一文了解水稻生长模型三十年来进展以及未来研究方向Feet in the water Hands o...

文章简介

题目：Feet in the water and hands on the keyboard: A critical retrospective of crop modelling at AfricaRice

期刊：Field Crops Research

关键词:RIDEV ；ORYZA2000 ；Crop calendars ；Transpirational cooling ；Climate change

摘要

水稻在非洲各地的各种环境中种植。非洲作物生长模型试图发展对基因型、管理和环境相互作用的理解，为研究和开发提供信息。本文回顾了三十年来建模取得的进展，以及仍然存在的知识差距。在模拟物候和冷热诱导不育方面取得了重大进展。这关键考虑到了灌溉水稻通过蒸腾降温产生的作物小气候。在此基础上，RIDEV模型及其后继模型为应用育种、遗传学、农学和种植制度研究提供了有效支持。作为一门主要的学问，如果水稻能大量散发水分，就能非常有效地避免热应激。对于限水系统，基于ORYZA2000的产量差距、气候变化影响和干旱绘图项目为非洲应用研究议程指明了方向。但是，在建模能力和基础知识方面仍然存在很大差距，特别是在生物压力、内陆河谷水文和水稻种植序列方面，例如包括蔬菜作物。就理解生理学而言，需要更多的研究来精确模拟小穗数、热适应、光合作用对极端温度的响应以及生根深度的变化。这将需要加强非洲与先进研究中心之间的合作，以解决作物建模中的科学和技术瓶颈。

研究结果

Fig. 1. Comparisons of simulations with the calibrated RIDEV V2 model with observations on crop duration (top) and spikelet sterility (center), and separa-tion of simulated chilling and heat effects on sterility (bottom); for Sahel 108 rice planted at different dates at Ndiaye, Senegal. Field data courtesy of ORYTAGE project (Cirad) and the Ph.D. thesis of Dr. Sabine Stürz (Hohenheim University). Model parameters: Tbase, base temperature; Topt, optimum temperature; PPexp / PPsens, exponentiality and sensitivity of day length response; SUMbvb / SUMrepr / SUMmatu, thermal duration of basic vegetative, repro-ductive and maturation phases, respectively; CritSterCold1 / CritSterCold2, thermal interval of sterility response to cold; CritSterHeat, critical panicle temperature for heat sterility; SterBase, baseline unexplained spikelet sterility.

Fig. 2. A: Variation of filled grain weight distribution of Jaya rice based on 500 randomly taken grains, as affected by sowing date. Hot conditions reduced grain weight homogenously whereas chilling caused heterogeneous grain filling. B: Relationship between relative kernel weight (fraction of reference weight under stress free conditions) and mean minimum air temperature during grain filling, for 5 cvs. incl. Jaya. Data were used to simulate kernel weight in ORYZAS according to a broken-stick model (straight lines). Ndiaye, Senegal rice garden trial 1993. Reprinted/adapted by permission from Springer Nature: Kluwer Academic Publishers, Applications of Systems Approaches at the Field Level, Potential yield of irrigated rice in African arid environments, by Dingkuhn and Sow © 1997.

Fig. 3. A: Relationship between panicle-air temperature difference (Tp-Ta) and relative air humidity for Sahel 108 rice in 3 environments. B: Relationship between plant-air temperature difference and air vapor pressure difference (VPD) across the environments (grey symbols, panicles; black symbols, leaves). C: Comparison of RIDEV V2 and IM2PACT model predictions of Tp-Ta.

Fig. 4. Predicted panicle temperature under varied air temperature and vapor pressure deficit (VPD) condition as calculated from the equation in Fig. 3B. The boxed values indicate the observed range of conditions observed in Senegal and the Philippines by Julia (2013, thesis data).

Fig. 5. Simulated potential yield (solid lines for means of 10 years and points for individual years, 1970-1979) and seed-to-seed crop duration (broken lines) as a function of sowing date for rice cv. Jaya on a climatic gradient (four sites) along the Senegal river, using ORYZAS model. Locally recommended months of sowing are enhanced with circles. Reprinted/adapted by permission from Springer Nature: Kluwer Academic Publishers, Applications of Systems Approaches at the Field Level, Potential yield of irrigated rice in African arid environments, by Dingkuhn and Sow © 1997.

Fig. 6. Brief history of rice models.

Fig. 7. Results of a sensitivity analysis on combinations of soil parameters on simulated rice yields. Yw is the water-limited rough rice yield at 14 % moisture content, averaged over simulations in multiple years in 29 stations across Africa. Table S1 in the supporting material provides details on the soil parameters used.

Fig. 8. Relationship between flag leaf (top) and panicle (bottom) temperature vs. air temperature at 2 m for irrigated rice during flowering, confounding different sites, seasons, times of day and genotypes. Underlying study was published by Julia and Dingkuhn (2012 & 2013). IR imagery data were re-analysed from Ph.D. thesis by C. Julia, Montpellier, France 2013.

详细文章信息请访问以下网址：