Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level

Water resources used in irrigated agriculture are increasingly scarce, particularly in many countries where irrigation has undergone recent expansion. To optimize the limited resources available, optimization models provide useful tools for technical and economic analyses. One of the key inputs of these models is the yield response to water which is often simulated with empirical water production functions. At present, dynamic crop simulation models, such as AquaCrop (Steduto et al., 2009) offer alternative predictions of crop responses to different irrigation strategies as inputs to economic optimization. A model at farm scale was developed and applied to an area in South-western Spain to assist farmers in pre-season decision making on cropping patterns and on irrigation strategies. Yield predictions were obtained from the AquaCrop model which was validated for four different crops. The model simulated the impact on farm income of: (a) irrigation water constraints; (b) variations in agricultural policies; (c) changes in product and water prices; and, (d) variations in the communication to farmers of the specific level of irrigation water allocation. The applications of the models to the study area showed that currently, the changes in cropping patterns induced by the agricultural policy will encourage water savings more than an increase in water prices. Under water restrictions, the best strategy combines planting of low water use crops in part of the area to release water to grow more profitable crops with greater water needs. The model predicted a strong negative impact on farm income of delaying a decision on the level of seasonal water allocation by the water authority, reaching up to 300 € ha⁻¹ in the case of the study area.     

小麦水分胁迫影响因子的定量研究 Ⅱ.模型的建立与测试

基于冬小麦水分生理生态关系,综合考虑土壤水分有效性、作物不同生育阶段对干旱或渍水胁迫的敏感性、作物主要生理过程（蒸腾、光合作用、干物质分配等）对干旱胁迫的差异性、渍水持续天数等确定了支持作物生长模拟的干旱和渍水胁迫影响因子的算法。用独立于建模的盆栽小麦水分试验观测资料对干旱和渍水胁迫影响因子的算法进     

作物非充分灌溉决策指标研究进展

为了有效地进行非充分灌溉,通过不同方面研究土壤和作物水分亏缺的诊断方法,从而制定科学有效的灌水指标。对目前非充分灌溉的土壤、灌溉、作物等指标的研究现状及存在的问题进行了的阐述,讨论了非充分灌溉决策指标今后研究发展的方向。从目前国内外研究情况来看,应用叶水势、茎直径变化、冠层温度等作物指标来精确诊断作物的水分状况,已逐渐成为非充分灌溉研究领域关注的热点,但其基础理论、监测方法及不同作物的应用效果仍需进一步研究完善。因此,单纯从一种灌溉决策指标出发确定灌溉量是不全面的,如何建立非充分灌溉条件下不同地区、作物的灌溉指标体系将是今后中国重要的研究内容。     

中国作物分子设计育种

分子设计育种通过多种技术的集成与整合,对育种程序中的诸多因素进行模拟、筛选和优化,提出最佳的符合育种目标的基因型以及实现目标基因型的亲本选配和后代选择策略,以提高作物育种中的预见性和育种效率,实现从传统的“经验育种”到定向、高效的“精确育种”的转化。分子设计育种主要包含以下3个步骤：(1)研究目标性状基因以及基因间的相互关系,即找基因(或生产品种的原材料),这一步骤包括构建遗传群体、筛选多态性标记、构建遗传连锁图谱、数量性状表型鉴定和遗传分析等内容;(2)根据不同生态环境条件下的育种目标设计目标基因型,即找目标(或设计品种原型),这一步骤利用已经鉴定出的各种重要育种性状的基因信息,包括基因在染色体上的位置、遗传效应、基因到性状的生化网络和表达途径、基因之间的互作、基因与遗传背景和环境之间的互作等,模拟预测各种可能基因型的表现型,从中选择符合特定育种目标的基因型;(3)选育目标基因型的途径分析,即找途径(或制定生产品种的育种方案)。本文评述近几年来我国在遗传研究材料创新、重要性状遗传分析、育种模拟工具开发和应用、设计育种实践、分子设计育种技术体系建设等方面取得的重要进展,结合国内外研究现状对分子设计育种的未来进行展望,最后指出我国近期应加强育种预测方法和工具、基因和环境互作、遗传交配设计、作物功能基因组学、生物信息学方法和工具、设计育种技术体系和决策支持平台等领域的研究,同时重视人才培养和团队建设。     

亏缺灌溉下小麦水分利用效率与光合产物积累运转的相关研究

在大田栽培条件下,以小麦旱地品种晋麦47和西峰20、水旱兼用型品种石家庄8号和水地品种4185为材料,分别进行0水(T0)、一水(T1)和二水灌溉(T2)处理(每次灌水量60mm),研究了光合速率、叶面积指数、干物质积累与分配、根系分布、耗水量、产量因子与水分利用效率(WUE)的关系。结果表明,在拔节前不灌溉,拔节到开花期亏缺灌溉,促进干物质积累和深根发育。随着灌溉水的增加,耗水量显著增加,产量和WUE与耗水量呈二次曲线关系。T0处理显著减少了干物质积累和成穗数,产量、经济系数(HI)和WUE最低。T1和T2产量的提高主要是增加了穗数和穗粒数。灌浆期水分亏缺降低了光合速率(Pn)和气孔导度(Gs),加速了功能叶片的衰老,但诱导了花前储存碳库的再转运,显著提高了HI和产量。因此,在拔节和开花期亏缺灌溉促进根系生长,提高了土壤水分的利用效率。而产量和产量WUE的提高主要是由于增加了灌浆期叶片的Pn和光合功能持续期,促进花前储存碳库的再转运,显著提高了HI。     

Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment

In recent years, maize has become one of the main alternative crops for the Autumn–Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.     

