International Crops Research Institute for the Semi-Arid Tropics
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Enhancing the capacity of smallholder farms to tap into digital climate service technologies opportunities for improved crop production in the cercles of Sikasso
Get PDFIn the Sahel, the agricultural sector, based mainly on rainfed farming system is extremely sensitive to climate change due to the higher frequency of excess heat, and changes in rainfall patterns leading to crop failure and crop damages from pests and diseases. In Mali, this threat of climate change is of particular concern as 80% of the population is engaged in agriculture and livelihoods, and are largely dependent on natural resources that are constantly degrading. Based on this observation, our approach was to help a group of 100 farmers to better integrate climate information and agricultural advice into their production systems through the Sénékèla/Sandji platform in the cercles of Sikasso and Kadiolo. A user group of 10 to 15 farmers was set up in seven (7) villages. The constitution of these groups took into account all social strata, including women who are the most marginalized in rural areas. Producers were trained in the use of the system (registration, interpretation of messages, holding a conversation with the agroadvisor). By using the platform, the farmers were able to better plan their activities, make decisions based on climate forecasts and have access to agricultural advice in real time. To evaluate the system, a study was conducted with a sample of 68 producers; the methodology adopted was based on data collection through a questionnaire and two rating sheets given to producers. The results show that the technology has had a positive impact on the lives of beneficiaries. We have seen a decrease in production costs of more than 30%, better use of inputs for 72% of producers and a decrease in working time (60.3% of producers). The majority of users (88%) are satisfied with Sénékèla/Sandji as a tool for disseminating climatic information, and 71% of forecasts received by producers were confirmed, which proves the effectiveness of the system
Comparative evaluation of changes in soil bio-chemical properties after application of traditional and enriched vermicompost
Get PDFFor nutrient-deficient soils, vermicompost is an excellent soil additive. We find biochemical fluctuations in soil by comparing enriched vermicomposts to regular vermicomposts
in a carefully controlled pot experiment. Various rock minerals, including mica, dolomite, and rock phosphate (RP), were used to create the enriched vermicompost before it was
applied to acid lateritic soil, and so we investigated how vermicompost’s biochemical impact on the soil evolves (15-day intervals). Our results suggested that traditional
vermicompost (VC) prepared from water hyacinth effectively improves nutrient content, enzymatic activities, and soil microbial properties. However, enriched VC application
significantly (p<0.05) augments the concentration of available P (60% higher than conventional VC) and exchangeable K (increased by 10% from conventional VC) in soil. Furthermore, we observed that enrichment of VC using a combination of rock minerals showed significantly higher urease (around 35%), acid phosphatase activity (by 93%), and
enhanced microbial biomass carbon (about 25%) and nutrient content of soil compared to only rock mineral additions. Nevertheless, our study revealed that conventional VC shows better soil organic carbon build-up than rock-based enriched VC. Although, enrichment conferred differential benefits to the soil in terms of increased P in RP-based and raised K in MC-based VC
Investigating the relationship between groundwater augmentation and water quality in the 6000 ha watershed in Telangana state, India
No full textGroundwater augmentation through rainwater harvesting has become a prime strategy to address water security and cope with the impact of climate change, especially in semi-arid regions. Increased water availability due to groundwater augmentation and its impact on rainfed agriculture has been well documented, but its impact on groundwater quality was rarely explored. In this study, data collected over 33-months on groundwater quality and groundwater table from a micro-watershed spread over 6000 ha in the semi-arid region of peninsular India were explored to assess the association between rainfall, groundwater augmentation, and groundwater quality. It was observed that the groundwater augmentation and related changes in the groundwater levels were influenced by the density of rainwater harvesting structures, rainfall distribution during the rainy season, groundwater withdrawals around the monitoring wells, and the distance between the wells and water storage structures. The results of principal component analysis (PCA) and hierarchal clustering revealed that the spatial and temporal variations in the groundwater quality governed by hydrogeochemical processes and preferential flow recharge processes might have been affected by groundwater augmentation and withdrawal. The fertilizer use in croplands as a non-point source of NO3–N and NH4–N in groundwater was affected by rainfall distribution. The high NO3–N levels in the vicinity of a burial site had indicated a possible point source of groundwater contamination. About 5%, 76%, 20%, and 4% of water samples were classified as poor, marginal, fair, and good as per the guidelines for drinking water with high fluoride and NH4–N content in groundwater as a point of concern. The majority of water samples were also classified as high salinity and low sodium hazard water, which may cause salt build-up in the poorly drained soil and affect crop water availability
Metabolic pathway genes for editing to enhance multiple disease resistance in plants
