International Crops Research Institute for the Semi-Arid Tropics
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Using homosoils to enrich sparse soil data infrastructure: an example from Mali
Get PDFMany areas in the world suffer from relatively sparse soil data availability. This results in inefficient implementation of soil-related studies and inadequate recommendations for improving soil management strategies. Commonly, this problem is tackled by collecting new soil data which are used to update legacy soil surveys. New soil data collection, however, is usually costly. In this paper, we demonstrate how to find homosoils with the objective of obtaining new soil data for a study area. Homosoils are soils that can be geographically distant but share similar soil-forming factors. We cluster the study area into five areas, and identify a homosoil to each area using distance metrics calculated in the character space spanned by the environmental covariates. In a case study in Mali, we found that large areas in India, Australia and America have similar soil-forming factors to the African Sahelian zone. We collected available soil data for these areas from the
WoSIS database. Statistical analysis on the relationship between the homosoils corresponding to different areas of Mali and tree soil properties (clay, sand, pH) displayed the unique variability captured by homosoils. The homosoils could explain 8% of the variation found in the soil datasets. There was a strong association between pH and homosoils corresponding to the semi-arid conditions
and sedimentary parent material of Mali, whereas homosoils corresponding to other areas of Mali showed moderate association either with clay or sand. The location and spread of the group centroids were statistically significantly different between depth-specific homosoils for the three soil properties. The approach developed in this paper shows the opportunity for identifying areas in the world with similar soils to populate areas with relatively low soil data density. The concept of homosoils is promising and we envision future applications such as transfer of soil models and agronomic experimental results between areas
Improving the representation of groundwater processes in a large-scale water resources model
Get PDFThis study explores whether incorporating a more sophisticated representation of groundwater, and human–groundwater interactions, improves predictive capability in a large-scale water resource model. The Global Water Availability Assessment model (GWAVA) is developed to include a simple layered aquifer and associated fluxes (GWAVA-GW), and applied to the Cauvery River basin in India, a large, human-impacted basin with a high dependence on groundwater. GWAVA-GW shows good predictive skill for streamflow upstream of the Mettur dam: Kling-Gupta efficiency ≥ 0.3 for 91% of sub-catchments, and improved model skill for streamflow prediction compared to GWAVA over the majority of the basin. GWAVA-GW shows some level of predictive skill for groundwater levels over seasonal and long-term time scales, with a tendency to overestimate depth to groundwater in areas with high levels of groundwater
pumping. Overall, GWAVA-GW is a useful tool when assessing water resources at a basin scale, especially in areas that rely on groundwater
Balancing co-benefits and trade-offs between climate change mitigation and adaptation innovations under mixed crop-livestock systems in semi-arid Zimbabwe
Get PDFAchieving Zimbabwe’s national and international commitments to food systems transformation and climate resilience building is of high priority. Integrated simulation-based research approaches developed under the Agricultural Model Intercomparison and Improvement Project (AgMIP) are important sources of evidence to guide policy decisions towards sustainable intensification. Through the identification of economically viable, socially inclusive and environmentally sustainable development pathways, the analysis in this study evaluates co-benefits and tradeoffs
between climate change adaptation and mitigation interventions for vulnerable smallholder crop-livestock
holdings in the semi-arid regions of Zimbabwe. We explore how climate effects disrupt the livelihoods and food
security for diverse farm types, the extremely vulnerable and those better resource endowed but facing high risks. In
an iterative process with experts and stakeholders, we co-developed context specific development pathways. They include market-oriented adaptation and mitigation interventions and social protection mechanisms that would support the transition towards more sustainable intensified, diversified and better integrated crop-livestock systems. We
assess the trade-offs associated with adoption of climate-smart interventions aimed at improving incomes and food
security but that may have consequences on GHG emissions for the different pathways and farm types. The approach and results inform the discussion on drivers that can bring about sustainable intensification, and the extent to which
socio-economic benefits could enhance the uptake of emission reducing technologies thereof. Through this strategy we evaluate interventions that can result in win–win outcomes, that is, adaptation-mitigation co-benefits, and what this would imply for policies that aim at transforming agri-food systems
Assessment of the relations between crop yield variability and the onset and intensity of the West African Monsoon
