Foliar cytokinins or brassinosteroids applications influence the rice plant acclimatization to combined heat stress.

The effect of different foliar sprays numbers of cytokinins - (CK) and brassinosteroids - (BR) on the physiological, biochemical, and panicle parameters of rice plants subjected to combined heat stress (high day/night temperatures) were studied in three different experiments. The treatments established for the first (E1) and second (E2) experiments were the following: i) absolute control, ii) stress control, iii) heat stress + one foliar spray of CK, iv) heat stress + two foliar sprays of CK, v) heat stress + three foliar sprays of CK, vi) heat stress + one foliar spray of BR, vii) heat stress + two foliar sprays of BR, or viii) heat stress + three foliar sprays of BR. For the third experiment (E3), the treatments were the following: i) absolute control, ii) stress control, iii) heat stress + three foliar applications of CK, iv) heat stress + three foliar applications of BR. Rice-stressed plants and sprayed with three foliar sprays of CK or BR had a better stomatal conductance in E1 and E2 compared to their heat-stressed control. The relative tolerance index suggests that three CK or BR applications helped to mitigate the combined heat stress in both experiments. The foliar CK or BR applications at the flowering and grain-filling stages in rice-stressed plants increased Fv/Fm ratio and panicle characteristics (number of filled spikelets and the percentage of panicle blanking in E3). In conclusion, foliar applications of BR or CK can be considered an agronomic strategy to help improve the negative effect of combined heat stress conditions on the physiological behavior of rice plants during different phenological stages.

Foliar Growth Regulator Sprays Induced Tolerance to Combined Heat Stress by Enhancing Physiological and Biochemical Responses in Rice.

Rice yield has decreased due to climate variability and change in Colombia. Plant growth regulators have been used as a strategy to mitigate heat stress in different crops. Therefore, this study aimed to evaluate the effect of foliar applications of four growth regulators [auxins (AUX), brassinosteroids (BR), cytokinins (CK), or gibberellins (GA)] on physiological (stomatal conductance, total chlorophyll content, Fv/Fm ratio, plant canopy temperature, and relative water content) and biochemical (Malondialdehyde (MDA) and proline contents) variables in two commercial rice genotypes exposed to combined heat stress (high day and nighttime temperatures). Two separate experiments were carried out using plants of two rice genotypes, Fedearroz 67 ("F67") and Fedearroz 2000 ("F2000") for the first and second experiments, respectively. Both trials were analyzed together as a series of experiments. The established treatments were as follows: absolute control (AC) (rice plants grown under optimal temperatures (30/25°C day/nighttime temperatures), heat stress control (SC) [rice plants only exposed to combined heat stress (40/30°C)], and stressed rice plants and sprayed twice (5 days before and after heat stress) with a plant growth regulator (stress+AUX, stress+BR, stress+CK, or stress+GA). The results showed that foliar CK sprays enhanced the total chlorophyll content in both cultivars (3.25 and 3.65 mg g-1 fresh weight for "F67" and "F2000" rice plants, respectively) compared to SC plants (2.36 and 2.56 mg g-1 fresh weight for "F67," and "F2000" rice plants, respectively). Foliar CK application also improved stomatal conductance mainly in "F2000" rice plants compared to their heat stress control (499.25 vs.150.60 mmol m-2s-1). Foliar BR or CK sprays reduced plant canopy temperature between 2 and 3°C and MDA content in plants under heat stress. The relative tolerance index suggested that foliar CK (97.69%), and BR (60.73%) applications helped to mitigate combined heat stress mainly in "F2000" rice plants. In conclusion, foliar BR or CK applications can be considered an agronomic strategy to help to ameliorate the negative effect of combined heat stress conditions on the physiological behavior of rice plants.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.