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Using weekly price data from 97 Nigerian markets, we examine how seasonal harvest timing shapes price dynamics for staple grains using a dyadic panel design. Our analysis reveals that markets operating in the same harvest phase experience faster price convergence, while asynchronous seasonal conditions slow adjustments—particularly for local rice and cowpea. In contrast, imported long-grain rice shows stable price behavior throughout the year. These results highlight the critical influence of seasonal cycles on market integration and offer fresh insights for food security strategies.

Legume seed systems in many developing countries are characterized by low availability of certified seeds because the private sector is often absent, and the public sector has limited capacity to produce such seeds. Farmer seed enterprises (FSEs) are therefore increasingly promoted as alternative suppliers of certified and in some instances, quality declared and truthfully labelled seeds. In this study, we assess the commercial viability of FSEs that produce chickpea and green gram certified seeds by comparing average seed production cost, inclusive of opportunity costs and expected profits, with consumers’ willingness to pay (WTP) price. The cost of seed production data come from a survey of 63 FSEs and the data on WTP are from the Becker, DeGroot, Marschak (BDM) bidding experiments conducted with 512 farmers from the Central Dry Zone of Myanmar. We find that the post-harvest storage cost during the 7–8 months between harvest and the next planting season contributes significantly to the total cost of producing seeds. Forty-seven percent of chickpea farmers and 53% of green gram farmers were willing to pay equal to or higher than the average minimum cost of producing certified seeds. which is as an upper bound estimate of potential market share for FSEs’ certified seeds. This potential customer base of FSEs can be further increased by reducing the cost, especially post-harvest and labor costs. What role government, private companies, and NGOs could play in reducing the cost and increasing the demand for certified seed are important policy research questions discussed in the paper.

New estimates of the impacts of germplasm improvement in the major staple crops between 1965 and 2004 on global land-cover change are presented, based on simulations carried out using a global economic model (Global Trade Analysis Project Agro-Ecological Zone), a multicommodity, multiregional computable general equilibrium model linked to a global spatially explicit database on land use. We estimate the impact of removing the gains in cereal productivity attributed to the widespread adoption of improved varieties in developing countries. Here, several different effects—higher yields, lower prices, higher land rents, and trade effects—have been incorporated in a single model of the impact of Green Revolution research (and subsequent advances in yields from crop germplasm improvement) on land-cover change. Our results generally support the Borlaug hypothesis that increases in cereal yields as a result of widespread adoption of improved crop germplasm have saved natural ecosystems from being converted to agriculture. However, this relationship is complex, and the net effect is of a much smaller magnitude than Borlaug proposed. We estimate that the total crop area in 2004 would have been between 17.9 and 26.7 million hectares larger in a world that had not benefited from crop germplasm improvement since 1965. Of these hectares, 12.0-17.7 million would have been in developing countries, displacing pastures and resulting in an estimated 2 million hectares of additional deforestation. However, the negative impacts of higher food prices on poverty and hunger under this scenario would likely have dwarfed the welfare effects of agricultural expansion.

Common bean ( Phaseolus vulgaris L.) is an important staple crop for smallholder farmers, particularly in Eastern and Southern Africa. To support common bean breeding and seed dissemination, a high throughput SNP genotyping platform with 1500 established SNP assays has been developed at a genotyping service provider which allows breeders without their own genotyping infrastructure to outsource such service. A set of 708 genotypes mainly composed of germplasm from African breeders and CIAT breeding program were assembled and genotyped with over 800 SNPs. Diversity analysis revealed that both Mesoamerican and Andean gene pools are in use, with an emphasis on large seeded Andean genotypes, which represents the known regional preferences. The analysis of genetic similarities among germplasm entries revealed duplicated lines with different names as well as distinct SNP patterns in identically named samples. Overall, a worrying number of inconsistencies was identified in this data set of very diverse origins. This exemplifies the necessity to develop and use a cost-effective fingerprinting platform to ensure germplasm purity for research, sharing and seed dissemination. The genetic data also allows to visualize introgressions, to identify heterozygous regions to evaluate hybridization success and to employ marker-assisted selection. This study presents a new resource for the common bean community, a SNP genotyping platform, a large SNP data set and a number of applications on how to utilize this information to improve the efficiency and quality of seed handling activities, breeding, and seed dissemination through molecular tools.

