Crop Development Rate Research Articles

Overcoming mechanistic limitations of process-based phenological models: A data clustering method for large-scale applications

Process-based phenological models use thermal requirement (TR) defined by planting date, temperature and photoperiod to predict crop developmental stages. The TR value for a specific developmental stage for a given variety is often presumed to be constant regardless of environmental conditions. We calibrated and compared 12 phenological models using 27-year of observation data of one unique rice (Oryza sativa L.) variety ('Shanyou63') from 46 sites in southern China. Our findings indicated that shifts in environmental conditions significantly affected TR values, e.g., standard deviations of TR at physiological maturation ranged from 83 to 167 °C d. Clustering sites together minimized environmental heterogeneity, and thus minimized the differences in TR for different phenological stages. When the increased from 1 to 24, simulation errors for the 12 models showed a significant decrease across all developmental stages, from 1.8 to 1.4 days for tillering, from 5.3 to 3.7 days for jointing, from 5.6 to 3.9 days for booting, from 4.7 to 3.3 days for heading, and from 6.6 to 3.7 days for physiological maturation. Furthermore, our findings indicate that models featuring a three-segment piecewise linear temperature response function provide a more precise prediction. In contrast, models incorporating a Beta temperature response function have not performed well. This difference is attributed to different mechanisms used to describe the response of crop development rate to temperature, particularly at non-optimum temperatures. The impact of the photoperiod response function on prediction accuracy became significant with the expansion of scale. Our results demonstrate that clustering method effectively compensates for the lack of crop adaptation processes in common phenological models, leading to significantly improved phenological prediction accuracy in regions with environmental diversity.

Adapting to the projected epidemics of Fusarium head blight of wheat in Korea under climate change scenarios.

Fusarium head blight (FHB) of wheat, mainly caused by Fusarium graminearum Schwabe, is an emerging threat to wheat production in Korea under a changing climate. The disease occurrence and accumulation of associated trichothecene mycotoxins in wheat kernels strongly coincide with warm and wet environments during flowering. Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). In this study, we adopted GIBSIM, an existing mechanistic model developed in Brazil to estimate the risk infection index of wheat FHB, to simulate the potential FHB epidemics in Korea using the SSP245 and SSP585 scenarios of CMIP6. The GIBSIM model simulates FHB infection risk from airborne inoculum density and infection frequency using temperature, precipitation, and relative humidity during the flowering period. First, wheat heading dates, during which GIBSIM runs, were predicted over suitable areas of winter wheat cultivation using a crop development rate model for wheat phenology and downscaled SSP scenarios. Second, an integrated model combining all results of wheat suitability, heading dates, and FHB infection risks from the SSP scenarios showed a gradual increase in FHB epidemics towards 2100, with different temporal and spatial patterns of varying magnitudes depending on the scenarios. These results indicate that proactive management strategies need to be seriously considered in the near future to minimize the potential impacts of the FHB epidemic under climate change in Korea. Therefore, available wheat cultivars with early or late heading dates were used in the model simulations as a realistic adaptation measure. As a result, wheat cultivars with early heading dates showed significant decreases in FHB epidemics in future periods, emphasizing the importance of effective adaptation measures against the projected increase in FHB epidemics in Korea under climate change.

Effects of tillage systems on soil water distribution, crop development, and evaporation and transpiration rates of soybean

Tillage practices are known to affect soil water retention, plant available water and, consequently, crop production. Impacts can be determined by assessing soil hydraulic properties and crop characteristics. In this study, three tillage practices were investigated with respect to vertical soil water distribution and development of soybean. A specific focus was set on determining evaporation and transpiration as fractions of evapotranspiration to obtain additional information on water availability and crop water use. The agricultural practices included conventional tillage, reduced tillage (no plow), and no-tillage. The study site was a long-term field experiment under rainfed conditions. The investigations covered a vegetation period of soybean. The measurements comprised weather and soil water monitoring using sensors and manual monitoring of crop development. Evapotranspiration and its components were determined using scintillometer measurements and an isotope-based water balance technique. In the researched vegetation period with limited water availability, the conservative tillage practices showed better water storage, water use, and crop yields compared to the conventional practice. The weekly evaporation and transpiration rates progressed according to the respective canopy development. Thus, delayed plant development of the no-till practice led to extended green cover and productive water use during the late season, where a large part of the precipitation has fallen. The tillage-induced differences of soil hydraulic properties had a substantial impact on soil water distribution, but a comparatively small impact on the soil surface wetness and thus directly on the evaporation rate. The tillage-induced impacts on soil cover by plant residues, however, showed the substantial reduction effect of plant residue cover on evaporation losses. Hence, assessment of evaporation and transpiration rates contributes to the understanding of differences in water productivity and promotes the efficient use of the available water resources.