亏缺灌溉下小麦水分利用效率与光合产物积累运转的相关研究

在大田栽培条件下,以小麦旱地品种晋麦47和西峰20、水旱兼用型品种石家庄8号和水地品种4185为材料,分别进行0水（T0）、一水（T1）和二水灌溉（T2）处理（每次灌水量60 mm）,研究了光合速率、叶面积指数、干物质积累与分配、根系分布、耗水量、产量因子与水分利用效率（WUE）的关系。结果表明,在拔节前不灌溉,拔节到开花期亏缺灌溉,促进干物质积累和深根发育。随着灌溉水的增加,耗水量显著增加,产量和WUE与耗水量呈二次曲线关系。T0处理显著减少了干物质积累和成穗数,产量、经济系数（HI）和WUE最低。T1和T2产量的提高主要是增加了穗数和穗粒数。灌浆期水分亏缺降低了光合速率（P_n）和气孔导度（G_s）,加速了功能叶片的衰老,但诱导了花前储存碳库的再转运,显著提高了HI和产量。因此,在拔节和开花期亏缺灌溉促进根系生长,提高了土壤水分的利用效率。而产量和产量WUE的提高主要是由于增加了灌浆期叶片的P_n和光合功能持续期,促进花前储存碳库的再转运,显著提高了HI。     

灌水控制下限对冬小麦产量及水分利用效率的影响

通过对冬小麦全生育期实施不同土壤水分控制下限,研究冬小麦的耗水规律,分析水分胁迫对其生长发育和产量形成的影响,并建立了产量与水分关系的数学模型。结果表明,不同水分处理的冬小麦耗水规律基本一致,但日耗水强度和总耗水量各处理间差别明显。各生育时段耗水量占全生育期总耗水量的百分比以孕穗灌浆期最大,达到45%;其次为拔节期,在20%左右;越冬期最小,只有4.0%~10.0%。土壤水分控制下限为55%的处理冬小麦水分利用效率最高,约为1.75kg/m3,对应的耗水量在350~400mm之间。     

干旱胁迫影响作物花粉发育的机制综述

作物生殖发育过程决定着其产量的形成,也对环境因子最为敏感。在生殖期遭遇干旱会影响花粉发育过程,导致作物结实率降低并引起作物减产。因此,探索作物生殖期抗旱机制对确保粮食生产安全尤为重要。研究发现,干旱引起作物花药淀粉积累异常、绒毡层降解提前或延后、花粉囊缺陷以及花粉发育的失败;还导致花器官中糖、激素以及氧化水平等的紊乱和相关基因表达的改变。为了全面解析作物生殖期响应干旱的机制,本研究从形态、生理生化特征和分子水平等方面对干旱影响花粉发育的机制进行了综述。本综述为作物抗旱机理的进一步解析及培育耐旱作物品种提供了理论依据,也为缺水条件下作物高产和稳产等实际问题提供了理论支持。     

反复干旱法的生理基础及其应用

研究了抗旱能力不同的品种对反复干旱的生理反应及土壤、植株水分的供需关系，结果表明反复干旱法能够鉴定作物或品种的抗旱性，反复干旱后的存活率是作物或品种对干旱反应的综合结果，可以代表该品种的抗旱能力。还研究了反复干旱法用于小麦后期的抗旱性鉴定，结果与大田鉴定基本一致     

沙漠绿洲隔沟交替灌溉辣椒的耗水特征及作物系数研究

为研究交替灌溉条件下辣椒的作物系数及土壤水分变化,用水量平衡法测定辣椒各生育期耗水量及土壤水分动态,实测得到辣椒各生育期的作物系数,并将作物系数与辣椒叶面积指数回归分析,研究隔沟交替灌溉辣椒各生育期的耗水特征及作物系数。结果表明,辣椒结果盛期是耗水量最大的时期,在辣椒定植—坐果期和结果末期交替灌溉处理作物的总耗水量与对照无显著差异,但结果盛期交替灌溉的总耗水量显著减少。辣椒交替灌溉下0~60 cm土层是土壤含水量变化活跃层。交替灌溉对辣椒的作物系数有显著影响,且随亏水程度的增大作物系数减小,‘美国红’的作物系数小于‘陇椒2号’。辣椒叶面积指数与作物系数呈显著的线性正相关。     

