Responses of phenology, yield attributes, and yield of wheat varieties under different sowing times in Indo-Gangetic Plains.

A field experiment with wheat was conducted at Pusa (25.98°N, 85.67°E, 52 m amsl), Bihar (middle Gangetic plains of India), to assess the responses of phenology, yield attributes, and yield to growing season temperature and heat stress. For this purpose, wheat was planted on five dates (viz., 15 November, 25 November, 5 December, 15 December, and 25 December) for three consecutive years (viz., 2014-2015, 2015-2016, and 2016-2017) with three prominent cultivars of the region (viz., RAU-3711, HD-2824, and HD-2733). Five dates of sowing represent different wheat-growing micro-environments as imposed by varying sowing dates encompassing the entire sowing window. The study observed the significant effect of sowing dates on phenophase duration. In general, with progress in the date of sowing, tiller initiation was delayed, while the reverse trend was observed for later growth phases. Sowing environments significantly influenced the number of effective tillers m-2. Average numbers of effective tillers (ET) m-2 for the wheat sown during 15-25 November were almost 11.6% higher than those of the 25 December sown crop. Grain filling duration (GFD) showed a declining trend with the advancement of sowing dates due to increased thermal load on the crop during the reproductive period. 15 November planted crop exhibited the highest GFD (47 days), which was shortened significantly beyond 25 November, signifying agrometeorological non-suitability of wheat sowing beyond this window. Wheat sown on 25 November recorded the highest grain yield (3.21 Mg ha-1), 48.61% higher than the 25 December sown crop due to the congenial thermal regime. In this context, we have identified optimal and sub-optimal conditions to escape heat stress for higher wheat productivity. Moreover, the sum of deviation of temperature from optimum thresholds, computed for sensitive growth phases (50% flowering to physiological maturity), helped us to identify heat stress and its impact on wheat. Genotype-by-environment (GGE) biplot analysis revealed that RAU-3711 was found to be the most stable cultivar. A decrease in the yield of wheat by 4.9% to 12.0%, sown during November, and 33.8% to 42.4%, sown during December, is predicted in 2050-51 and 2080-81, respectively, under RCP 4.5.

Critical weather limits for paddy rice under diverse ecosystems of India.

Rice yields are largely influenced by variability in weather. Here, we demonstrate the effect of weather variables viz., maximum and minimum temperatures, rainfall, morning and evening relative humidity, bright sunshine hours on the yield of rice cv. Swarna, grown across five rice ecologies of India through field experiments during kharif (wet) season (Jun-Sept.). Critical thresholds of weather elements were identified for achieving above average, average and below average yield for each ecology. The investigation could determine how different weather elements individually and collectively affect rice yield in different rice ecosystems of India. While a sudden increase in minimum temperature by 8-10 °C (> 30 °C) during reproductive period resulted in 40-50 per cent yield reduction at Mohanpur, a sudden decrease (< 20 °C) caused yield decline at Dapoli. The higher yields may be attributed to a significant difference in bright sunshine hours between reproductive phases of above-average and below-average yield years (ranging from 2.8 to 7.8 hours during P5 stages and 1.7 to 5.1 during P4 stages). Rice cultivar Swarna performed differently at various sowing dates in a location as well as across locations (6650 kg ha-1 at Dapoli to 1101 kg ha-1 at Samastipur). It was also found that across all locations, the above average yield could be associated with higher range of maximum temperature compared to that of below average yield. Principal component analysis explained 77 per cent of cumulative variance among the variables at first growth stage, whereas 70 per cent at second growth stage followed by 74 per cent and 66 per cent at subsequent growth stages. We found that coastal locations, in contrast to inland ones, could maximize the yield potential of the cultivar Swarna, due to the longer duration of days between panicle initiation to physiological maturity. We anticipate that the location-specific thresholds of weather factors will encourage rice production techniques that are climate resilient.

Identifying appropriate prediction models for estimating hourly temperature over diverse agro-ecological regions of India.