Plastic temperature response function accurately simulates crop flowering or heading date

AbstractAlthough crop phenology is responsive and adaptable to cultural and climatic conditions, many phenology models are too sensitive to variable climatic conditions. We developed a plastic temperature response function by assuming that development rate was linearly related to temperature and that the linearity was linearly responsive to day of year (DOYv) of the starting date of the vegetative growth period (VGP). Phenology observations and weather data were acquired for winter wheat (Triticum aestivum L.), rice (Oryza sativa L.), maize (Zea mays L.), and soybean [Glycine max (L.) Merr.] at 12 locations over 15–26 yr. Additional data were observed for maize grown in an interval planting experiment. For 78.6% of the sites, the crop development rate during the VGP was positively affected by DOYv. Partial correlation analysis (controlling for temperature) indicated that DOYv was independent of temperature. When averaged over all crops and sites, the RMSE for a plastic phenology model based on both response and adaptation mechanisms was lower (RMSE = 2.81 d) than models (RMSE = 3.39) based only on response mechanism (p < .01). Furthermore, simulations produced by the plastic model showed less bias to DOYv, temperature, and year. The plastic function provided a simple and effective method for achieving better phenology simulation accuracy. According to the plastic function, growing season under warming conditions will not be reduced by as much as simulated by models based only on response mechanism, so yield loss due to warming is likely to be overestimated.

ALLELIC DIVERSITY OF GENES CONTROLLING RESPONSES TO VERNALIZATION AND PHOTOPERIOD AMONG SPRING BREAD WHEAT VARIETIES OF DIVERSE GEOGRAPHIC ORIGIN

Spring bread wheat is the most important cereal crop, cultivated under various climatic conditions and on different latitudes. Modern molecular genetic studies of wheat are aimed at investigating the crop’s genetic potential. By now, molecular markers have been developed to identify alleles of the Vrn (vernalization response) and Ppd (photoperiod response) genes. Vrn genes are responsible for crop development rate regulation and crop yield structure. Ppd genes determine the response of plants to the length of the day, that is, the timing of flowering and the beginning of heading in plants under different cultivation conditions. The use of diagnostic DNA markers made it possible to analyze the presence of allelic combinations of the Vrn and Ppd genes in local and commercial wheat varieties from Europe, Asia, North and South Americas, Africa and Australia. This review summarizes the results of studies on the distribution of alleles of Vrn and Ppd genes in wheat breeding material over different geographical areas of its cultivation. For example, the dominant Vrn-A1a allele was found in 62% of European varieties; 52% of the studied Turkish wheat varieties carried dominant Vrn-B1 alleles. A dominant Vrn-D1 was found in 61% of Pakistani wheat accessions. Vrn-D1 is present in 41.9% of the studied varieties of Chinese wheat. Higher incidence of Ppd-D1A is typical for West European varieties. A Ppd-D1a allele was found in 58.6% of varieties preserved in the Turkish wheat collection, with a 60% frequency of this allele in commercial cultivars. Among local Afghan varieties, 97% are sensitive to photoperiod (carriers of Ppd-D1b); they are distributed throughout the country without much dependence on agroecological zones. All Pakistani varieties are insensitive to photoperiod (carriers of Ppd-D1a). In China, the highest incidence of the Ppd-D1a allele was observed in zone VII (87.5% of varieties).

