost of risk. The analysis also shows that the beneficial effects of diversity become of greater value in degraded land.

Despite widespread adoption of genetically modified crops in many countries, heated controversies about their advantages and disadvantages continue. Especially for developing countries, there are concerns that genetically modified crops fail to benefit smallholder farmers and contribute to social and economic hardship. Many economic studies contradict this view, but most of them look at short-term impacts only, so that uncertainty about longer-term effects prevails. We address this shortcoming by analyzing economic impacts and impact dynamics of Bt cotton in India. Building on unique panel data collected between 2002 and 2008, and controlling for nonrandom selection bias in technology adoption, we show that Bt has caused a 24% increase in cotton yield per acre through reduced pest damage and a 50% gain in cotton profit among smallholders. These benefits are stable; there are even indications that they have increased over time. We further show that Bt cotton adoption has raised consumption expenditures, a common measure of household living standard, by 18% during the 2006–2008 period. We conclude that Bt cotton has created large and sustainable benefits, which contribute to positive economic and social development in India.

A survey regarding general management, sire selection, reproductive management, inseminator training and technique, heat abatement, body condition scoring, facility design and grouping, nutrition, employee training and management, and animal health and bio-security was carried out from March to September of 2004 in 153 herds in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program. A total of 103 herds (67.3%) completed the survey. Herd size was 613±46 cows, with herds located in Wisconsin (26), California (12), New York (11), Minnesota (10), Michigan (7), Washington (6), Pennsylvania (6), Iowa (5), Idaho (5), Texas (4), Ohio (4), and other states (7). These farms sold 34.5±0.3kg of milk/d per cow, with an annual culling rate of 34±1% and a calving interval of 13.8±0.1 mo. Cows were observed for estrus 2.8±0.3 times/d, for a duration of 27±4min, but 78% of the respondents admitted that detection of estrus was not the employee's sole responsibility at that time. Managers tried to achieve pregnancy until 8.8±0.9 failed inseminations, 300±26 d postpartum, or milk yield <17.7±0.5 kg/d. Nonpregnant cows were culled at 326±36 d postpartum or milk yield <16.4±0.3 kg/d. Mean durations of the voluntary waiting period were 52±1.3 and 53±1.4 d for primiparous and multiparous cows, respectively. Hormonal synchronization or timed artificial insemination programs were used in 87% of the herds, with 86% synchronizing first services, 77% resynchronizing repeat services, and 59% treating cystic, anestrous, or anovular cows. Finding good employees was identified as the greatest labor challenge, followed by training and supervising employees. Mastitis and hairy heel warts were noted as the greatest animal health concerns, followed by lameness, abortions, and death losses, whereas the greatest reproductive challenges were artificial insemination service rate, conception rate, twinning, and retained placenta or metritis. Results of this study can provide a useful benchmark or reference with regard to commonly used management practices on large commercial US dairy farms at the present time.

Agriculture is responsible for nearly one-quarter of global greenhouse gas (GHG) emissions, with livestock and poultry systems contributing significantly through methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2). Achieving net-zero agriculture demands tools that not only quantify emissions but also guide management decisions and foster behavioral change. The Cool Farm Tool (CFT)—a science-based calculator for farm-level carbon footprints, water use, and biodiversity—has been widely adopted across Europe and parts of the United States. Yet, despite its proven potential, no Canadian studies have tested or adapted CFT, leaving a major gap in the country’s progress toward climate-smart farming. This paper addresses that gap by presenting the first surveys of poultry and dairy producers in Atlantic Canada as a foundation for tailoring and localizing CFT. Our mixed-methods surveys examined farm practices, feed, manure, energy use, waste management, sustainability perceptions, and openness to digital tools. Results on 23 responses (20 for poultry, 3 for dairy) revealed limited awareness but moderate interest in emission tracking: dairy farmers, already accustomed to digital systems such as robotic milking and herd software, were receptive and confident about adopting CFT. Poultry farmers, by contrast, voiced greater concerns over cost, complexity, and uncertain benefits, signaling higher adoption barriers in this sector. These findings highlight both the opportunity and the challenge: while dairy farms appear ready for rapid uptake, poultry requires stronger incentives, clearer value demonstration, and sector-specific customization. We conclude that adapting CFT with regionally relevant data, AI-driven decision support, and supportive policy frameworks could make it a cornerstone for achieving net-zero agriculture in Atlantic Canada.

Failure of passive transfer of immunity (FPT) in dairy replacement calves has been linked to increased neonatal morbidity and mortality and long-term decreases in productivity. The purpose of this study was to estimate the prevalence of FPT in US dairy heifer calves in 2007 and to use nationally representative data to investigate associations of FPT with colostrum and calf management practices. A cross-sectional study was conducted by the USDA's National Animal Health Monitoring System between January and August 2007. Producers from 394 operations in 17 states completed survey questions about colostrum and calf management practices, and serum samples were collected from 1,816 healthy heifer calves on those operations. Serum immunoglobulin G (IgG) levels were determined by radial immunodiffusion, and calves were classified as having FPT if the IgG concentration was less than 10mg/mL. To investigate associations between FPT and management practices, a multivariable analysis was completed using a weighted logistic regression model. The estimated prevalence of FPT in US dairy heifer calves was 19.2%. The odds of FPT were higher for calves on operations that pooled colostrum [odds ratio (OR = 2.2)], allowed nursing (OR = 2.4), or hand fed colostrum more than 4h after birth (OR = 2.7). The odds of FPT were also higher for calves on operations that did not provide a source of heat during cold weather for calves experiencing a dystocia (OR = 1.6), would not seek veterinary assistance when unable to correctly position a calf for delivery (OR = 2.6), or did not routinely monitor serum proteins in calves as a measure of passive transfer (OR = 13.8). The prevalence of FPT in dairy heifer calves has decreased in the last 15 yr, so progress has been made in this important area of calf management. This study identified several management practices associated with FPT that could be targeted for educational campaigns or further research.