Drought-tolerant rice, weather index insurance, and comprehensive risk management for smallholders: evidence from a multi-year field experiment in India.
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ABSTRACT:
SUBMITTER: Ward PS
PROVIDER: S-EPMC7188305 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In shallow rainfed rice agro-ecosystems, drought stress can occur at any growth stage and can cause a significant yield reduction. During recent years, some rice varieties possessing tolerance of reproductive-stage drought stress have recently been developed. Tolerance of vegetative-stage drought stress is also required to improve rice productivity in drought-prone regions. In this study, we evaluated a set of rice breeding lines for their response to a range of different types of vegetative-stage drought stress in order to propose standardized phenotyping protocols for conducting vegetative-stage drought stress screening trials and also to identify genotypes combining tolerance of vegetative- and reproductive-stage drought stress. A soil water potential threshold of -20 kPa during the vegetative stage was identified as the target for effective selection under vegetative stage with grain yield reduction of about 50% compared to irrigated control trials. Genotypes identified as showing high yield under reproductive-stage drought stress were not necessarily the genotypes showing best performance under vegetative-stage drought stress. Genotypes IR72667-16-1-B-B-3, IR78908-126-B-2-B, and IR79970-B-47-1 showed tolerance of both vegetative-stage and reproductive-stage drought stress. For most, the genotypes that were best under vegetative stage drought or even vegetative stage + reproductive stage drought were different from the genotypes that were best under reproductive stage drought. Based on the cultivar superiority measure, IR69515-6-KKN-4-UBN-4-2-1-1-1 and IR78908-126-B-1-B were the stable genotypes (indicated by low Pi ) under both irrigated control and severe vegetative stress conditions, genotypes IR83614-203-B and IR78908-80-B-3-B were stable under irrigated control conditions and moderate stress, whereas IR72667-16-1-B-B-3 was stable under both moderate and severe vegetative-stage stress conditions.
| S-EPMC5473176 | biostudies-other
Project description:Drought Tolerant Maize Varieties (DTMV) and Rainfall Index Insurance (RII) are potential complements, though with limited empirical basis. We employ a multivariate spatial framework to investigate the potential for bundling DTMV with a simulated multi-site and multi-environment RII, designed to insure against mild, moderate and severe drought risk. We use yield data from on-farm trials conducted by the International Maize and Wheat Improvement Center (CIMMYT) and partners over 49 locations in Eastern and Southern Africa spanning 8 countries and 5 mega-environments (dry lowland, dry mid altitude, wet lower mid altitude, low wetland and wet upper mid altitude) in which 19 different improved maize varieties including DTMV were tested at each location. Spatially correlated daily rainfall data are generated from a first-order two-state Markov chain process and used to calibrate the index and predict yields with a hierarchical Bayes multivariate spatial model. Results show high variation in the performance and benefits of different bundles which depend on the maize variety, the risk layer insured, and the type of environment, with high chances of selecting a sub-optimal and unattractive contract. We find that complementing RII with a specific DTMV produces contracts with lower premiums and higher guaranteed returns especially in dry lowland increasing the chances of scaling up RII within this environment.
| S-EPMC7198119 | biostudies-literature
Project description:A field experiment was conducted at the Federal University of Alagoas in Maceio, Brazil. varieties RB86-7515, RB85-5536 and RB92-579 were distributed in a randomized block design with four replicates in two conditions: irrigated (control) and non-irrigated (treatment).