Adaptation of paddy rice in China to climate change: The effects of shifting sowing date on yield and irrigation water requirement

Warming and increasing extreme climate events are expected to reduce crop yields including rice production in China, threatening the Chinese food security. Shifting sowing date has been considered as a key adaptation strategy to sustain rice production in China. However, the extent to which it can mitigate the adverse climate change impact on yield and whether more irrigation is required remains unclear. Here, by driving ORYZA v3 with four climate models (GCMs), we analyzed the impacts of climate change on China rice yield and net irrigation water requirement (NIR) at 21 sites under a wide range of sowing date. We found that without altering sowing date, weighted average rice yield for all sites will decline 5.1, 7.3 and 15.1% in periods 2011–2040, 2041–2070 and 2071–2100, respectively. Yields losses in temperate zones are linked to increased crop development rates with higher temperatures, but in subtropical regions, the reduction is more related to the damage of heat stress during rice heading or flowering periods. NIR increases notably in all regions (up to 71%) except northeastern China, where the shortened growth duration resulted in less time to consume water. When the optimized sowing date is applied, average yield losses will be effectively compensated. To achieve these, rice-sowing date will be shifted by up to 54 days and on average 17.8–23.4 % more fresh water in future periods are needed to meet the water requirement of rice growth. We also found that, due to increasing the frequency of heat events, farmers in Chinese rice production regions (e.g., Yangtze River Basin) will have narrow sowing windows at the end of this century. This study suggests that adequate irrigation and adjusting sowing dates could mitigate the negative climate impacts on rice production in China.

Use of a plastic temperature response function reduces simulation error of crop maturity date by half

Understanding how crop development rate responds to the environment provides the basis for evaluating the impact of climate change on crop yield. In most crop simulation models, temperature response functions of development rate during the reproductive growth period (RGP) are assumed to only vary with temperature and not with other environmental factors. However, studies have indicated that the response functions may be plastic with other factors. Until now, little attention has been paid to this type of response. Here, using extensively collected field observations and data from intentionally designed interval planting experiments with winter wheat (Triticum aestivum L.), rice (Oryza sativa L.), and spring maize (Zea mays L.), we show that temperature response functions during RGP are plastic with day of year of flowering/heading (DOYR). Coefficients of determination between DOYR and development rate were significant for 69% sites. Partial correlation coefficients between development rate, temperature, and DOYR suggest that DOYR explains almost the same variability in maturity date as temperature. The plastic model was developed by coupling DOYR with a linear temperature response function. The model can improve the fitting efficiency by 112%, while dependency between DOYR and temperature explains less than 25% of this improvement. The average RMSEs of simulated maturity date estimated by the plastic model in the three crops were 2.1, 2.5, and 3.7 d, respectively, while the corresponding values given by widely applied traditional models were 3.1, 6.5, and 7.4 d, respectively. Therefore, the plastic model can reduce simulation error by half. Moreover, simulation errors resulting from the plastic model have less systematic bias than traditional models. The plastic model simply and effectively provides accurate estimates of crop maturity and reduces the system deviation of the estimates. Coupling the plastic model of crop development with crop simulation models will likely decrease uncertainties in simulated yield under warming conditions. Additionally, results of this study will encourage future studies of other phenotype plasticity considered in current crop simulation models.

Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models

A combination of Landsat 8 and Sentinel-2 offers a high frequency of observations (3–5 days) at moderate spatial resolution (10–30 m), which is essential for crop yield studies. Existing methods traditionally apply vegetation indices (VIs) that incorporate surface reflectances (SRs) in two or more spectral bands into a single variable, and rarely address the incorporation of SRs into empirical regression models of crop yield. In this work, we address these issues by normalizing satellite data (both VIs and SRs) derived from NASA’s Harmonized Landsat Sentinel-2 (HLS) product, through a phenological fitting. We apply a quadratic function to fit VIs or SRs against accumulated growing degree days (AGDDs), which affects the rate of crop development. The derived phenological metrics for VIs and SRs, namely peak, area under curve (AUC), and fitting coefficients from a quadratic function, were used to build empirical regression winter wheat models at a regional scale in Ukraine for three years, 2016–2018. The best results were achieved for the model with near infrared (NIR) and red spectral bands and derived AUC, constant, linear, and quadratic coefficients of the quadratic model. The best model yielded a root mean square error (RMSE) of 0.201 t/ha (5.4%) and coefficient of determination R2 = 0.73 on cross-validation.

