Stem carbohydrate dynamics during post anthesis period in diverse wheat genotypes under different environments

The contribution of stem water soluble carbohydrates (SWSCs) to grain biomass of wheat ranges from 10 to 20% under irrigated condition and 40 to 60% under stresses such as terminal heat and drought. Genetic variation in SWSC and its mobilization can be useful to increase the grain yield of wheat under harsh environments. Hence, a set of 16 genotypes varying in spike morphology and grain yield was grown in field under timely sown, late sown and terminal drought stress conditions. The anthrone method was used to measure the SWSC concentration in the dried peduncle and penultimate internodes in three replicates at 3 growth stages starting from anthesis. The effect of delay in sowing and terminal drought on the SWSC concentration was significant from anthesis to 14 days after anthesis. Significant genetic variation was observed in the rate of post anthesis change in SWSC during the early grain filling period under the three conditions which partially contributed to the variation in grain yield per spike among the genotypes. Due to sterile florets and/or shorter grain filling duration, all the genotypes did not have a correlation between grain weight per spike and rate of decrease of SWSCs. Thus, our experiments reconfirm the significance of SWSC in present cultivars of wheat and also the scope for exploiting the genetic variation in this trait

Molecular investigations on grain filling rate under terminal heat stress in bread wheat (Triticum aestivum L.)

Grain yield under post anthesis high temperature stress is largely influenced by grain filling rate (GFR). To investigate molecular basis of this trait, a set of 111 recombinant inbred lines (RILs) derived from Raj 4014, a heat sensitive genotype and WH 730, heat tolerant cultivar was phenotyped during 2009-2010 and 2010-2011 crop seasons, under field conditions. The difference in GFR (dGFR) between the timely and late sown conditions was used as a phenotypic parameter to find association with molecular markers, as parental lines exhibited significant difference for this trait. The mapping population showed clear-cut segregation pattern for differences in GFR between timely and late sown conditions. About 75% of the progenies showed no difference while 25% showed significant difference in GFR under high temperature stress created by late sown condition. To study the association of this trait with the markers, the parental lines were screened with 300 simple sequence repeat (SSR) microsatellite markers out of which 15% (45) were polymorphic between parental lines. These polymorphic markers were utilized for genotyping a subset, comprising of 43 RILs that had clear contrasting variation for dGFR. Regression analysis revealed significant association of dGFR of RILs with two markers viz., Xbarc04 and Xgwm314 with coefficients of determination (R2) values of 0.10 and 0.06, respectively.Keywords: Grain filling rate (GFR), simple sequence repeat (SSR), heat tolerance, wheatAfrican Journal of Biotechnology Vol. 12(28), pp. 4439-444

Use of Phenomics for Differentiation of Mungbean (Vigna radiata L. Wilczek) Genotypes Varying in Growth Rates Per Unit of Water

In the human diet, particularly for most of the vegetarian population, mungbean (Vigna radiata L. Wilczek) is an inexpensive and environmentally friendly source of protein. Being a short-duration crop, mungbean fits well into different cropping systems dominated by staple food crops such as rice and wheat. Hence, knowing the growth and production pattern of this important legume under various soil moisture conditions gains paramount significance. Toward that end, 24 elite mungbean genotypes were grown with and without water stress for 25 days in a controlled environment. Top view and side view (two) images of all genotypes captured by a high-resolution camera installed in the high-throughput phenomics were analyzed to extract the pertinent parameters associated with plant features. We tested eight different multivariate models employing machine learning algorithms to predict fresh biomass from different features extracted from the images of diverse genotypes in the presence and absence of soil moisture stress. Based on the mean absolute error (MAE), root mean square error (RMSE), and R squared (R2) values, which are used to assess the precision of a model, the partial least square (PLS) method among the eight models was selected for the prediction of biomass. The predicted biomass was used to compute the plant growth rates and water-use indices, which were found to be highly promising surrogate traits as they could differentiate the response of genotypes to soil moisture stress more effectively. To the best of our knowledge, this is perhaps the first report stating the use of a phenomics method as a promising tool for assessing growth rates and also the productive use of water in mungbean crop

Biotic and Abiotic Constraints in Mungbean Production—Progress in Genetic Improvement