Get PDFTimely information on the onset of rain is essential for effectively adapting to climate variability and increasing the resilience of rain-fed systems. However, defining optimal sowing dates based on the onset of rain has been challenging. We compared and analyzed the West African Monsoon onset according to Raman’s, modified
Sivakumar’s, Yamada’s, and Liebmann’s definitions using station data from 13 locations in Senegal from 1981 to 2020. Subsequently, we systematically analyzed the effect of the differently estimated monsoon onsets(WAM-OS) on maize development. To this end, we applied the set of the generated WAM-OS as sowing dates in simulations
of maize growth and yields, applying the Agricultural Production Systems sIMulator(APSIM) at 13 locations representing different agroclimatic regions across Senegal. We examined the impact of the sowing dates under variable conditions of soil organic carbon(SOC) and plant available water capacity(PAWC). Our analysis showed
statistically significant differences between the WAM-OS dates, rainfall characteristics computed for these, and maize yields simulated using different sowing dates according to the WAM-OS definitions. We found Liebmann’s onset dates were most suitable for both hydrological and agronomic applications since they were characterized
by the lowest probabilities of prolonged dry spells after onset, the highest amount of rainfall in the mid-season, and the highest simulated maize yields compared to other onset definitions. Our results highlight the importance of sowing dates and their accurate prediction for improving crop productivity in the study area. We also found
SOC and PAWC were important factors that improved maize yields. We recommend improved access to climate information services to help smallholder farmers get timely information that helps them in their sowing decisions and encourage agronomic interventions that improve the SOC level, soil pore volume to retain more water and
other soil properties directly(e.g., tillage) and indirectly(suited cropping systems) that contribute to enhancing crop productivity
Establishing Breeding Priorities for Developing Biofortified High-Yielding Pearl Millet (Pennisetum glaucum (L.) R. Br.) Varieties and Hybrids in Dosso Region of Niger
Get PDFWest Africa is the origin and epicenter of pearl millet genetic diversity. Niger is a standalone country that produces 3.5 million tons of pearl millet from an area of 6.7 million hectares, with productivity varying from 0.5 to 0.7 t/ha. Low grain yield is a result of low soil fertility, drought, downy mildew, head miner, and the non-utilization of improved and quality seeds. Around 30 pearl millet varieties were released in Niger, but the adoption rate of improved varieties is still lagging. There has been no systematic mapping implemented for new varieties’ adoption preferences and the availability of quality seeds. Considering this and assessing the need for biofortified cultivars, the present participatory study was conducted in the Dosso region of Niger, wherein high rates of malnutrition persist. This study aimed (i) to identify breeding priorities for key traits of pearl millet preferred by farmers, with gender-based segregation, for varieties and hybrids, and (ii) to survey the preference for biofortified varieties with added nutritional value. Structured questionnaires and focus groups were used to collect data from 150 randomly selected respondents in 12 villages from three representative departments of Dogondoutchi, Dosso, and Gaya. The results reveal that pearl millet is a primary staple crop grown (98% of respondents) and consumed on a daily basis as food and also used as feed for their animals. The majority of farmers preferred a long panicle (50.7%) and a good seed set (45.3%). For grain traits, a white color (50%) and larger size (100%) were predominantly preferred, which fetches them higher prices in the market, where they compete with sorghum grains. All respondents unanimously rated growing biofortified pearl millet varieties as high (100%), owing to higher Fe and Zn, in addition to yield. Furthermore, 99.3% of farmers perform grain decortication before consumption, thus potentially depleting staple grain nutrition, which is expedient for pearl millet biofortification in the region. This study has the potential for establishing pearl millet breeding priorities that are likely to be employed for other West African pearl millet breeding programs
ICRISAT and WFP: India Working Paper Quantifying Climate Hazards and Its Relationship with Food Availability: A Comprehensive District Level Analysis in India
Get PDFThe escalating impact of climate change has emerged as a pivotal concern of the 21st century, transcending geographical boundaries and affecting myriad facets of human existence. Among the various sectors grappling with its consequences, the domain of food production stands at the forefront, intricately interwoven with the well-being of societies and the stability of global economies. Climate change, driven predominantly by anthropogenic activities, has triggered alterations in temperature patterns, precipitation regimes, and the frequency of extreme weather events (Li et. al, 2023). These transformations have cascading effects on the agricultural landscape, compelling a comprehensive examination of the intricate nexus between climate variability and food production (Haq et al, 2015)...