Improving rice development and phenology prediction across contrasting climate zones of China

Modelling rice development rate and phenology is crucial for robust yield prediction. However significant uncertainties originating from the temperature response functions in rice models exist. In this study, both the Wang-Engel temperature response function and the Johnson temperature response function were coupled in the MCWLA-Rice model and evaluated at 10 agro-meteorological experiment stations located in contrasting climate zones across China. Results show that the MCWLA-Rice model with the Wang-Engel temperature response function is able to improve the predictions of heading and maturity date for double season rice at the stations in the middle and lower reaches of the Yangtze River. Mean improvements were 23.5% and 25.1%, respectively. The MCWLA-Rice model with the Johnson temperature response function is able to improve the predictions of heading date by 26.2% and maturity date by 22.9% on average at all stations. At the locations characterised by high temperature stress conditions, both the Wang-Engel and the Johnson temperature response functions are able to improve predictions of heading and maturity date, nevertheless the improvement is not as pronounced as for those locations not suffered from high temperature stress. These results demonstrate how rice phenology simulation can be improved, yet suggest that further improvements should be made to reproduce phenology in locations suffering from heat stress. This study highlights the value of environment-controlled experiments on the effects of exceeding threshold temperatures from several hours to several days on instantaneous crop development rate and improving crop phenology simulations.

Stability of wheat grain yields over three field seasons in the UK.

Ensuring food security in a changing climate is a major contemporary challenge and requires development of climate‐resilient crops that perform well under variable environments. The hypothesis that yield stability in suboptimal conditions is linked to yield penalties in optimal conditions was investigated in field‐grown wheat in the UK. The phenotypic responses, rate of wheat crop development, and final grain yield to varying sowing date, rainfall, air temperature, and radiation patterns were studied for a panel of 61 elite commercial wheat cultivars grown in the UK in 2012, 2013, and 2014. Contrasting climatic patterns, particularly rainfall accumulation and distribution over the season, influenced the relative performance of the cultivars affecting the duration of grain development stage and impacting on productivity. Indices for crop productivity, yield stability, and performance under suboptimal conditions revealed four cultivars with a combination of stable and high relative grain yields over the three seasons: Gladiator, Humber, Mercato, and Zebedee. Genetic similarity between cultivars partially explained yield performance in the contrasting seasons. The year of release of the cultivars correlated with grain yield but not with yield stability, supporting the contention that breeding for yield potential does not select for climate resilience and yield stability of crops. Further analysis of the outstanding cultivars may unravel target traits for breeding efforts aimed at increasing wheat yield potential and stability in the changing climate.

Simulation of climate change impacts on production and phenology of durum wheat in Mediterranean environments using CERES-Wheat model

The CERES-Wheat crop model was used to simulate grain yields, kernel weights and anthesis dates for three Italian durum wheat varieties (Creso, Duilio and Simeto) under climate change projections at two typical Mediterranean environments (Ussana and Benatzu sites) located in Southern Sardinia (Italy). The model was calibrated and validated in a previous modelling study using long-term weather data from the same experimental sites and agronomic data-sets of the same sites and varieties over the period 1973–2004. To assess the responses of durum wheat varieties to climate changes, 48 synthetic climates based on the combination of increasing temperature and decreasing rainfall were used to represent paths of possible future climate change. The simulated impacts of climate projections on durum wheat varieties at both sites were: grain yield reduction, slightly increasing kernel weight, and earlier anthesis dates. The late variety Creso showed a larger grain yield reduction compared to the early genotypes Duilio and Simeto. Anticipation of time to flowering was larger at Ussana (medium-low fertility soil) than at Benatzu (high fertility soil) with no differences between varieties. Earlier anthesis response was due to temperature increase rather than rainfall reduction, since in the CERES-Wheat model as well as in the majority of crop growth models water availability has no effect on crop development rate. Predictions for kernel weight were more uncertain with a slightly increasing trend in response to increasing temperatures and decreasing rainfall. The CERES-Wheat crop model seems to capture fairly well the greater resilience shown by early genotypes in Mediterranean rainfed conditions. In general, the CERES-Wheat model showed results in line with the findings from real experiments in different pedoclimatic conditions. For these reasons, CERES-Wheat appeared to be reliable when used to evaluate plant responses to projected climate change conditions and can represent a useful tool for developing adaptation strategies and measures such as the choice and selection of adapted genotypes to tackle the negative impact of climate change.