This study assesses preferences for COVID‐19 pandemic recovery policies from four key groups representing the upstream (input retailers), farm (farmers), and downstream (millers and traders) levels of Myanmar's agri‐food‐system using the best–worst scaling (BWS) method. Our results show that nonrestrictive policies such as maintaining open international borders and allowing businesses to stay open are preferred to cash transfers and free COVID‐19 vaccination. However, there is considerable heterogeneity across groups, and group characteristics matter more than individual characteristics in shaping policy preferences. This paper highlights the need for careful consideration of diverse stakeholder perspectives in designing recovery policies.

Common bean is the most important legume crop for human consumption around the world. For this reason, bean breeders are challenged with increasing bean production while facing new problems like climate change. Guatemalan climbing beans have been suggested to represent a previously undefined race in the Middle American gene pool that may represent an untapped source of alleles for bean improvement that can contribute to solving production problems affecting both developed and developing countries. The genetic diversity, population structure, and genetic differentiation of two Guatemalan climbing bean collections were analyzed with ~ 45,000 SNPs markers and confirmed the existence of race Guatemala in the Middle American gene pool and its differentiation from other races. Further analysis using geospatial data, showed that elevation was an important factor when defining the population structure of race Guatemala beans.

This study investigates how quality signaling, through packaging and lab test labels, affects farmers' willingness to pay (WTP) for certified legume seeds in Myanmar. Using Becker‐DeGroot‐Marschak experiments with 500 chickpea and green gram farmers, results show that packaging and lab test labeling increase WTP for green gram seeds by 8%–12% but have no significant effect for chickpea. Despite low current usage, 42% of green gram and 23% of chickpea farmers are willing to pay above market prices, indicating strong demand. Farmer seed enterprises, offering the lowest prices, are best positioned to meet this demand with an effective quality signaling strategy.

Background Accurate identification of crop cultivars is crucial in assessing the impact of crop improvement research outputs. Two commonly used identification approaches, elicitation of variety names from farmer interviews and morphological plant descriptors, have inherent uncertainty levels. Genotyping-by-sequencing (GBS) was used in a case study as an alternative method to track released varieties in farmers' fields, using cassava, a clonally propagated root crop widely grown in the tropics, and often disseminated through extension services and informal seed systems. A total of 917 accessions collected from 495 farming households across Ghana were genotyped at 56,489 SNP loci along with a \"reference library\" of 64 accessions of released varieties and popular landraces. Results Accurate cultivar identification and ancestry estimation was accomplished through two complementary clustering methods: (i) distance-based hierarchical clustering; and (ii) model-based maximum likelihood admixture analysis. Subsequently, 30 % of the identified accessions from farmers' fields were matched to specific released varieties represented in the reference library. ADMIXTURE analysis revealed that the optimum number of major varieties was 11 and matched the hierarchical clustering results. The majority of the accessions (69 %) belonged purely to one of the 11 groups, while the remaining accessions showed two or more ancestries. Further analysis using subsets of SNP markers reproduced results obtained from the full-set of markers, suggesting that GBS can be done at higher DNA multiplexing, thereby reducing the costs of variety fingerprinting. A large proportion of discrepancy between genetically unique cultivars as identified by markers and variety names as elicited from farmers were observed. Clustering results from ADMIXTURE analysis was validated using the assumption-free Discriminant Analysis of Principal Components (DAPC) method. Conclusion We show that genome-wide SNP markers from increasingly affordable GBS methods coupled with complementary cluster analysis is a powerful tool for fine-scale population structure analysis and variety identification. Moreover, the ancestry estimation provides a framework for quantifying the contribution of exotic germplasm or older improved varieties to the genetic background of contemporary improved cultivars.