Get PDFDiseases are one of the major constraints in commercial crop production. Genetic diversity in varieties is the best option to manage diseases. Molecular marker-assisted breeding has produced hundreds of varieties with good yields, but the resistance level is not satisfactory. With the advent of whole genome sequencing, genome editing is emerging as an excellent option to improve the inadequate traits in these varieties. Plants produce thousands of antimicrobial secondary metabolites, which as polymers and conjugates are deposited to reinforce the secondary cell walls to contain the pathogen to an initial infection area. The resistance metabolites or the structures produced from them by plants are either constitutive (CR) or induced (IR), following pathogen invasion. The production of each resistance metabolite is controlled by a network of biosynthetic R genes, which are regulated by a hierarchy of R genes. A commercial variety also has most of these R genes, as in resistant, but a few may be mutated (SNPs/InDels). A few mutated genes, in one or more metabolic pathways, depending on the host–pathogen interaction, can be edited, and stacked to increase resistance metabolites or structures produced by them, to achieve required levels of multiple pathogen resistance under field conditions
Genetic gains in grain yield in wheat (Triticum aestivum L.) cultivars developed from 1965 to 2020 for irrigated production conditions of northwestern plains zone of India
Get PDFField trials with 13 landmark wheat cultivars released between 1965 and 2020 were conducted at 15 different locations during 2019–2020 and 2020–2021, providing data from 30 environments. The study of the historical set of spring wheat varieties from the North-Western Plains Zone (NWPZ) of India developed in the last 55 years demonstrated an improvement of grain yield from 3208 to 6275 kg ha−1 or a genetic gain of 1.21% year−1 over long-term check cultivar C306. In real terms, the yield has increased at a rate of 44.14 kg ha−1 year−1. To compare the present genetic gain study, a trend analysis based on historical grain yield data in standard AVT in the zone from 1980 to 2020 was also attempted, which revealed that the percent yield increase was 0.78 per annum. To achieve a higher rate of genetic gain, it requires greater breeding efficiency in the national breeding program through more systematic use of genetic diversity to introduce novel alleles as well as application of new breeding approaches like speed breeding and genomic selection
Adherence to EAT-Lancet dietary recommendations for health and sustainability in the Gambia
Get PDFFacilitating dietary change is pivotal to improving population health, increasing food system resilience, and minimizing adverse impacts on the environment, but assessment of the current 'status-quo' and identification of bottlenecks for improvement has been lacking to date. We assessed deviation of the Gambian diet from the EAT-Lancet guidelines for healthy and sustainable diets and identified leverage points to improve nutritional and planetary health. We analysed the 2015/16 Gambian Integrated Household Survey dataset comprising food consumption data from 12 713 households. Consumption of different food groups was compared against the EAT-Lancet reference diet targets to assess deviation from the guidelines. We computed a 'sustainable and healthy diet index (SHDI)' based on deviation of different food groups from the EAT-Lancet recommendations and modelled the socio-economic and geographic determinants of households that achieved higher scores on this index, using multivariable mixed effects regression. The average Gambian diet had very low adherence to EAT-Lancet recommendations. The diet was dominated by refined grains and added sugars which exceeded the recommendations. SHDI scores for nutritionally important food groups such as fruits, vegetables, nuts, dairy, poultry, and beef and lamb were low. Household characteristics associated with higher SHDI scores included: being a female-headed household, having a relatively small household size, having a schooled head of the household, having a high wealth index, and residing in an urban settlement. Furthermore, diets reported in the dry season and households with high crop production diversity showed increased adherence to the targets. While average Gambian diets include lower amounts of food groups with harmful environmental footprint, they are also inadequate in healthy food groups and are high in sugar. There are opportunities to improve diets without increasing their environmental footprint by focusing on the substitution of refined grains by wholegrains, reducing sugar and increasing fruit and vegetables consumption
Comparative assessment of Auto Regressive Integrated Moving Average with Explanatory variable (ARIMAX) and Neural Network Autoregressive models with Exogeneous inputs (NNARX) for forecasting the old-world bollworm, Helicoverpa armigera (Lepidoptera: Noctuidae) in India
No full textThe old world bollworm, Helicoverpa armigera Hubner (Lepidoptera: Noctuidae) is a key polyphagous agricultural pest with global wide distribution. To combat the damage caused by H. armigera farmers rely heavily on pesticides which is not a benevolent practice, environmentally and economically. To provide a more effectual and precise information on timely application of insecticides, this research was intended to develop a forecast model to predict the future trend of pod borer population by means of pheromone trap catch using Autoregressive Integrated Moving Average (ARIMAX) and Artificial Neural Networks (NNARX) with weather parameters as exogeneous variables. Several ARIMAX (p, d, q) and NNARX models were fitted by using the historical trap catch input data in different combinations. ARIMAX (2,0,0) with maximum temperature and rainfall as external variables was selected as the best ARIMAX fit. The neural network (10–32-1) was found to be the best fit to predict the male moth catches of old world bollworm from September, 2021 to August, 2023. A comparative assessment of ARIMAX and NNARX, showed that the NNARX models were found best suit for effective pest prediction to suggest timely intervention of control measures with appropriate decision-making schedule for application of insecticides
