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Rural credit, food security, and resilience: An empirical evaluation from Kenya
No full textIn this paper, we examine the role of credit in enhancing rural households’ food security and resilience. In so doing, we consider resilience as a higher order capacity outcome, different from traditional development outcomes associated with households’ or individuals’ welfare. We evaluate the effectiveness of two types of agricultural production credit products, one a traditional credit and one that is linked to rainfall index insurance to protect borrowers against the adverse effects of drought. Based on a randomized controlled trial conducted in Machakos county, Kenya, we report both intent-to-treat effects as well as local average treatment effects to demonstrate the impacts of these credit products not only among borrowers, but the broader effects of expanding rural credit markets. We see generally low levels of food security resilience among our sampled households, but we find compelling evidence that credit and expanded credit markets more broadly had beneficial impacts on enhancing households’ food security and resilience. Despite the differences in the two credit products being evaluated, we do not find an appreciable difference in the effects of the two credit types, concluding that the expansion of affordable agricultural credit markets should be among the key policy tools for building resilience among rural smallholders.44 page
Maize under heat stress in lowland tropics: Learnings and the way forward
No full textThe two main factors contributing to heat stress are higher temperatures and low relative humidity at high temperatures. Growing almost year-round, maize crops in the lowland tropics are exposed to rising temperatures, negatively affecting crop productivity, especially under rainfed conditions. Studies have identified several morphological, biochemical, and physiological changes in field crops, including maize under heat stress. Among these, a few changes enable plants to adapt to heat stress (stress-adaptive traits), while others exhibit adverse effects of stress (stress-responsive traits). At the biochemical level, heat stress results in increased levels of superoxide dismutase (SOD) and catalase enzyme activities in cells, as well as elevated levels of Heat Shock Proteins (HSPs). Options have been identified to mitigate the effects of heat stress on maize crops, such as suitable planting time to avoid a high-temperature regime coinciding with critical crop growth stages, furrow sowing, and frequent irrigation to maintain a vital minimum relative humidity in the air. Efforts on genetic improvement for heat tolerance in maize resulted in the development of new heat-tolerant maize hybrids, which can thrive at temperatures beyond threshold limits for tropical maize and suffer relatively less under heat stress. However, the challenge remains mainly due to low genotypic variability for stress in elite maize germplasm and strong genotype-by-environment interaction under heat stress, resulting from varying vapor pressure deficits (VPD) at high temperatures. Therefore, diving deeper and exploring local landraces and wild accessions is necessary to explore wider genotypic variation for heat stress tolerance in tropical maize. Recent advances in genomics-assisted breeding may help identify genomic regions associated with heat stress tolerance in maize and target the introgression of validated genomic regions into elite maize germplasm to develop the next generation of maize cultivars with improved, stable performance under heat stress conditions. In this article, we reviewed the progress and key findings on various aspects of research on heat stress in field crops, with an emphasis on tropical maize, which may help refine the approaches of research programs working on heat stress and aiming to develop crop varieties with improved tolerance to heat stress.876-88
Onerice breeding framework: an end-to-end system to develop better varieties faster
No full textBreeding in the Consultative Group on International Agricultural Research (CGIAR) system is an intricate process that integrates the contributions of market research, pre-breeding, breeding, breeding operations, and seed systems. Therefore, a well-defined framework is critical for the effective and efficient operation of a breeding program. The OneRice Breeding Framework developed at the International Rice Research Institute (IRRI) integrates these components, from initial market research to establish breeding goals, creating breeding strategies for improved product design and development, and swiftly testing and replacing products through effective seed systems. The framework represents a cutting-edge breeding approach that offers comprehensive guidance on harnessing modern tools and technologies, including genomic selection, speed breeding, sparse testing, and so on. Additionally, the framework outlines strategies for systematically integrating novel genetic variation into elite breeding programs through pre-breeding efforts. It is adaptable across different crops and is dynamic, allowing adjustments in the breeding program based on target objectives, resource availability, and tools. The OneRice Breeding Framework is a comprehensive end-to-end framework that integrates all the components to enhance genetic gains and develop and disseminate better products faster to address food, nutrition, and income security. Consequently, the OneRice Breeding Framework is the fundamental blueprint for modern rice (Oryza sativa) crop breeding
