The economic value of glyphosate-resistant canola in the management of two widespread crop weeds in a Western Australian farming system

Nitrogen fertilisation is a source of potential groundwater pollution and is a key issue in the current debate about the environmental impacts of agricultural production. It is also a key element in the management of cropping systems by farmers. Therefore, cropping system design entails the understanding and evaluation of farmers' fertilisation practices. Biophysical models describing the soil–plant system can serve this purpose. A comparison between model outputs and farmers' practices was made of a set of 128 apple (Malus domestica Borkh.) plots from 31 members of a farmers' co-operative in south-eastern France. Farmers' fertilisation practices were compared with theoretical practices generated by a series of soil–plant system models of increasing complexity, each model giving the amount of nitrogen that should be applied to the plot according to the knowledge included in the model. The model that reproduced farmers' fertilisation practices most closely was the most complex, taking all plant requirements, soil organic matter and residue mineralisation, denitrification and irrigation supply into account. A Monte Carlo method showed that the differences between farmers' practices and model outputs were not random. Spatial analysis showed a strong spatial organisation of these differences, mainly due to three farms. This congruence between farmers' practices and model outputs suggests the existence of some indicators that depict the N nutrition status of the orchard as a basis for rules indicating how much nitrogen should be applied. The spatial analysis suggests the existence of farmer and neighbourhood effects, which need to be explained. Models appear to be useful tools to study farmers' practices by removing biophysical effects (soil, variety, etc.). This raises new questions concerning agricultural research at the interface between the biophysical and social sciences.     

Evaluation of fertigation scheduling for sugarcane using a vadose zone flow and transport model

Micro-irrigation has become an optimal means for providing water and nutrients to crops. There is an ample space for improving fertilizer use efficiency with micro-irrigation, if the movement and reactions of fertilizers in the soil are well understood. However, the rhizosphere dynamics of nutrients is very complex, depending on many factors such as soil temperature, pH, water content, and soil and plant characteristics. Many factors cannot be easily accurately quantified. However, using state-of-the-art modelling techniques, useful and reliable information can be derived.An attempt was made to evaluate the reactive transport of urea in the root zone of a sugarcane crop under drip irrigation, and to quantify the fluxes of urea, ammonium, and nitrate into the crop roots, volatilization fluxes, and deep drainage using a numerical model. This quantification helped in designing an optimal fertigation schedule. Various parameters used in the model were taken from either the literature or the field study. A typical scenario, based on the recommended total quantity of urea for sugar cane crop under drip irrigation in India, was tested using HYDRUS-2D. The total amount of urea was divided into fortnightly doses, depending on the stage of crop growth. For this scenario, the modelled crop uptake was found to be 30% higher than the crop demand. Consequently, an optimal fertigation schedule was developed that reduced the use of urea by 30% while at the same time providing enough N for its assimilation at all stages of crop growth. This type of modelling study should be used before planning field experiments for designing optimal fertigation schedules.     

I. A decision support system to improve planning and management in large irrigation schemes

This paper describes a decision support system (DSS) that was developed to improve planning and management for the large irrigation schemes in the Alentejo region of Portugal. The system was designed to help in the analysis and evaluation of the crops and crop systems that can potentially be cultivated, together with identification of limitations affecting crop selection and crop yields. It integrates socio-economic and biophysical data at the field level to analyse the performance of an irrigation scheme in terms of the adoption of irrigation by farmers and farmers’ incomes. The final output is given in the form of specific actions and policies for the irrigated areas. The DSS was designed initially to be used in the Alqueva project, a large irrigation scheme that is under construction in Alentejo. Nevertheless, the final framework is generic in nature, being suitable for planning and policy evaluation in other large irrigation schemes.     

Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic–stochastic combined model. Part I: model development

This study describes a model named HydroGEN that was conceived for simulating hydrographs of daily volumes and hourly flow rates during peak-demand periods in pressurized irrigation delivery networks with on-demand operation. The model is based on a methodology consisting of deterministic and stochastic components and is composed of a set of input parameters to reproduce the crop irrigation management practices followed by farmers and of computational procedures enabling to simulate the soil water balance and the irrigation events for all cropped fields supplied by each delivery hydrant in a distribution network. The input data include values of weather, crop, and soil parameters, as well as information on irrigation practices followed by local farmers. The resulting model outputs are generated flow hydrographs during the peak-demand period, which allow the subsequent analysis of performance achievable under different delivery scenarios. The model can be applied either for system design or re-design, as well as for analysis of operation and evaluation of performance achievements of on-demand pressurized irrigation delivery networks. Results from application of HydroGEN to a real pressurized irrigation system at different scales are presented in a companion paper (Part II: model applications).     