Genetic diversity of fig (Ficus carica L.) germplasm from the Mediterranean basin as revealed by SSR markers
No full textFig (Ficus carica L.) tree is cultivated worldwide and is highly appreciated for its fruit, which is consumed fresh or dried, having high nutritional and pharmaceutical value and for these reasons there is an increasing interest for its cultivation. In the present study, an ex situ collection of 60 fig accessions (41 indigenous Greek and 19 from other Mediterranean countries) was established and its diversity was analyzed using eight simple sequence repeat (SSR) loci. Greek fig genotypes showed relatively low allelic variation (the average number of SSR alleles per locus was 3.75), an excess of heterozygosity (mean He = 0.489 and Ho = 0.557), and extensive outbreeding (mean F index − 0.151). Cluster analysis showed that the established fig population exhibited weak genetic structure, with most of the genetic variation (89%) being present within individual members of the clusters. Both cluster and principal coordinate analysis confirmed that there is little correlation between genetic makeup and geographical origin of the fig accessions. Polymorphism information content with an average of 0.421 was reasonably informative. An identification key scheme for fig cultivars that will be useful in cultivar discrimination and intellectual property protection was developed. This work will contribute to a sustainable fig production regionally and worldwide, through the establishment and conservation of a reference fig collection, providing germplasm for future breeding efforts
Exploiting genetic variation from unadapted germplasm—An example from improvement of sorghum in Ethiopia
Get PDFSocietal Impact Statement The productivity of sorghum in Ethiopia has been largely limited by rain-fed condi-
tions because farmers tend to use local drought-tolerant but low-yielding landraces, as high-yielding and late-maturing landrace cultivars risk failure due to drought. Addressing such issues often requires a far-reaching approach to identify and incorporate new traits into a gene pool, followed by a period of selection to re-establish an overall adaptive phenotype. The sorghum backcross nested association mapping (BC-NAM) population developed in this study increases the genetic diversity available in Ethiopian elite adapted sorghum germplasm, providing new scope to improve
food security in a region known for periodic devastating droughts. Summary • As the center of diversity for sorghum, Sorghum bicolor (L.) Moench, elite cultivars selected in Ethiopia are of central importance to sub-Saharan food security. Despite being presumably well adapted to their center of diversity, elite Ethiopian sorghums nonetheless experience constraints to productivity, for example, associ-
ated with shifting rainfall patterns associated with climate change.
• A sorghum backcross nested association mapping (BC-NAM) population developed by crossing 13 diverse lines preidentified to have various drought resilience
mechanisms with an Ethiopian elite cultivar, Teshale, was tested under three rainfed environments in Ethiopia.
• Twenty-seven, 15, and 15 quantitative trait loci (QTLs) with predominantly small additive effects were identified for days to flowering, days to maturity, and plant height, respectively. Many associations detected in this study corresponded closely to known or candidate genes or previously mapped QTLs, supporting their validity.
• The expectation that genotypes such as Teshale from the center of diversity tend to have a history of strong balancing selection, with novel variations more likely to
persist in small marginal populations, was strongly supported in that for these three traits, nearly equal numbers of alleles from the donor lines conferred
increases and decreases in phenotype relative to the Teshale allele. Such rich variation provides a foundation for selection to arrive at a new “adaptive peak,” exemplifying the nature of efforts that may be necessary to adapt many crops to new climate extremes
Genetic mapping of QTLs for drought tolerance in chickpea (Cicer arietinum L.)
Get PDFChickpea yield is severely affected by drought stress, which is a complex quantitative trait regulated by multiple small-effect genes. Identifying genomic regions associated with drought tolerance component traits may increase our understanding of drought tolerance mechanisms and assist in
the development of drought-tolerant varieties. Here, a total of 187 F8 recombinant inbred lines (RILs) developed from an interspecific cross between drought-tolerant genotype GPF 2 (Cicer arietinum) and droughtsensitive accession ILWC 292 (C. reticulatum) were evaluated to identify quantitative trait loci (QTLs) associated with drought tolerance component traits. A total of 21 traits, including 12 morpho-physiological traits and nine rootrelated traits, were studied under rainfed and irrigated conditions. Composite
interval mapping identified 31 QTLs at Ludhiana and 23 QTLs at Faridkot locations for morphological and physiological traits, and seven QTLs were identified for root-related traits. QTL analysis identified eight consensus QTLs for six traits and five QTL clusters containing QTLs for multiple traits on linkage groups CaLG04 and CaLG06. The identified major QTLs and genomic regions associated with drought tolerance component traits can be introgressed into elite cultivars using genomics-assisted breeding to enhance
drought tolerance in chickpea