Understanding seed selection decisions among small-scale maize farmers in Machakos County, Kenya: the dominance of market leader varieties
No full textIntroduction: The maize seed market in Kenya is highly competitive, yet older varieties dominate smallholder farmers’ preferences. The current study aimed to identify the key drivers of maize seed selection by examining trait priorities, prior experience, purchase behavior, and sociodemographic profiles of farmers across different seed variety groups. Methods: Farmers were categorized into three groups based on their preferred maize varieties: market leader, competitor, and low-cost. A multinomial logit model was used for inferential analysis. Results: The results revealed that 70% of the farmers preferred market leader varieties, while 21% preferred competitor varieties and 7% chose low-cost varieties. Drought tolerance emerged as the most valued trait, reported by 72% of farmers. In addition, farmers reported little experience with different maize seed varieties and hybrids. Trait preferences, previous knowledge and farm size primarily significantly influenced seed selection. Regarding purchasing behavior, most farmers made quick decisions at a mock agro-dealer store, often disregarding price offers and informational posters when their preferred variety was available. Discussion: This study provides a basis for developing strategies that encourage and influence farmers to broaden their maize seed choice considerations which will ultimately improve domestic maize production as climate change continues. It aimed to understand better the factors influencing farmers’ loyalty to market leader maize varieties in Machakos County, Kenya
Conservation agriculture can enhance maize productivity in high-rainfall regions: Nine-year evidence from Northern Zambia
No full textConservation Agriculture (CA) is often perceived to underperform in high-rainfall regions, leading to limited research and promotion in such environments. In Zambia, most CA studies have focused on Southern and Eastern regions, with little emphasis on Northern Zambia, despite its need for improved productivity and sustainability. Understanding CA's performance in high-rainfall areas is critical for sustainable agricultural intensification. This nine-year study in Northern Zambia evaluated the effects of cropping systems and rainfall variability on maize productivity, soil pH, and soil organic carbon (SOC) using a randomized complete block design. Three CA-based cropping systems were compared to two conventional tillage systems. Yearly precipitation showed significant interannual variability, influencing maize grain yield in a complex cubic response pattern, highlighting nonlinear interactions between cropping systems and rainfall. CA-based systems generally outperformed conventional tillage, particularly in moderate to below-average rainfall years, demonstrating resilience under drier conditions. However, conventional ridge and furrow tillage outperformed CA systems during exceptionally high rainfall years, likely due to better drainage. Over time, yield declines indicated soil fertility depletion, though CA-based systems slowed this decline compared to conventional tillage. Rainfall was identified as a primary driver of cropping system performance, with CA-based systems performing better in below-average to moderate rainfall years and tillage-based systems in excessive rainfall years. Soil pH increased significantly under basin planting at 5–15 cm and 30–60 cm depths, while SOC accumulation was highest at 60–90 cm under ridge and furrow tillage. These findings suggest that while CA can enhance maize productivity in high-rainfall regions, site-specific management strategies are needed to mitigate waterlogging and sustain soil fertility. Further research is needed to explore soil-water dynamics and optimize CA practices under varying rainfall regimes
Resistance of maize (Zea mays L.) genotypes against ear rot causing pathogens in Southern and Western Ethiopia
No full textMaize production and productivity in western and southwestern parts of Ethiopia is affected by, the potential outbreaks of major diseases such as ear rot caused by Fusarium spp., dominantly Fusarium and Gibberella ear rots. Hence, maize genotypes including (commercial hybrids, open pollinated varieties (OPVs) and elite pre commercial hybrids) collected from Ethiopia were evaluated at Bako, Jimma and Hawassa Agricultural Research Centers in 2021 and 2022 cropping seasons to assess their resistance to Gibberella ear rot (GER) and Fusarium ear rot (FER). Local isolates of F. verticillioides and F. meridionale were used and the genotypes were inoculated by introducing conidial suspensions into the silk channels of the primary ears. Twenty (20) maize genotypes were used in this study arranged in split-plot design in all the environments. Maize genotypes were randomly assigned to main plots units and fungal species to subplot units. Result showed that maize genotypes exhibited resistant (R), moderately resistant (MR), moderately susceptible (MS) and susceptible (S) reactions to the inoculation. The percentage of resistant maize genotypes ranged from 25 to 45% for GER and 15 to 25%for FER across