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Climate change poses a major threat to global food security. Agricultural systems that rely on monsoon rainfall are especially vulnerable to changes in climate variability. This paper uses machine learning to deepen understanding of how monsoon variability impacts agricultural productivity. We demonstrate that random forest modelling is effective in representing rice production variability in response to monsoon weather variability. Our random forest modelling found monsoon weather predictors explain similar levels of detrended anomaly variation in both rice yield (33%) and area harvested (35%). The role of weather in explaining harvested rice area highlights that production area changes are an important pathway through which weather extremes impact agricultural productivity, which may exacerbate losses that occur through changes in per-area yields. We find that downwelling shortwave radiation flux is the most important weather variable in explaining variation in yield anomalies, with proportion of area under irrigation being the most important predictor overall. Machine learning modelling is capable of representing crop-climate variability in monsoonal agriculture and reveals additional information compared to traditional parametric models. For example, non-linear yield and area responses of irrigation, monsoon onset and season length all match biophysical expectations. Overall, we find that random forest modelling can reveal complex non-linearities and interactions between climate and rice production variability. [ABSTRACT FROM AUTHOR]

In winter, the paddy residues become wet during morning and late evening due to dew, which restricts the operation of sowing machines (Happy Seeder and Super Seeder) into paddy residues, as wet residues do not slide on furrow openers/tines. A PAU Smart Seeder (PSS) was developed and evaluated for a four-wheel tractor that can sow wheat with optimum crop establishment in combined harvested rice fields. The PSS were evaluated for its performance under varying straw load, forward speed, and rotor speed in terms of fuel consumption, field capacity, seed emergence, and grain yield. The crop establishment and wheat yield of PSS was also compared with the existing straw management machines Happy Seeder (HS) and Super Seeder (SS) under heavy paddy residue conditions. The effect of the straw load was more pronounced on dependent variables than the effect of the speed index. PSS performance was best at a forward speed of 2.6 km h−1, rotor speed of 127.5 rpm, and a straw load of 6 t ha−1. Average fuel consumption using PSS was lower than SS but higher than HS. Wheat emergence was higher by 15.6 and 25.7% on the PSS plots compared to HS and SS, respectively. Average wheat grain yield in PSS plots was significantly higher by 12.7 and 18.9% than SS and HS, respectively in one experiment, while the grain yield was similar for both PSS and HS in other experiments. PSS has a novel mechanism to manage paddy straw and simultaneously sow wheat into a heavy straw load (> 8 t ha−1) mixture of anchored and loose straw. In conclusion, PSS showed promise for in-situ management of rice straw as it eliminates most of the operational problems encountered by the existing seeders (HS and SS). [ABSTRACT FROM AUTHOR]

The 'Green Revolution (GR)' has been successful in meeting food sufficiency in India, but compromising its nutritional security. In a first, we report altered grain nutrients profile of modern-bred rice and wheat cultivars diminishing their mineral dietary significance to the Indian population. To substantiate, we evaluated grain nutrients profile of historical landmark high-yielding cultivars of rice and wheat released in succeeding decades since the GR and its impacts on mineral diet quality and human health, with a prediction for decades ahead. Analysis of grain nutrients profile shows a downward trend in concentrations of essential and beneficial elements, but an upward in toxic elements in past 50 y in both rice and wheat. For example, zinc (Zn) and iron (Fe) concentration in grains of rice decreased by ~ 33.0 (P < 0.001) and 27.0% (P < 0.0001); while for wheat it decreased by ~ 30.0 (P < 0.0001) and 19.0% (P < 0.0001) in past more than 50 y, respectively. A proposed mineral-diet quality index (M-DQI) significantly (P < 0.0001) decreased ~ 57.0 and 36.0% in the reported time span (1960–2010) in rice and wheat, respectively. The impoverished M-DQI could impose hostile effects on non-communicable diseases (NCDs) like iron-deficiency anemia, respiratory, cardiovascular, and musculoskeletal among the Indian population by 2040. Our research calls for an urgency of grain nutrients profiling before releasing a cultivar of staples like rice and wheat in the future. [ABSTRACT FROM AUTHOR]

Seasonal variations in rainfall patterns, particularly during sowing, early growing season, and flowering, drastically affect rice production in northeastern India. However, sensitivity to drought stress is genotype-specific. Since 80% of the land in this region is used for rice production, it is crucial to understand how they have adapted to water stress. This study evaluated 112 rice genotypes grown in NE India for seed germination percentage and seedling development under PEG-mediated drought stress. Among the rice genotype, Sahbhagi dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128 showed drought-tolerant traits, while Ketaki Joha, Chakhao, Chandan, RCPL-1-185 and IR-64 were the most drought-sensitive rice genotypes. Drought-tolerant rice also showed significantly higher seed germination potential, proline content, antioxidant activity and expression of drought-responsive genes than drought-sensitive rice genotypes. A similar expression pattern of genes was also observed in the rice genotype treated with a 50% water deficit in pot culture. In addition, drought stress reduced the pollen fertility and yield per plant in sensitive rice genotypes. Molecular markers associated with drought stress were also used to characterize genetic diversity among the rice genotypes studied. [ABSTRACT FROM AUTHOR]

Direct-seeded rice (DSR) seeds are often exposed to multiple environmental stresses in the field, leading to poor emergence, growth and productivity. Appropriate seed priming agents may help to overcome these challenges by ensuring uniform seed germination, and better seedling stand establishment. To examine the effectiveness of sodium selenite (Na-selenite), sodium selenate (Na-selenate), zinc oxide nanoparticles (ZnO-NPs), and their combinations as priming agents for DSR seeds, a controlled pot experiment followed by a field experiment over two consecutive years was conducted on a sandy clay loam soil (Inceptisol) in West Bengal, India. Priming with combinations of all priming agents had advantages over the hydro-priming treatment (control). All the combinations of the three priming agents resulted in the early emergence of seedlings with improved vigour. In the field experiment, all the combinations increased the plant chlorophyll, phenol and protein contents, leaf area index and duration, crop growth rate, uptake of nutrients (N, P, K, B, Zn and Si), and yield of DSR over the control. Our findings suggest that seed priming with the combination of ZnO-NPs, Na-selenite, and Na-selenate could be a viable option for the risk mitigation in DSR. [ABSTRACT FROM AUTHOR]

Biotic stresses, including diseases, severely affect rice production, compromising producers' ability to meet increasing global consumption. Understanding quantitative responses for resistance to diverse pathogens can guide development of reliable molecular markers, which, combined with advanced backcross populations, can accelerate the production of more resistant varieties. A candidate gene (CG) approach was used to accumulate different disease QTL from Moroberekan, a blast-resistant rice variety, into Vandana, a drought-tolerant variety. The advanced backcross progeny were evaluated for resistance to blast and tolerance to drought at five sites in India and the Philippines. Gene-based markers were designed to determine introgression of Moroberekan alleles for 11 CGs into the progeny. Six CGs, coding for chitinase, HSP90, oxalate oxidase, germin-like proteins, peroxidase and thaumatin-like protein, and 21 SSR markers were significantly associated with resistance to blast across screening sites. Multiple lines with different combinations, classes and numbers of CGs were associated with significant levels of race non-specific resistance to rice blast and sheath blight. Overall, the level of resistance effective in multiple locations was proportional to the number of CG alleles accumulated in advanced breeding lines. These disease resistant lines maintained tolerance to drought stress at the reproductive stage under blast disease pressure. [ABSTRACT FROM AUTHOR]