Management model for decision support when applying low quality water in irrigation

Use of low quality water for irrigation of food crops is an important option to secure crop productivity in dry regions, alleviate water scarcity and recycle nutrients, but it requires assessment of adverse effects on health and environment. In the EU-project “SAFIR¹” a model system was developed that combines irrigation management with risk evaluation, building on research findings from the different research groups in the SAFIR project. The system applies to field scale irrigation management and aims at assisting users in identifying safe modes of irrigation when applying low quality water. The cornerstone in the model system is the deterministic “Plant-Soil-Atmosphere” model DAISY, which simulates crop growth, water and nitrogen dynamics and if required heavy metals and pathogen fate in the soil. The irrigation and fertigation module calculates irrigation and fertigation requirements based on DAISY's water and nitrogen demands. A Water Source Administration module keeps track of water sources available and their water quality, as well as water treatments, storage, and criteria for selection between different sources. At harvest, the soil concentrations of heavy metals and pathogens are evaluated and the risk to consumers and farmers assessed. Crop profits are calculated, considering fixed and variable costs of input and output. The user can run multiple “what-if” scenarios that include access to different water sources (including wastewater), water treatments, irrigation methods and irrigation and fertilization strategies and evaluate model results in terms of crop yield, water use, fertilizer use, heavy metal accumulation, pathogen exposure and expected profit. The management model system can be used for analysis prior to investments or when preparing a strategy for the season.     

Adapting the CROPGRO model for saline soils: the case for a common bean crop

Water scarcity and severe environmental degradation are causing water managers in the Fergana Valley, Uzbekistan to re-evaluate irrigation water use. Crop models could play an important role in helping farmers decide which systems (crops and irrigation technologies) are feasible. CROPGRO is a physiologically robust agronomic model, although the current version does not consider the effects of soil salinity on crop water use or growth. CROPGRO was modified to include a salinity response function and was tested for gypsiferous soils. A qualitative analysis of the model indicated the model performed as expected under a range of atmospheric, irrigation and crop tolerance scenarios. Model simulations compared very favourably for common bean (Phaseolus vulgaris) to results obtained in the greenhouse for yield and seasonal crop evapotranspiration with values of the Willmott agreement index (i) of 0.98 for both variables evaluated at different levels of salinity and deficit irrigation. Final biomass predictions were less satisfactory, although the modified model performed as well as the original model. The modified model was successfully tested with field data on common bean from an experiment in the Fergana Valley (i of 0.75 for ET and 0.74 for final yield), although the sensitivity of the model to a soil fertility function and relative nodule number made it difficult to assess the model performance.     

Effect of mulching on soil and plant water status, and the growth and yield of wheat (Triticum aestivum L.) in a semi-arid environment

Mulching is one of the important agronomic practices in conserving the soil moisture and modifying the soil physical environment. Wheat, the second most important cereal crop in India, is sensitive to soil moisture stress. Field experiments were conducted during winter seasons of 2004-2005 and 2005-2006 in a sandy loam soil to evaluate the soil and plant water status in wheat under synthetic (transparent and black polyethylene) and organic (rice husk) mulches with limited irrigation and compared with adequate irrigation with no mulch (conventional practices by the farmers). Though all the mulch treatments improved the soil moisture status, rice husk was found to be superior in maintaining optimum soil moisture condition for crop use. The residual soil moisture was also minimum, indicating effective utilization of moisture by the crop under RH. The plant water status, as evaluated by relative water content and leaf water potential were favourable under RH. Specific leaf weight, root length density and dry biomass were also greater in this treatment. Optimum soil and canopy thermal environment of wheat with limited fluctuations were observed under RH, even during dry periods. This produced comparable yield with less water use, enhancing the water use efficiency. Therefore, it may be concluded that under limited irrigation condition, RH mulching will be beneficial for wheat as it is able to maintain better soil and plant water status, leading to higher grain yield and enhanced water use efficiency.     