2021-01-14 | GSE125070 | GEO
Project description:In rice, gene expression profiling under different stresses have been carried out earlier through microarrays and SAGE (Kawasaki et al., 2001; Rabbani et al., 2003,;. Yazaki et al., 2003, 2004; Walia et al., 2005; Zhou et al., 2005; Jiao et al., 2005; Zhou, 2007; Wang, et al., 2007)). The results reported so far were mostly derived from different stress treatments, array formats, species, tissue types, and time courses, which make it difficult for direct comparison among studies. Also, most of the stress experiments on expression profiles were conducted under laboratory, growth chamber or field grown plants subjected to stress in laboratory conditions, usually by inducing stress with exogenous compounds such as abscisic acid (ABA) or gibberellin (GA) genes (Yazaki et al., 2003, 2004; Rabbani et al., 2003), salt (Kawasaki et al., 2001; Rabbani et al., 2003; Walia et al., 2005), organ specific gene expression under high salinity (Jiao et al., 2005) and drought (Zhou et al., 2007), comparison with different cultivars (Wang et al., 2007) and other environmental stresses such as cold and drought (Rabbani et al., 2003; Zhou et al., 2005). However, such laboratory, growth chamber grown plants or field grown plants subjected to stress under laboratory conditions significantly differ from the field stress conditions and therefore the resultant plant response may not truly represent the actual stress conditions prevailing on field. This has been extensively reviewed by Mittler, 2006 and the need for utilizing data from multiple stress experiments for developing plants resistant to stress has been focused. The review also focuses on evaluating farmers experiences in stress management and kinds of stress that a plant is subjected prior to taking up research on stress resistances has been of significant importance. In the present study, to bridge the gap between the available data on drought stress and the gene regulation under field drought conditions has been paid attention. The outcome of this data will give new leads for breeders to design strategies to develop plants resistant to drought without much loss in yield. In the present study experiments were conducted under different field capacities using a rainout shelter to minimizing the effects of drought induction due to rains. The microarray analysis is thus expected to throw light on stress responsive gene expression in field drought conditions. Till now, to our knowledge there have been no reports on gene expression in rice under field drought conditions. Further, there is no data available on gene expression profiling during various stages of plant growth in leaf and panicle tissues under different levels of water stress. Here, we have focused on generating stress responsive gene (SRG) expression profiles in field drought conditions through the entire life cycle of rice plant. Optimal drought simulation was achieved by conducting a drought stress experiment and validated by a series of dry runs. The main reason for evaluating gene expression under drought in field condition is as drought itself is not limited to water stress but various other factors, such as heat, humidity, hot winds, and long day lengths effect the gene regulation. All these are likely to trigger common pathways that are also a part of drought stress response and therefore significantly affect the expression profiles. In the present study, field drought stress was initiated from 31 days after germination and transplantation to the field at 100%, 60%, 40% and 15% field capacities designated as A1, A2, A3, and A4. It took 7 days for the onset of the actual drought for the experimental plots to reach to their designated field capacities from 100% FC. Samples were collected from 7 days after drought stress to 33 days after drought stress to evaluate different drought stress regimes based on the developmental stages of the plant. At all the tested stress levels the data points were Hierarchically grouped and clustered sets of genes were examined and an approximate number of clusters to be formed were estimated. Finding a group of genes showing a similar pattern of gene expression by means of expression data from microarray analysis is the basis for identification of genes and pathways controlling a specific trait. We have followed unsupervised classification and clustered the genes hierarchically after normalizing expression data to obtain a set of co-regulated genes. Analysis of data revealed that there are at least 3 to 4 clusters which show differential regulation under each stress regime. The annotated genes falling in these clusters interestingly include a number of novel genes from N22 library along with some known candidate genes for drought tolerance which were earlier identified in our study (Markandeya et al., 2007). Expression pattern of these genes from 7 days after drought stress to 33 days after drought stress with their fold changes were evaluated in the present study. In particular, it is observed that many genes of unknown function are also co-regulated in an interesting pattern along with known genes.
2011-11-27 | GSE31974 | GEO
Project description:Selection and breeding for drought tolerance in rice have always been one of the leading objectives for rice breeders in water-deficient farming areas. In the present study, we applied the potential of recombinant inbred lines (RILs) population, which were derived from cross Shahpasand (Iranian landrace) and IR28, for the development of drought-tolerant rice lines. One hundred fifty-two lines along with five check varieties were investigated from 2017 to 2019 under non-stress and drought stress conditions. The yield reduction caused by drought based on overall mean during 2017, 2018, and 2019 were estimated to be 89.40, 57.95, and 35.31%, respectively. Using different statistical methods, certain lines, including L33, L90, and L109, which are considered as the best lines in most environments, were found to be promising for being utilized to increase rice drought tolerance. The averages of grain yield of the above-mentioned lines were respectively 6.45, 5.80, and 5.70 t ha-1 under non-stress condition, and respectively 2.77, 2.66, and 2.59 t ha-1 under drought stress condition. The yield reduction of the selected lines were significantly lower than that of others indicating the significant transgressive segregation. The results revealed using the combination of the best identified tolerance and susceptibility indices and GT-biplot are effective methods for screening superior lines. However, their utilization is not easy and requires specialized packages. For the first time, we introduced a new composite index as a combination of significant indices (CSI). CSI is in the form of a linear function of indices which effectiveness is determined by their correlation coefficient with grain yield. According to our results, using CSI, the identified rice drought-tolerant lines were in high agreement with those obtained by other methods, demonstrating that CSI is a simple but reliable composite index.