A unique approach to demonstrating that apical bud temperature specifically determines leaf initiation rate in the dicot Cucumis sativus.

Main conclusionLeaf initiation rate is largely determined by the apical bud temperature even when apical bud temperature largely deviates from the temperature of other plant organs.We have long known that the rate of leaf initiation (LIR) is highly sensitive to temperature, but previous studies in dicots have not rigorously demonstrated that apical bud temperature controls LIR independent of other plant organs temperature. Many models assume that apical bud and leaf temperature are the same. In some environments, the temperature of the apical bud, where leaf initiation occurs, may differ by several degrees Celsius from the temperature of other plant organs. In a 28-days study, we maintained temperature differences between the apical bud and the rest of the individual Cucumis sativus plants from −7 to +8 °C by enclosing the apical buds in transparent, temperature-controlled, flow-through, spheres. Our results demonstrate that LIR was completely determined by apical bud temperature independent of other plant organs temperature. These results emphasize the need to measure or model apical bud temperatures in dicots to improve the prediction of crop development rates in simulation models.

Cereal Breeding for Organic Farming: Crop Traits Related with Competitiveness Against Weeds

The objectives of the investigation were to identify competitive traits in cereal species in order to contribute to development of a methodology for evaluation of cereal genotypes for their competitive capacity against weeds, which is important for organic breeding aims. The investigation was carried out with spring barley, spring oat, winter triticale and winter wheat genotypes in organic crop rotations in two different locations. Relations between crop traits and weed dry weight were evaluated by Pearson correlation coefficients. The results stressed the significance of some crop traits for cereal competitiveness against weeds for organic breeding purposes: (i) growth habit, canopy height, and crop development rate for spring barley; (ii) crop development rate for spring oats; (iii) winter hardiness and the coefficient of tillering for winter triticale, and (iv) winterhardiness, the coefficient of tillering, the number of productive stems, crop canopy and plant height for winter wheat. It coud be useful to include measurements of crop ground cover for estimating competitiveness of cereal species against weeds

Climate change at winter wheat breeding sites in central Asia, eastern Europe, and USA, and implications for breeding

Key weather parameters (monthly minimum and maximum temperature, precipitation) were extracted for 35 winter wheat breeding sites in central Asia, eastern Europe and Great Plains of USA from 1961 to 2009. Autumn and winter warming happened gradually, over a long period of time, but mostly before 1991. Climate changes after 1991 were mainly expressed through higher temperatures in spring, May, and June. Clear regional differences were observed for air temperature variation. Breeding sites in the USA seemed to be least subjected to climate change. There were no significant linear trends in yearly, seasonal, or monthly precipitation. Changing climates expressed through rising temperatures during critical stages of winter wheat development have already negatively affected yield gains in several countries, especially in eastern Europe. There are some positive changes associated with warmer winters, which may not require additional investment in traits associated with winter survival. Rising temperatures in spring are of particular concern since their effect on yield is negative in some regions. They certainly accelerate wheat development and shift heading to earlier dates. The interaction of higher temperatures in spring with the rate of crop development and yield is a fundamental issue which requires research. Rising temperatures in June are detrimental for grain development and filling and heat tolerance warrants high priority in breeding programs.