Mungbean [Vigna radiata (L.) R. Wilczek var. radiata] is an important food and cash legume crop in Asia. Development of short duration varieties has paved the way for the expansion of mungbean into other regions such as Sub-Saharan Africa and South America. Mungbean productivity is constrained by biotic and abiotic factors. Bruchids, whitefly, thrips, stem fly, aphids, and pod borers are the major insect-pests. The major diseases of mungbean are yellow mosaic, anthracnose, powdery mildew, Cercospora leaf spot, halo blight, bacterial leaf spot, and tan spot. Key abiotic stresses affecting mungbean production are drought, waterlogging, salinity, and heat stress. Mungbean breeding has been critical in developing varieties with resistance to biotic and abiotic factors, but there are many constraints still to address that include the precise and accurate identification of resistance source(s) for some of the traits and the traits conferred by multi genes. Latest technologies in phenotyping, genomics, proteomics, and metabolomics could be of great help to understand insect/pathogen-plant, plant-environment interactions and the key components responsible for resistance to biotic and abiotic stresses. This review discusses current biotic and abiotic constraints in mungbean production and the challenges in genetic improvement

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

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Not AvailableHigh-temperature stress is one of the significant abiotic stresses that reduce crop yields across the world. Heat stress is more prevalent in arid and semiarid regions of the tropics, and its occurrence has become more frequent in the subtropical areas. However, concerns related to this stress are significant due to the predicted rise in ambient temperatures due to global warming. It necessitates renewed phenotyping methods and crop breeding strategies to develop high-temperature tolerant crop cultivars. These strategies have a higher chance of success if the trait-based selection approach is implemented to achieve higher productivity under hotter environments. Hence, trait identification and phenotyping for key traits will play a crucial role in breeding programmes aiming at developing heat-tolerant crops. Although the concept has been around for decades, trait-based breeding has always been a challenge as screening large number genotypes for traits of interest is laborious and time-intensive. However, recent advances in phenomics have opened up new avenues to address this bottleneck efficiently and rapidly. It is attributed to the potential of phenomics tools to capture temporal and spatial changes in morphology and physiology and then related to the biochemistry of plants. These changes can provide clues about useful traits that can be used for selection of heat-tolerant lines in breeding programs. For this purpose, however, intensified efforts are needed to translate existing knowledge of mechanisms underlying heat tolerance into heritable traits and also into protocols for high throughput screening. In this regard, this review attempts to summarize the current status of breeding efforts to improve heat tolerance in crop plants and avenues for employing phenomic tools.Not Availabl

Comparative Analysis of Canopy Cooling in Wheat under High Temperature and Drought Stress

The size and the weight of wheat grains vary across the length of each spike (Triticum aestivum L.). High temperature and water scarcity often reduce the single grain weight, and this reduction also varies across the spike length. Plants tend to cope with high temperature and drought stress through inherent mechanisms such ascanopy cooling through transpiration, which can contribute to yield stability. The effect of canopy cooling on the average grain weight at different positions in spike is still unknown. In this study, we planned to assess the role of canopy temperature, yield-related traits, and spike shape in final grain weight. For two years (2017–2018 and 2018–2019), fifteen diverse genotypes released for cultivation in different environmental conditions were grown in the field. They were examined for canopy temperature, spikelets spike−1, grain number spike−1, grain yield spike−1, and grain weight of the spike’s basal, median, and distal regions. The Pearson correlation coefficient (r) was obtained for all pair-wise combinations of traits under different treatments and spike shapes. The results indicated that cooler canopy is correlated to grain weight in normal spike shape at all three positions within the spike irrespective of stress. The advantage of the cooler canopy in improving grain-filling at basal, median, and distal regions was more conspicuous in the high temperature stress conditions compared to non-stressed and drought conditions

Comparative Analysis of Canopy Cooling in Wheat under High Temperature and Drought Stress

The size and the weight of wheat grains vary across the length of each spike (Triticum aestivum L.). High temperature and water scarcity often reduce the single grain weight, and this reduction also varies across the spike length. Plants tend to cope with high temperature and drought stress through inherent mechanisms such ascanopy cooling through transpiration, which can contribute to yield stability. The effect of canopy cooling on the average grain weight at different positions in spike is still unknown. In this study, we planned to assess the role of canopy temperature, yield-related traits, and spike shape in final grain weight. For two years (2017–2018 and 2018–2019), fifteen diverse genotypes released for cultivation in different environmental conditions were grown in the field. They were examined for canopy temperature, spikelets spike−1, grain number spike−1, grain yield spike−1, and grain weight of the spike’s basal, median, and distal regions. The Pearson correlation coefficient (r) was obtained for all pair-wise combinations of traits under different treatments and spike shapes. The results indicated that cooler canopy is correlated to grain weight in normal spike shape at all three positions within the spike irrespective of stress. The advantage of the cooler canopy in improving grain-filling at basal, median, and distal regions was more conspicuous in the high temperature stress conditions compared to non-stressed and drought conditions