Key descriptors for fonio millets
Get PDFThe Key descriptors for fonio millets consist of an initial minimum set of characterization and evaluation descriptors for Digitaria exilis Stapf and Digitaria iburua Stapf of the family Poaceae. This strategic set aims at facilitating access to and utilization of these species and it does not
exclude the addition of other descriptors later. This work has been done jointly with the ICAR-Indian Institute of Millets Research (ICARIIMR), the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the
ICAR-National Bureau of Plant Genetic Resources (ICAR-NBPGR) and the FAO International Treaty on Plant Genetic Resources for Food and Agriculture. The descriptor list is based on a
draft list of descriptors for fonio developed by Dr Raymond Vodohuè and a group of scientists. Subsequently, internet searches were carried out looking for the most updated information on relevant characteristics and traits. The original list was afterwards integrated with evaluation
traits. Special attention was given to the inclusion of descriptors relevant to germplasm utilization, including nutritional traits and biotic and abiotic stresses of particular importance in the context of emerging adverse weather events, which are expected to intensify under
current and future climate challenges. The key set of access and utilization descriptors was defined through an online survey, in which 28 experts from 23 different organizations and universities from 16 countries participated. The results of the survey were subsequently validated in consultation with a Core Advisory Group (see “Contributors”) led by ICAR-IIMR, ICAR-NBPGR and ICRISAT. The strategic set of data standards is designed to facilitate access to and utilization of plant genetic resources for food and agriculture. Together with passport information (Alercia, A.
et al. 2015), descriptors are critical to the effective sharing of characterization and evaluation data and to the efficient use of plant genetic resources for food and agriculture
Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet
Get PDFFinger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a ‘poor man’s crop’, finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts
Validation of Genome-Wide SSR Markers Developed for Genetic Diversity and Population Structure Study in Grain Amaranth (Amaranthus hypochondriacus)
Get PDFGrain Amaranth is the most promising C4 dicotyledonous pseudocereal and is distributed globally. It has an excellent nutritional profile and adaptability against a broad range of environmental factors. These traits have renewed the interest of researchers and breeders in exploring this underutilized orphan crop. The present study aimed to validate the genome-wide SSR to assess the
genetic diversity among 94 Amaranthus hypochondriacus accessions using 57 genomic SSR (g-SSR) markers developed in-house. A total of 36 g-SSRs were recorded as polymorphic and amplified 138 alleles, with an average of 3.83 alleles per locus. Major allele frequency ranged from 0.29 to 0.98,
with an average of 0.63 per marker. The expected heterozygosity ranged from 0.03 to 0.81, with an average of 0.46 per locus. Polymorphism information content (PIC) ranged from 0.03 to 0.79, with an average of 0.40, indicating a high level of polymorphism across amaranth accessions. Population structure analysis resulted into two major genetic clusters irrespective of their geographical origin, which suggests there may be sharing of common genomic regions across the accessions. High allelic
frequency and heterozygosity levels indicate significant genetic variability in the germplasm, which can be further used in future breeding programs
Genetic diversity, population structure, and genome‑wide association study for the flowering trait in a diverse panel of 428 moth bean (Vigna aconitifolia) accessions using genotyping by sequencing
Get PDFBackground Moth bean (Vigna aconitifolia) is an underutilized, protein-rich legume that is grown in arid and semiarid areas of south Asia and is highly resistant to abiotic stresses such as heat and drought. Despite its economic importance, the crop remains unexplored at the genomic level for genetic diversity and trait mapping studies. To date, there is no report of SNP marker discovery and association mapping of any trait in this crop. Therefore, this study aimed to dissect the genetic diversity, population structure and marker-trait association for the flowering trait in a diversity panel of 428 moth bean accessions using genotyping by sequencing (GBS) approach. Results A total of 9078 high-quality single nucleotide polymorphisms (SNPs) were discovered by genotyping of 428 moth bean accessions. Model-based structure analysis and PCA grouped the moth bean accessions into two subpopulations. Cluster analysis revealed accessions belonging to the Northwestern region of India had higher variability than accessions from the other regions suggesting that this region represents its center of diversity. AMOVA revealed more variations within individuals (74%) and among the individuals (24%) than among the populations (2%). Marker-trait association analysis using seven multi-locus models including mrMLM, FASTmrEMMA FASTmrEMMA, ISIS EM-BLASSO, MLMM, BLINK and FarmCPU revealed 29 potential genomic regions for the trait days to 50% flowering, which were consistently detected in three or more models. Analysis of the allelic effect of the major genomic regions explaining phenotypic variance of more than 10% and those detected in at least 2 environments showed 4 genomic
regions with significant phenotypic effect on this trait. Further, we also analyzed genetic relationships among the Vigna species using SNP markers. The genomic localization of moth bean SNPs on genomes of closely related Vigna species demonstrated that maximum numbers of SNPs were getting localized on Vigna mungo. This suggested that the moth bean is most closely related to V. mungo. Conclusion Our study shows that the north-western regions of India represent the center of diversity of the moth bean. Further, the study revealed flowering-related genomic regions/candidate genes which can be potentially exploited in breeding programs to develop early-maturity moth bean varieties