International Crops Research Institute for the Semi-Arid Tropics
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Development of Temporal Model for Forecasting of Helicoverpa armigera (Noctuidae: Lepidopetra) Using Arima and Artificial Neural Networks
Get PDFHelicoverpa armigera (Hübner) (Noctuidae: Lepidopetra) is a polyphagous pest of major crops grown in India. To prevent the damage caused by H. armigera farmers rely heavily on insecticides of diverse groups on a regular basis which is not a benign practice, environmentally and economically. To provide more efficient and accurate information on timely application of insecticides, this research was aimed to develop a forecast model to predict population dynamics of pod borer using Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN). The data used in this study were collected from the randomly installed sex
pheromone traps at International Crops Research Institute for the Semi-arid Tropics (ICRISAT), Patancheru, Hyderabad. Several ARIMA (p, d, q) (P, D, Q) and ANN models were developed using the historical trap catch data. ARIMA model (1,0,1), (1,0,2) with minimal BIC, RMSE, MAPE, MAE, and MASE values and higher R2 value (0.53) was selected as the best ARIMA fit model, and neural network (7-30-1) was found to be the best fit to predict the catches of male moths of pod borer from September 2021 to August 2023. A comparative analysis performed between the ARIMA and ANN, shows that the ANN based on feed forward neural networks is best suited for effective pest prediction. With the developed ARIMA model, it would be easier to predict H. armigera adult population dynamics round the year and timely intervention of control measures can be followed by appropriate decision-making schedule for insecticide application
Water Stress Detection in Pearl Millet Canopy with Selected Wavebands using UAV Based Hyperspectral Imaging and Machine Learning
No full textThe major bottleneck in plant phenotyping is the assessment of thousands of genotypes under field conditions, which can be accelerated through Unmanned Aerial Vehicle (UAV) based sensing. Phenotyping for complex traits such as abiotic stress (drought) adaptation can be explored more precisely through the rich spectral information acquired by Hyperspectral Imaging (HSI) sensors. HSI sensors can identify plant water stress early by observing the changes in canopy reflectance due to drought. This study used a UAV-based HSI sensor in the 400-1000 nm range to identify canopy water stress in the pearl millet crop. Five Machine learning-based Feature Selection (FS) methods were used to identify the top-ranked ten wavebands sensitive to canopy water stress. Wavelengths around 692, 714-716, 763-769, 774-882, 870, and 949 nm were repeatedly selected by two or more FS methods. The Recursive feature elimination method with the Support vector machine (SVM) classifier outperformed the other FS methods in selecting the best bands subset. SVM classifier with linear kernel on the selected bands could classify two water stress levels with 95.38% accuracy and early detect stress with 80.76% accuracy in the pearl millet canopy. This study will benefit the agriculture sector by accelerating crop phenotyping using UAV-based HSI
Contribution of root system architecture and function in the performance of tropical maize (Zea mays L.) genotypes under different moisture regimes
No full textUnderstanding how roots respond to increasing rate of evapotranspiration in warmer days and exposure to dry spells is crucial for saving productivity of rainfed crops, including maize, grown in Asian tropics. In a semi-automatic root phenotyping facility (lysimetric system) a set of 100 elite and diverse tropical maize inbred lines were phenotyped under managed drought stress (DT) and well-watered (WW) conditions. Plants were grown in PVC (Polyvinyl chloride) cylinder of 30.0 cm diameter and 150.0 cm length. In drought experiment, last irrigation was applied based accumulated growing degree days (SigmaGDD) criteria to achieved reproductive stress DT, whereas optimal moisture was maintained in WW trials. Data recorded on various root structural and function traits in both DT and WW trials. Significant phenotypic variability was observed for various root traits, including both structural and functional traits, under both the moisture regimes. Correlation studies showed that grain yield of early maturity group of genotypes was positively and significantly associated with all the root structural traits under drought, whereas, in case of medium and late maturity group of entries root structural traits showed either weak positive or significant negative correlation with grain yield under drought. Though, root functional traits of all the maturity group of genotypes showed positive and significant correlations with both grain yield and total biomass under both well-watered drought stress. Regression analysis showed that water uptake had significant positive relationship with total biomass in all the three-maturity group of genotypes. However, grain yield seems to be less dependent directly on the total amount of water uptake. We conclude that contribution of various traits in root system architecture under drought or well-watered conditions vary with maturity of genotypes. However, root functional traits, such as water uptake and transpiration efficiency are equally important across maturity groups and water availability regimes