Response of crop yields to climate trends since 1980 in China

We used improved datasets on both climate and crop production to investigate climate trends during the crop growing period and their impacts on yields of major crops (rice, wheat, maize and soybean) in China by county, during 1980-2008. We found clear regional climate trends during this period, particularly for temperature. Such trends have had measurable impacts on crop yields, with a distinct spatial pattern. For the entire country, the planting area-weighted average showed that climate trends from 1980-2008 reduced wheat, maize and soybean yields by 1.27, 1.73 and 0.41%, respectively, while increasing rice yields by 0.56%. As a result, climate trends as a whole reduced wheat and maize production by 3.60 x 10(5) t and 1.53 x 10(6) t, respectively, and increased rice and soybean production by 7.44 x 10(4) t and 4.16 x 10(3) t, respectively. Estimates of climate impacts are smaller than previous estimates that used different scales, datasets and methods. The particular crops and regions that have been most affected and should be priorities for adaptation are maize and wheat in arid and semi-arid areas of northern and northeast China, where droughts induced by increases in temperature and solar radiation could limit the benefits of improved thermal conditions. Climate warming decreases crop yields by accelerating crop development rate, and thus reducing crop growth duration and yield accumulation, and by increasing temperature extremes and heat stress.

Improving the CROPGRO-Tomato Model for Predicting Growth and Yield Response to Temperature

Parameterizing crop models for more accurate response to climate factors such as temperature is important considering potential temperature increases associated with climate change, particularly for tomato (Lycopersicon esculentum Mill.), which is a heat-sensitive crop. The objective of this work was to update the cardinal temperature parameters of the CROPGRO-Tomato model affecting the simulation of crop development, daily dry matter (DM) production, fruit set, and DM partitioning of field-grown tomato from transplanting to harvest. The main adaptation relied on new literature values for cardinal temperature parameters that affect tomato crop phenology, fruit set, and fruit growth. The new cardinal temperature values are considered reliable because they come from recent published experiments conducted in controlled-temperature environments. Use of the new cardinal temperatures in the CROPGRO-Tomato model affected the rate of crop development compared with prior default parameters; thus, we found it necessary to recalibrate genetic coefficients that affect life cycle phases and growth simulated by the model. The model was recalibrated and evaluated with 10 growth analyses data sets collected in field experiments conducted at three locations in Florida (Bradenton, Quincy, and Gainesville) from 1991 to 2007. Use of modified parameters sufficiently improved model performance to provide accurate prediction of crop and fruit DM accumulation throughout the season. Overall, the average root mean square error (RMSE) over all experiments was reduced 44% for leaf area index, 71% for fruit number, and 36% for both aboveground biomass and fruit dry weight simulations with the modified parameters compared with the default. The Willmott d index was higher and was always above 0.92. The CROPGRO-Tomato model with these modified cardinal temperature parameters will predict more accurately tomato growth and yield response to temperature and thus be useful in model applications.

Evaluation of biodegradable mulches for production of warm-season vegetable crops

While plastic soil mulches are widely used in vegetable crop production, removal and disposal of these plastics at the end of the growing season is costly and environmentally unsound. This trial assessed the field performance of several colors of corn-starch-based biodegradable mulches for the production of warm season vegetable crops (sweet corn, zucchini, cantaloupe, pepper and eggplant) over three cropping seasons in Saskatchewan. The clear and wavelength selective types of mulch most commonly produced beneficial effects on the rate of crop development and yields. This may be attributed to these mulch types enhancing soil temperatures, especially early in the growing season. There were no appreciable differences in the soil temperatures or crop growth and yield responses on the biodegradable mulches as compared with the same color of standard low-density polyethylene mulch. The biodegradable mulches were easy to apply and were readily incorporated into the soil at the end of the growing season. Although the clear and to a lesser extent the wavelength selective forms of biodegradable mulch tended to break down well before the end of the growing season, this early failure did not negatively impact the performance of any of the crops tested, as long as supplemental weed control was provided. Supplemental weed control would be more important for slow-growing, erect crops like peppers and eggplants than for the more robust and sprawling crops like corn and melons. Although the biodegradable mulches are more expensive than the corresponding standard polyethylene-based plastics, this added cost is more than offset by the costs to remove and dispose of the standard plastic mulches. Key words: Sweet corn, pepper, zucchini, eggplant, cantaloupe, Biotelo