干旱与正常供水条件下小麦光合午休及其机理的研究

在小麦生育后期测定了干旱与正常供水条件下旗叶光合速率及其相应指标的日变化。结果表明,两处理条件下小麦午休开始的时间相同,午休的发生皆以气孔限制为肇端,非气孔限制随后才参与进来,但由于干旱胁迫使小麦光合机构受到一定程度的损伤,而使干旱条件下的小麦午休在降低的光合水平上进行。     

作物模拟技术的研究现状及其发展对策探讨

作物模拟技术是当今农业科学中一个新的研究领域。笔者在简要总结国内外作物模拟技术总体研究概况的基础上,阐述了作物模拟研究及模型应用尚存在的一些主要问题,并对其进一步发展的对策作了相应的探讨。     

An overview of the crop model

is a model that has been developed at INRA (France) since 1996. It simulates crop growth as well as soil water and nitrogen balances driven by daily climatic data. It calculates both agricultural variables (yield, input consumption) and environmental variables (water and nitrogen losses). From a conceptual point of view, relies essentially on well-known relationships or on simplifications of existing models. One of the key elements of is its adaptability to various crops. This is achieved by the use of generic parameters relevant for most crops and on options in the model formalisations concerning both physiology and management, that have to be chosen for each crop. All the users of the model form a group that participates in making the model and the software evolve, because is not a fixed model but rather an interactive modelling platform. This article presents version 5.0 by giving details on the model formalisations concerning shoot ecophysiology, soil functioning in interaction with roots, and relationships between crop management and the soil–crop system. The data required to run the model relate to climate, soil (water and nitrogen initial profiles and permanent soil features) and crop management. The species and varietal parameters are provided by the specialists of each species. The data required to validate the model relate to the agronomic or environmental outputs at the end of the cropping season. Some examples of validation and application are given, demonstrating the generality of the model and its ability to adapt to a wide range of agro-environmental issues. Finally, the conceptual limits of the model are discussed.     

节水灌溉方式下作物需水量和灌溉需水量研究综述

中国是一个严重缺水的国家,农业用水浪费严重,发展节水农业势在必行。作物生长需水量与灌溉需水量密切相关,作物生长需水量估算方法各异,并以彭曼公式为主,该公式与参照作物需水量（ET0）和作物生长系数（Kc）有关。计划灌溉需水量是节水灌溉管理的一个重要因素,其定额方式各有利弊,仍然以农田水量平衡方程为主要评估手段。     

Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials

Crop simulation models of plant processes capture the biological interactions between the sensing of signals at an organ level (e.g. drought affecting roots), the response of the plant at a biochemical level (e.g. change in development rate) and the result at the organ (or crop) level (e.g. reduced growth). In dissecting the complex control of phenotypes like yield, simulation models have several roles. Models have been used to generate an index of the climatic environment (e.g. of drought stress) for breeding programme trials. In wheat and sorghum grown in northern Australia, this has shown that mid-season drought generates large genotype by environment interaction. By defining gene action to calculate the value of input trait parameters to crop models, simulated multi-environment trials estimate the yield of ‘synthetic’ sorghum cultivars grown in historical or artificial climates with current or potential management regimes. In this way, the biological interactions among traits constrain the crop yields to only those that are biologically possible in the given set of environments. This allows the construction of datasets that are more ‘realistic’ representations of gene by trait by environment interaction than is possible using only the statistical attributes (e.g. means, variances and correlations) of real-world trait datasets. This approach has an additional advantage in that ‘biological and experimental noise’ can be manipulated separately. These ‘testbeds’ for statistical techniques can be extended to the interpretation of a crossing and selection programme where the processes of chromosomal recombination are simulated using a quantitative genetics model and applied to the trait parameters. Statisticians are challenged to develop improved methods for the resulting simulated phenotype datasets, with the objective of revealing the (known) underlying genetic and environment structure that was input to the simulations. These improved methods can then be applied to existing plant breeding programmes.     

Landscape Position and Precipitation Effects on Spatial Variability of Wheat Yield and Grain Protein in Southern Italy

Wheat yield and protein content are spatially variable because of inherent spatial variability of factors affecting the yield at field scale. In Mediterranean environments, yield variability is often caused by the irregular weather pattern, particularly rainfall and by position on the landscape. The objective of this study was to determine the effects of landscape position and rainfall on spatial variability of wheat yield and protein in a rolling terrain field of Southern Italy, and to propose stable management areas through simulation modelling and georesistivity imaging in rolling landscape. The study was carried out in Southern Italy, during 2 years of wheat monoculture; extensive soil properties and in-season plant measurements were measured. This study showed that soil water content was the main factor affecting spatial variation of yield for both years. The interactions between rainfall, topography and soil attributes increase the chances to observe yield variability among years. The principal component analysis demonstrated that for both years, soil water content explained most of the variability. The crop simulation model provided excellent results when compared with measured data with root mean square error of 0.2 t ha⁻¹. The simulated cumulative probability function showed that the model was able to confirm the yield temporal stability of three different zones.