Technology Heterogeneity and Poverty Traps: A Latent Class Approach to Technology Gap Drivers of Chronic Poverty
No full textThe analysis of household wealth dynamic remains an important methodology in the identification of poverty traps. To overcome measurement issues in survey data, livelihoods-based approaches of the dynamics of poverty are typically examined using panel regressions of a livelihoods regression on household assets and other socio-economic factors over time. In this paper, we characterise the livelihoods regression as a ‘livelihoods technology’, and use a latent class-technology approach to account for heterogeneity in how households generate a livelihood. We use a detailed dataset from rural India covering 213 households across 2001–2014, and control for selection issues through a Heckman Selection model. Our results are the first in the wealth dynamics literature to show that substantial heterogeneity exists in the technologies with which households generate their livelihoods. Importantly, we show that accounting for heterogeneity in household livelihoods ‘technologies’ more readily identifies different equilibria in wealth levels and provides previously foregone information on who is poor and why they remain poor
Maize response to temporary floods under ambient on-farm conditions of the West African Sahel
Get PDFWith the ongoing global warming, the occurrence and amplitude of extreme weather events have increased over the West African Sahel. The increasing frequency of heavy rain events, can negatively affect the lowland crops’ growth and production. Two-season field experiments were conducted near
Ouagadougou (Burkina Faso) to test the effects of temporary flooding and surface water stagnation on maize (Zea mays L.) growth and productivity. The treatments were organized into a split-split plot design. Three factors were monitored, including aboveground flooding levels (i.e., 0 cm, 2–3 cm, and 7–8 cm), flooding duration (i.e., three days and six days), and growth stages (i.e., six-leaf stage (V6),
tasseling stage (VT) and milky stage (R3)). Optimal crop management was practiced to Obatanpa cultivar planted during the rainy season and flooding was induced by over-irrigation. The results show that three days and six days of flooding, reduced grain yield by at least 35% when they occurred at the tasseling stage. Only 4–6 days of flooding reduced grain yield by 21% at the six-leaf stage. Further
scrutiny, using the stress day index (SDI), revealed that the penalty on yield increases exponentially under flooding conditions as the value of the stress day index increases. Considering the new characteristics of the rainfall regime in the West African Sahel, dominated by a high frequency of heavy rain events and wet spells, temporary floods, and water stagnation are tremendously contributing to yield loss of on-farm maize. As the region’s climate changes, we hypothesize that excess water stress will become the next cause of food insecurity in the area
Capturing Genetic Variability and Identification of Promising Drought-Tolerant Lines in Exotic Landrace Derived Population Under Reproductive Drought Stress in Rice
Get PDFDrought is one of the most predominant abiotic stresses in this century, leading to a drastic reduction in the yield of rainfed rice ecosystems. Breeding of drought-resilient rice varieties is very much in demand for sustainable rice production in drought-prone rainfed ecology. An experiment was designed under irrigated non-stress and drought-stress situations involving an exotic drought-tolerant landrace (Chao Khaw) and a high-yielding aromatic rice cultivar (Kasturi), and an F2:4 derived population of 156 breeding lines was developed at IRRI South Asia Hub, Hyderabad. The objective of the study was to assess the genetic variability, drought tolerance behavior, and identify promising breeding lines for different rice ecologies and drought breeding programs. Restricted maximum likelihood (REML) analysis using the mixed model approach revealed a considerable genetic variation in the population for yield and yield contributing traits in non-stress and drought-stress conditions. We observed very high heritability for all the selected traits under stress 2015 WS (73.8% to 85.3%) and 2016 WS (72.4% to 93.5%) and non-stress 2015 WS (68.2% To 92.9%) and 2016 WS (61.4% to 92.6%) environments, indicating possible selection for grain yield under drought stress and non-stress with the same precision level. None of the secondary traits except harvest index and biomass included in our study showed a positive association with grain yield, indicating indirect selection’s ineffectiveness in improving yield under drought. A total of 48 promising breeding lines were found to have a better yield than donor Chao Khaw (up to 38% advantage) and popular drought-tolerant cultivars Shabhagidhan (up to 48% advantage) in stress conditions and recommended for rainfed upland ecology, 34 breeding lines under the well-watered condition suited for rainfed lowland ecology. Overall, the study found 21 common breeding lines that showed their superiority in non-stress and under drought stress situations, fitting best in rainfed lowland ecology with occasional drought occurrence. The large genetic variation found in this population can be exploited further to develop a few forward breeding high-yielding lines with better drought tolerance ability and used as drought donors in drought breeding programs