The present study tests the accuracy of four models in estimating the hourly air temperatures in different agroecological regions of the country during two major crop seasons, kharif and rabi, by taking daily maximum and minimum temperatures as input. These methods that are being used in different crop growth simulation models were selected from the literature. To adjust the biases of estimated hourly temperature, three bias correction methods (Linear regression, Linear scaling and Quantile mapping) were used. When compared with the observed data, the estimated hourly temperature, after bias correction, is reasonably close to the observed during both kharif and rabi seasons. The bias-corrected Soygro model exhibited its good performance at 14 locations, followed by the WAVE model and Temperature models at 8 and 6 locations, respectively during the kharif season. In the case of rabi season, the bias-corrected Temperature model appears to be accurate at more locations (21), followed by WAVE and Soygro models at 4 and 2 locations, respectively. The pooled data analysis showed the least error between estimated (uncorrected and bias-corrected) and observed hourly temperature from 04 to 08 h during kharif season while it was 03 to 08 h during the rabi season. The results of the present study indicated that Soygro and Temperature models estimated hourly temperature with better accuracy at a majority of the locations situated in the agroecological regions representing different climates and soil types. Though the WAVE model worked well at some of the locations, estimation by the PL model was not up to the mark in both kharif and rabi seasons. Hence, Soygro and Temperature models can be used to estimate hourly temperature data during both kharif and rabi seasons, after the bias correction by the Linear Regression method. We believe that the application of the study would facilitate the usage of hourly temperature data instead of daily data which in turn improves the precision in predicting phenological events and bud dormancy breaks, chilling hour requirement etc.

Evaluating area-specific adaptation strategies for rainfed maize under future climates of India.

This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess the impact of future climate on yield in 16 major maize growing districts of India. DSSAT model was used to simulate maize yield and evaluate adaptation strategies during mid (2040-69) and end-centuries (2070-99) under RCP 4.5 and 8.5. Genetic coefficients were calibrated and validated for each of the study locations. The projected climate indicated a substantial increase in mean seasonal maximum (0.9-6.0 °C) and minimum temperatures (1.1-6.1 °C) in the future (the range denotes the lowest and highest change during all the four future scenarios). Without adaptation strategies, climate change could reduce maize yield in the range of 16% (Tumkur) to 46% (Jalandhar) under RCP 4.5 and 21% (Tumkur) to 80% (Jalandhar) under RCP 8.5. Only at Dharwad, the yield could remain slightly higher or the same compared to the baseline period (1980-2009). Six adaptation strategies were evaluated (delayed sowing, increase in fertilizer dose, supplemental irrigation, and their combinations) in which a combination of those was found to be effective in majority of the districts. District-specific adaptation strategies were identified for each of the future scenarios. The findings of this study will enable in planning adaptation strategies to minimize the negative impact of projected climate in major maize growing districts of India.

Untranslated regions (UTRs) orchestrate translation reprogramming in cellular stress responses.

Stress is the result of an organism's interaction with environmental challenges. Regulations of gene expression including translation modulations are critical for adaptation and survival under stress. Untranslated regions (UTRs) of the transcripts play significant roles in translation regulation and continue to raise many intriguing questions in our understanding of cellular stress physiology. IRES (Internal ribosome entry site) and uORF (upstream open reading frame) mediated alternative translation initiations are emerging as unique mechanisms. Recent studies have revealed novel means of mRNAs stabilization in stress granules and their reversible modifications. Differential regulation of select transcripts is possible by the interplay between the adenine/uridine-rich elements (AREs) in 3'UTR with their binding proteins (AUBP) and by microRNA-mediated effects. Coordination of these various mechanisms control translation and thereby enables appropriate responses to environmental stress. In this review, we focus on the role of sequence signatures both at 5' and 3'UTRs in translation reprogramming during cellular stress responses.

Identification of SNP in HSP90AB1 and its association with the relative thermotolerance and milk production traits in Indian dairy cattle.

Heat shock proteins (Hsp) play crucial role in cellular thermotolerance and heat stress response. In the present work, Allele specific PCR (AS-PCR) was standardized to detect the nucleotide polymorphism within the HSP90AB1 gene (SNP g.4338T>C) in Indian breeds of dairy cattle. The identified genotypes were associated with relative thermotolerance in terms of physiological parameters and milk production traits. The results of the experiments revealed that the genotype frequency of CC, CT, and TT for Sahiwal were 0.05, 0.78, and 0.17, respectively, and in Frieswal, the frequencies were 0.20, 0.70, and 0.10, respectively. The average rectal temperature (ART) and average respiration rates (ARR) were recorded during peak summer stress and heat tolerance coefficient (HTC) was calculated. The association studies indicated that TT genotypes had significantly (P < 0.01) higher HTC and lower ARR values than CT and CC in both the breeds. The TT genotype animals also had better production parameter in terms of total milk yield (TMY) (P < 0.01). These findings may partly suggest the role of HSP90AB1 polymorphisms in the regulation of heat stress response and consequent effect on production traits. Nevertheless, involvement of other regulatory mechanisms cannot be overruled.