Timing, Effect, and Recovery from Intraspecific Competition in Maize

In production agriculture, it is not uncommon for a crop to experience both intra‐ and interspecific competition during the normal course of development. Although the competition between crop plants (i.e., intraspecifc) is often considered independently of crop‐weed competition (i.e., interspecific), the mechanisms through which yields are reduced may be common to both. The objective of this study was to use the experimental structure of a critical time for weed removal study to examine the timing and effect of intraspecific competition on maize (Zea mays L.) biomass accumulation and phenological development. A field trial was conducted in which maize stands were thinned from a higher to a lower density at six stages of development. Results indicated that intraspecific competition at densities of 8 and 16 plants m−2 did not affect maize biomass accumulation until the 14th and 12th leaf tip stages, respectively. Before these stages, maize seedling growth at 8 or 16 plants m−2 was not resource limited. Increases in leaf area index and specific leaf area at the onset of intraspecific competition, and the recovery of plants following the removal of competitors, suggest that reductions in the rate of crop growth and development may have been linked to competition for light quantity.

AquaCrop—The FAO Crop Model to Simulate Yield Response to Water: II. Main Algorithms and Software Description

The AquaCrop model was developed to replace the former FAO I&D Paper 33 procedures for the estimation of crop productivity in relation to water supply and agronomic management in a framework based on current plant physiological and soil water budgeting concepts. This paper presents the software of AquaCrop for which the concepts and underlying principles are described in the companion paper (Steduto et al., 2009). Input consists of weather data, crop characteristics, and soil and management characteristics that define the environment in which the crop will develop. Algorithms and calculation procedures modeling the infiltration of water, the drainage out of the root zone, the canopy and root zone development, the evaporation and transpiration rate, the biomass production, and the yield formation are presented. The mechanisms of crop response to cope with water shortage are described by only a few parameters, making the underlying processes more transparent to the user. AquaCrop is a menu‐driven program with a well‐developed user interface. With the help of graphs which are updated each time step (1 d) during the simulation run, the user can track changes in soil water content, and the corresponding changes in crop development, soil evaporation and transpiration rate, biomass production, and yield development. One can halt the simulation at each time step, to study the effect of changes in water related inputs, making the model particularly suitable for developing deficit irrigation strategies and scenario analysis.

Simulating winter wheat development response to temperature: Modifying Malo's exponential sine equation

Predicting crop developmental events is fundamental to simulation models and crop management decisions. Many approaches to predict developmental events have been developed, however, most only simulate the mean time for reaching a developmental event. An exponential sine equation developed by Malo [Malo, J.E., 2002. Modelling unimodal flowering phenology with exponential sine equation. Funct. Ecol. 16, 413–418] to predict flower number over time was modified to incorporate the response of crop development rate to temperature. The revised model (ExpSine model) uses the base, optimum, and maximum cardinal temperatures specific to a crop or genotype. Most model parameters were estimated from the literature, and four of the five model parameters have physiological significance. Model evaluation for winter wheat ( Triticum aestivum L.) was based on two controlled environment studies from the literature and two field experiments conducted in the North China Plain (NCP) and the Tibet Plateau (TPC). The r 2 for the modified temperature response function was 0.74 and 0.91 for two different experiments and compared very well (identical mean r 2's) to an existing function (Beta model) [Yin, X., Kropff, M.J., McLaren, G., Visperas, R.M., 1995. A nonlinear model for crop development rate as a function of temperature. Agric. Forest Meteorol. 77, 1–16]. Differences between observed and predicted flowering dates ranged from −2 to 3 days in the NCP and from −7 to 4 days on the TPC, with the mean percent error in both sites less than 1% and no apparent bias observed in the model. This modification of Malo's exponential sine equation expanded the predictive ability of the original equation to simulate phenology across a broader range of environments. The ExpSine model developed can be used as a phenological module in various crop or ecological simulation models.