| S-EPMC8828889 | biostudies-literature
Project description:Water-deficit stress tolerance in rice is important for maintaining stable yield, especially under rain-fed ecosystem. After a thorough drought-tolerance screening of more than 130 rice genotypes from various regions of Koraput in our previous study, six rice landraces were selected for drought tolerance capacity. These six rice landraces were further used for detailed physiological and molecular assessment under control and simulated drought stress conditions. After imposing various levels of drought stress, leaf photosynthetic rate (PN), photochemical efficiency of photosystem II (Fv/Fm), SPAD chlorophyll index, membrane stability index and relative water content were found comparable with the drought-tolerant check variety (N22). Compared to the drought-susceptible variety IR64, significant positive attributes and varietal differences were observed for all the above physiological parameters in drought-tolerant landraces. Genetic diversity among the studied rice landraces was assessed using 19 previously reported drought tolerance trait linked SSR markers. A total of 50 alleles with an average of 2.6 per locus were detected at the loci of the 19 markers across studied rice genotypes. The Nei's genetic diversity (He) and the polymorphism information content (PIC) ranged from 0.0 to 0.767 and 0.0 to 0.718, respectively. Seven SSR loci, such as RM324, RM19367, RM72, RM246, RM3549, RM566 and RM515, showed the highest PIC values and are thus, useful in assessing the genetic diversity of studied rice lines for drought tolerance. Based on the result, two rice landraces (Pandkagura and Mugudi) showed the highest similarity index with tolerant check variety. However, three rice landraces (Kalajeera, Machhakanta and Haldichudi) are more diverse and showed highest genetic distance with N22. These landraces can be considered as the potential genetic resources for drought breeding program.
| S-EPMC6214433 | biostudies-literature
Project description:Weather risks are an essential and increasingly important driver of agricultural income volatility. Agricultural insurances contribute to support farmers to cope with these risks. Among these insurances, weather index insurances (WII) are an innovative tool to cope with climatic risks in agriculture. Using WII, farmers receive an indemnification not based on actual yield reductions but are compensated based on a measured weather index, such as rainfall at a nearby weather station. The discrepancy between experienced losses and actual indemnification, basis risk, is a key challenge. In particular, specifications of WII used so far do not capture critical plant growth phases adequately. Here, we contribute to reduce basis risk by proposing novel procedures how occurrence dates and shifts of growth phases over time and space can be considered and test for their risk reducing potential. Our empirical example addresses drought risks in the critical growth phase around the anthesis stage in winter wheat production in Germany. We find spatially explicit, public and open databases of phenology reports to contribute to reduce basis risk and thus improve the attractiveness of WII. In contrast, we find growth stage modelling based on growing degree days (thermal time) not to result in significant improvements.
| S-EPMC5758701 | biostudies-literature
Project description: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.
| S-EPMC10445142 | biostudies-literature
Project description:Sugarcane drought experiment under field conditions
| PRJNA515077 | ENA
Project description:MicroRNAs regulate a spectrum of developmental and biochemical processes in plants and animals. Thus, knowledge of the entire miRNome is essential to understand the complete regulatory schema of any organism. The current study attempts to unravel yet undiscovered miRNA genes in rice. Analysis of small RNA libraries from various tissues of drought-tolerant 'aus' rice variety Nagina 22 (N22) identified 71 novel miRNAs. These were validated based on precursor hairpin structure, small RNA mapping pattern, 'star' sequence, conservation and identification of targets based on degradome data. While some novel miRNAs were conserved in other monocots and dicots, most appear to be lineage-specific. They were segregated into two different classes based on the closeness to the classical miRNA definition. Interestingly, evidence of a miRNA-like cleavage was found even for miRNAs that lie beyond the classical definition. Several novel miRNAs displayed tissue-enriched and/or drought responsive expression. Generation and analysis of the degradome data from N22 along with publicly available degradome identified several high confidence targets implicated in regulation of fundamental processes such as flowering and stress response. Thus, discovery of these novel miRNAs considerably expands the dimension of the miRNA-mediated regulation in rice.
| S-EPMC4976344 | biostudies-literature