物件導向軟體之架構(Object-Oriented Software Construction)探討

This article introduces the FAO crop model AquaCrop. It simulates attainable yields of major herbaceous crops as a function of water consumption under rainfed, supplemental, deficit, and full irrigation conditions. The growth engine of AquaCrop is water-driven, in that transpiration is calculated first and translated into biomass using a conservative, crop-specific parameter: the biomass water productivity, normalized for atmospheric evaporative demand and air CO 2 concentration. The normalization is to make AquaCrop applicable to diverse locations and seasons. Simulations are performed on thermal time, but can be on calendar time, in daily time-steps. The model uses canopy ground cover instead of leaf area index (LAI) as the basis to calculate transpiration and to separate out soil evaporation from transpiration. Crop yield is calculated as the product of biomass and harvest index (HI). At the start of yield formation period, HI increases linearly with time after a lag phase, until near physiological maturity. Other than for the yield, there is no biomass partitioning into the various organs. Crop responses to water deficits are simulated with four modifiers that are functions of fractional available soil water modulated by evaporative demand, based on the differential sensitivity to water stress of four key plant processes: canopy expansion, stomatal control of transpiration, canopy senescence, and HI. The HI can be modified negatively or positively, depending on stress level, timing, and canopy duration. AquaCrop uses a relatively small number of parameters (explicit and mostly intuitive) and attempts to balance simplicity, accuracy, and robustness. The model is aimed mainly at practitioner-type end-users such as those working for extension services, consulting engineers, governmental agencies, nongovernmental organizations, and various kinds of farmers associations. It is also designed to fit the need of economists and policy specialists who use simple models for planning and scenario analysis.

AquaCrop-The FAO Crop Model to Simulate Yield Response to Water: I. Concepts and Underlying Principles

CropSyst, a cropping systems simulation model

Changes in temperature, CO 2 , and precipitation under the scenarios of climate change for the next 30 yr present a challenge to crop production. This review focuses on the impact of temperature, CO 2 , and ozone on agronomic crops and the implications for crop production. Understanding these implications for agricultural crops is critical for developing cropping systems resilient to stresses induced by climate change. There is variation among crops in their response to CO 2 , temperature, and precipitation changes and, with the regional differences in predicted climate, a situation is created in which the responses will be further complicated. For example, the temperature effects on soybean [Glycine max (L.) Merr.] could potentially cause yield reductions of 2.4% in the South but an increase of 1.7% in the Midwest. The frequency of years when temperatures exceed thresholds for damage during critical growth stages is likely to increase for some crops and regions. The increase in CO 2 contributes significantly to enhanced plant growth and improved water use efficiency (WUE); however, there may be a downscaling of these positive impacts due to higher temperatures plants will experience during their growth cycle. A challenge is to understand the interactions of the changing climatic parameters because of the interactions among temperature, CO 2 , and precipitation on plant growth and development and also on the biotic stresses of weeds, insects, and diseases. Agronomists will have to consider the variations in temperature and precipitation as part of the production system if they are to ensure the food security required by an ever increasing population.

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Climate Impacts on Agriculture: Implications for Crop Production

In big-leaf models of canopy photosynthesis, the Rubisco activity per unit ground area is taken as the sum of activities per unit leaf area within the canopy, and electron transport capacity is similarly summed. Such models overestimate rates of photosynthesis and require empirical curvature factors in the response to irradiance. We show that, with any distribution of leaf nitrogen within the canopy (including optimal), the required curvature factors are not constant but vary with canopy leaf area index and leaf nitrogen content. We further show that the underlying reason is the difference between the time-averaged and instantaneous distributions of absorbed irradiance, caused by penetration of sunflecks and the range of leaf angles in canopies. These errors are avoided in models that treat the canopy in terms of a number of layers ‐ the multi-layer models. We present an alternative to the multi-layer model: by separately integrating the sunlit and shaded leaf fractions of the canopy, a single layered sun/shade model is obtained, which is as accurate and simpler. The model is a scaled version of a leaf model as distinct from an integrative approach.

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Simple scaling of photosynthesis from leaves to canopies without the errors of big‐leaf models

Publisher Summary This chapter discusses some crop simulation models in agronomic systems. Many crop models or parts of crop models have been built to help the researcher and students understand the operation of some part of an agronomic cropping system, for example, soil water flow, stomata1 control, or fertilizer nutrient movement. In addition to understanding various parts of agronomic systems, the modelers want to see what can be expected to happen if some change is made in that system. Field tests are very expensive, especially as the numbers of variables and/or treatments increase, and years of results are needed. A proven model of the system helps to evaluate these treatments and indicates which ones could be expected to give the desired results. The cotton model, GOSSYM, has been widely validated. GOSSYM has been used in a user-friendly form on a PC microcomputer as a tool for on-farm management decisions pertaining to nitrogen fertilizer applications, irrigation scheduling, and timing of harvest-aid chemicals. By combining GOSSYM with an expert system program, COMAX, the on-farm management decisions have been run in several combinations to give the user an optimal plan for fertilizer and irrigation scheduling.

Crop simulation models in agronomic systems.

Crop Modeling and Applications: A Cotton Example

If global surface temperatures change as projected because of radiative and physiological effects of a changing environment, we should expect important changes in crop production in the 21st Century. Experiments were conducted at ambient and twice ambient atmospheric CO2 concentrations at five temperatures. The 1995 temperature in Mississippi was used as a reference with the other temperatures being 1995 minus 2˚C, and 1995 plus 2, 5 and 7˚C. Daily and seasonal variation and amplitudes were maintained. Seedlings had 4–6 times as much leaf area and dry weight at 20 d after emergence when grown at 28˚C as at 23˚C (1995 ambient) average temperature during that growth period. Number of days to first square, flower, and open boll decreased as temperature increased. Double atmospheric CO2 did not affect these developmental rates. Temperatures above 28˚C, or 1995 average whole-season temperatures, were detrimental to mid- and late-season boll retention and growth. No fruits were retained to maturity at 1995 plus 5 or 7˚C. However, whole season vegetative growth was not significantly reduced by temperature 5–7˚C above the 1995 ambient conditions. Twice ambient CO2 caused about 40% increase in vegetative dry matter accumulation across temperatures. In a separate experiment, similar results were obtained on fruiting cotton grown at a range of temperatures based on long-term average US Midsouth July temperatures. Therefore, if global warming occurs as predicted, food and fibre production in such high-temperature and humid environments may be more limited to vegetative structures and the animals that consume vegetative structures.

James M. McKinion

Papers

Crop simulation models in agronomic systems.

Crop Modeling and Applications: A Cotton Example

A comparison of scenarios for the effect of global climate change on cotton growth and yield

Expert systems for agriculture

Application of the GOSSYM/COMAX system to cotton crop management