Mainstreaming orphan millets for advancing climate smart agriculture to secure nutrition and health
Get PDFThe ever-changing climate and the current COVID-19 pandemic compound the problems and seriously impact agriculture production, resulting in socio-economic insecurities and imposing health implications globally. Most of the poor and malnourished population in the developing countries depends on agriculture for food, income, and employment. Impact of climate change together with the COVID-19 outbreak revealed immense problems highlighting the importance of mainstreaming climate-resilient and low input crops with more contemporary agriculture practices. Orphan millets play a vital role in the poor and malnourished population's livelihood, food and nutrition security. Recognizing their unique potential, the United Nations-Food and Agriculture Organization has announced the year 2023 as the “International Year of Millets”. However, despite the unique properties for present and future agriculture of orphan millets, their cultivation is declining in many countries. As a result, millets have gained attention from researchers which eventually decelerated “multi-omics” resource generation. This review summarizes the benefits of millets and major barriers/ bottlenecks in their improvement. We also discuss the pre- and post-harvest technologies; policies required to introduce and establish millets in mainstream agriculture. To improve and ensure the livelihood of the poor/malnourished population, intensive efforts are urgently needed in advancing the research and development, implementing pre- and post-harvest technological intervention strategies, and making favorable policies for orphan crops to accomplish food and nutrition security. National and international collaborations are also indispensable to address the uncertain effects of climate change and COVID-19
Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses
Get PDFLegume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas
Are Millets More Effective in Managing Hyperlipidaemia and Obesity than Major Cereal Staples? A Systematic Review and Meta-Analysis
Get PDFMillets are important staples across developing countries in Asia and Africa. A previous systematic review and meta-analysis showed that eating millets significantly controlled hyperlipidaemia and obesity by focusing on a comparison of pre- and post-intervention measurements. This study further provides meta-analysis of the effects of the consumption of millets on hyperlipidaemia and obesity by analysing millets against other staple grains using the difference-in-differences method, where the effects were computed on the Standardised Mean Difference scale. Thus, only studies
that included a control group as well as the baseline were included. The results from twelve eligible studies on blood lipid profile show significant (p < 0.05) favourable effects of consuming millets compared to other staples (rice, wheat, and quinoa). Specifically, the effects on total cholesterol,
triacylglycerol, and very low-density lipoprotein holesterol levels were -0.44, -0.29, and -0.41, respectively (p < 0.05), while the effect on the high-density lipoprotein cholesterol level was +0.59 (p < 0.05). In addition, the effects on low-density lipoprotein cholesterol and the body mass index were -0.60 and -0.29, respectively, with p = 0.06 each. While this study strengthens the evidence that the consumption of millets contributes to reducing the risks of hyperlipidaemia, and therefore cardiovascular diseases, more detailed and rigorous studies are recommended
Going underground: soil hydraulic properties impacting maize responsiveness to water deficit
Get PDFPurpose Although the coordination between stomatal closure and aboveground hydraulics has extensively been studied, our understanding of the impact of belowground hydraulics on stomatal regulation remains incomplete. Here, we investigated whether and how the water use of maize (Zea mays L.) varied under hydraulically contrasting soil textures. Our hypothesis is that a textural-specific drop in the hydraulic conductivity is associated with a distinct decrease in transpiration during soil drying.
Methods Maize plants were grown in contrasting soil textures (sand, sandy loam, loam) and exposed to soil drying. We measured the relationships between transpiration rate, soil water content as well as soil and leaf water potential. We used a soil-plant hydraulic model to reproduce the experimental observations and infer the hydraulic conductance of the soil-plant system during soil drying.
Results We observed the impact of soil texture on plant response to soil drying in various relationships. The soil water potentials at which transpiration decreased were more than one order of magnitude more negative in loam than in sand. The soil-plant conductance decreased not only abruptly but also at less negative soil water potentials in sand than in sandy loam or loam. Stomata closed at less negative leaf water potentials in sand than in loam. The model predictions matched well the experimental observations.
Conclusion The results elucidated that the critical soil water content and potential at which plants close stomata depends on the soil texture. These findings support our plea to include soil properties for understanding and predicting stomatal regulation during soil drying