different environments. The genotypes BH661, BHQP548, CML 395/CML 202//CML 536-#, Damot (P3506W), DK 777, and Gibe3 exhibited lesser disease severity (R or MR) in most of the environments than did the susceptible genotypes (CML 395/CML202//P3812W(F2)-24-2-2-1-1-1-B-#, BH660, and BHQPY545) across all environments. Only one hybrid (BH660) showed high susceptibility to F. verticillioides, and another (BHQPY545) displayed high susceptibility to F. meridionale at Hawassa and Jimma. From the present study, it can be concluded that, the majority of maize cultivars displayed susceptibility to ear rot caused by at least one of these Fusarium spp. in most environments. Additionally, FER severity was significantly (P < 0.001) and positively (r = 0.45) associated with GER severity, suggesting that both pathogens share the same mechanisms of disease resistance. Moreover, agronomic traits such as kernel texture (r = 0.401, 0.261), ear aspect (r = 0.024, 0.310), husk cover (r = 0.147, 0.268), date of anthesis (r = 0.149, 0.09), and date of silking (r = 0.153, 0.09) were positively and significantly (p < 0.001) associated with GER and FER severity, respectively. While ear height was significantly (p < 0.001) and negatively (r = -0.164, -0.158) associated with GER and FER severity, respectively. Thus, selecting for resistance to one fungal species would likely result in indirect selection for resistance to the other fungal species. Therefore, it is suggested that, the usage of these maize genotypes in traditional breeding programs might face challenges due to undesirable gene linkages. Hence, further research on molecular markers may be necessary to overcome these obstacles and fully leverage the potential of these genotypes in breeding programs in the country
Development of a FER0.4K SNP array for genomic predication of Fusarium ear rot resistance in maize
No full textFusarium ear rot (FER) caused by Fusarium species severely reduces grain yield and quality of maize. Genome prediction (GP), a promising tool for quantitative trait breeding in plants and animals, uses molecular markers for capturing quantitative trait loci and predicting the genetic value of candidates for selection. In the present study, different subsets of markers and statistical methods for GP accuracy were tested in diverse inbred populations for FER resistance using a five-fold cross-validation approach. The prediction accuracy increased with an increase in the number of random markers; however, an increase in number beyond 10K did not increase the prediction accuracy. The prediction accuracy of selected markers was higher than that of random markers, and 500–1000 selected markers had the highest prediction accuracy, beyond which it slowly decreased. Although there was no difference among statistical methods when using selected markers at high prediction accuracy, significant differences were observed when using random markers. On this basis, a liquid chip named FER0.4K (liquid chip for genomic prediction of FER) containing 381 SNPs was developed for low-cost, high-throughput genotyping, with a prediction of approximately 0.82. The statistical method of genome prediction was compiled into a web-based, easy-to-use statistical analysis software using the “shiny” package in R. In summary, this study provides a foundation for FER resistance breeding in maize and offers new insights into the genetic improvement of other complex quantitative traits in plants.996-100
Cover crop functional trait plasticity in response to soil conditions and interspecific interactions
No full textBackground and aims: Cover crops support ecosystem services in agroecosystems, but their performance can be highly variable. Functional trait ecology provides a useful framework for understanding variation in cover crop performance across different growing conditions. However, trait variation within species remains understudied compared to variation between species. Methods: In a two-year experiment, we measured nine functional traits for three cover crop species across 13 fields on working farms that spanned a gradient of soil health. Each field contained three cover crop treatments: a functionally diverse mixture of cereal rye (Secale cereale), crimson clover (Trifolium incarnatum), and dwarf-essex rapeseed (Brassica napus), and rye and clover monocrops. We evaluated i) the magnitude and relative importance of intraspecific and interspecific trait variation; ii) which soil health indicators best explained trait variation; and iii) whether interspecific interactions in mixture induced trait plasticity. Results: Despite strong trait contrasts between species, intraspecific trait variation comprised 50% of total trait variation, on average. Trait variation was best explained by particulate organic matter nitrogen (POM N), soil phosphorus, pH, and permanganate oxidizable carbon for clover; by POM N and soil phosphorus for rye; and by POM N for dwarf essex. Rye and clover also showed significant trait plasticity in mixture relative to monocrop treatments. Conclusion: Our study demonstrates that intraspecific and interspecific trait variation are equally important, and that examining trait variation within species can improve the ability to predict cover crop outcomes. This information can inform cropping system design in distinct contexts to promote success of component species and complementary ecosystem functions.1489–150
