Effectiveness of heat tolerance rice cultivars in preserving grain appearance quality under high temperatures - A meta-analysis
Wakatsuki, H.; Takimoto, T.; Ishigooka, Y.; Nishimori, M.; Sakata, M.; Saida, N.; Akagi, K.; Makowski, D.; Hasegawa, T.
Show abstract
BackgroundClimate change, particularly rising temperatures, negatively affects rice grain quality, increasing chalky grain percentage (CG) and hampering rice grade and price. Heat-tolerant cultivars have been bred and released since the 2000s, but the effectiveness of heat tolerance in reducing the occurrence of CG has yet to be quantified. ObjectivesThis study aimed to measure the effectiveness of breeding for better heat tolerance in reducing the negative impact of high temperatures on rice quality. MethodsThrough a systematic literature search, we developed a dataset including 1297 field observations covering 48 cultivars from five different heat tolerant ranks (HTRs) at 44 sites across Japan. A linear mixed-effect model (LME) and a random forest model (RF) were fitted to the data to analyze the effect of HTR and climatic factors such as the cumulative mean air temperature above 26 {degrees}C (TaHD), mean solar radiation, and mean relative humidity for 20 days after heading on CG. ResultsThe LME model explained 63 % of the variation with a 14% RMSE. The RF partial dependence plot revealed that the logit-transformed CG response to climate factors was linear, supporting the assumption of LME. The statistical analysis showed that CG increased as a function of TaHD (P < 0.001), with significant differences among HTRs (P < 0.001). The strongest effect of TaHD was obtained for the lowest HTR and was found to decrease with increasing HTR. CG also increased with higher relative humidity (P < 0.001) and solar radiation (P < 0.01). Based on our modeling, we estimated that as TaHD increased from 20 to 80 {degrees}Cd (equivalent to a mean temperature increase from 27 {degrees}C to 30 {degrees}C), CG increased by 66 % points (difference in CG) for cultivars with the lowest HTR, 45 % points for cultivars with an intermediate HTR, and 19 % points for cultivars with the highest HTR. Raising HTR by just one step (from intermediate to moderately tolerant) is projected to increase the proportion of first-grade rice at a grain-filling temperature of 27 {degrees}C, but tolerance levels need to be improved further in case of stronger warming. ConclusionsThe effect of high temperatures on CG was highly dependent on the cultivars HTR. Improvements in HTR effectively reduce the negative impacts of high temperatures on rice grain quality. SignificanceHeat-tolerant cultivars are projected to suppress the prevalence of CG more than threefold compared with heat-sensitive cultivars when grain-filling temperature increases from 27 to 30 {degrees}C.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Combining modelling and experimental approaches to assess the feasibility of developing rice-oil palm agroforestry system 95%
- Phenotyping the hidden half: Combining UAV phenotyping and machine learning to predict barley root traits in the field 95%
- High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase 94%
Similar papers in this journal
- Integrating Load-Cell Lysimetry and Machine Learning for Prediction of Daily Plant Transpiration 95%
- Deciphering transcriptomic signatures explaining the phenotypic plasticity of non-heading lettuce genotypes under artificial light conditions 94%
- Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles 93%
Similar papers in this journal
- GIS-FA: An approach to integrate thematic maps, factor-analytic and envirotyping for cultivar targeting 95%
- Image-based phenomic prediction can provide valuable decision support in wheat breeding 94%
- Genetic Gains in IRRIs Rice Salinity Breeding and Elite Panel Development as a Future Breeding Resource 94%
Similar papers in this journal
- Targeting Enhanced Digestibility: Prioritizing Low Pith Lignification to Complement low p-Coumaric Acid content as environmental stress intensity increase 95%
- Transpiration efficiency variations in the pearl millet reference collection PMiGAP 94%
- Evaluation of Conditional Treatment Effect of Salt Stress on Tomato Sugar Content Using Causal Machine Learning: A Pilot Study 93%
Similar papers in this journal
- An integrative process-based model for biomass and yield estimation of hardneck garlic (Allium sativum) 94%
- Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat 94%
- Crop modeling suggests limited transpiration would increase yield of sorghum across drought-prone regions of the United States 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.