Two-dimensional modeling of nitrate leaching for various fertigation scenarios under micro-irrigation

The regular application of nitrogen fertilizers by irrigation is likely responsible for the increase in nitrate concentrations of groundwater in areas dominated by irrigated agriculture. Consequently, sustainable agricultural systems must include environmentally sound irrigation practices. To reduce the harmful effects of irrigated agriculture on the environment, the evaluation of alternative irrigation water management practices is essential. Micro-irrigation offers a large degree of control, enabling accurate application according to crop water requirements, thereby minimize leaching. Furthermore, fertigation allows the controlled placement of nutrients near the plant roots, reducing fertilizer losses through leaching into the groundwater. The presented two-dimensional modeling approach provides information to improve fertigation practices. The specific objective of this project was to assess the effect of fertigation strategy and soil type on nitrate leaching potential for four different micro-irrigation systems. We found that seasonal leaching was the highest for coarse-textured soils, and conclude that fertigation at the beginning of the irrigation cycle tends to increase seasonal nitrate leaching. In contrast, fertigation events at the end of the irrigation cycle reduced the potential for nitrate leaching. For all surface-applied irrigation systems on finer-textured soils, lateral spreading of water and nitrates was enhanced by surface water ponding, causing the water to spread across the surface with subsequent infiltration downwards and horizontal spreading of soil nitrate near the soil surface. Leaching potential increased as the difference between the extent of the wetted soil volume and rooting zone increased.     

Evaluation of the RZWQM for the Simulation of Water and Nitrate Movement in Level-Basin,Fertigated Maize

This study concerns the evaluation of the root zone water quality model (RZWQM) to simulate the seasonal water and nitrate movement in a level basin irrigated corn field under three different nitrogen (N) fertilizer treatments. The three N treatments, superimposed over a split basal dose applied before and at planting, were: a single broadcast application of 150 kg N/ha as urea (100% amidic form), a single fertigation application of the same N as UAN (50% amidic, 25% ammonium and 25% nitrate) with the first irrigation, and multiple UAN fertigations with three irrigations. Certain variety-specific maize crop parameters in the model were obtained by fitting these parameters to field data from the single fertigation treatment. The model was then evaluated on water and N results for the treatments. The model adequately simulated the water and nitrate transport for the season, with the seasonal averages of measured and predicted values differing by less than 5%. The most significant differences between measured and simulated water and nitrate occurred near the soil surface (15 cm depth), mostly during the days when the soil was extremely wet following irrigations. With the soil hydraulic properties estimated by simple means, the model tends to overestimate downward water fluxes and related nitrate transport through a compacted layer; however, it is found to be a useful tool to study the relative impacts of alter- nate nitrogen fertilizer and irrigation practices on root zone water quality.     

Development and evaluation of an integrated simulation model for assessing smallholder crop-livestock production in Yucatán, Mexico

Mixed farming systems constitute a large proportion of agricultural production in the tropics, and provide multiple benefits for the world’s poor. However, our understanding of the functioning of these systems is limited. Modeling offers the best approach to quantify outcomes from many interacting causal variables in these systems. The objective of this study was to develop an integrated crop-livestock model to assess biophysical and economic consequences of farming practices exhibited in sheep systems of Yucatán state, Mexico. A Vensim™ dynamic stock-flow feedback model was developed to integrate scientific and practical knowledge of management, flock dynamics, sheep production, partitioning of nutrients, labor, and economic components. The model accesses sheep production and manure quantity and quality data generated using the Small Ruminant Nutrition System (SRNS), and interfaces on a daily basis with an Agricultural Production Systems Simulator (APSIM) model that simulates weather, crop, and soil dynamics. Model evaluation indicated that the integrated model adequately represents the complex interactions that occur between farmers, crops, and livestock.     

Water balance and nitrate leaching in an irrigated maize crop in SW Spain

During 3 consecutive years (1991–1993) a field experiment was conducted in an intensively irrigated agricultural soil in SW Spain. The main objective of this study was to determine the water flow and nitrate (N0₃) leaching, below the root zone, under an irrigated maize crop and after the growing season (bare soil and rainy period). The experiment was carried out on a furrow-irrigated maize crop at two different nitrogen (N)-fertilization rates, one the highest traditionally used by farmers in the region (about 500 kg N ha⁻¹ per year) and the other one-third of the former (170 kg N ha⁻¹ per year). The aim was to obtain data that could be used to propose modifications in N-fertilization to maintain crop yield and to prevent the degradation of the environment. The terms for water balance (crop evapotranspiration, drainage and soil water storage) and nitrate leaching were determined by intensive field monitoring of the soil water content, soil water potential and extraction of the soil solution by a combination of neutron probe, tensiometers and ceramic suction cups. Nitrogen uptake by the plant and N0₃-N produced by mineralization were also determined.The results showed that, in terms of water balance, crop evapotranspiration was similar at both N-fertilization rates used. During the irrigation period, drainage below the root zone was limited. Only in 1992 did the occurrence of rainfall during the early growing period, when the soil was wet from previous irrigation, cause considerable drainage. Nitrate leaching during the whole experimental period amounted to 150 and 43 kg ha⁻¹ in the treatments with high and low N-fertilization, respectively. This occurred mainly during the bare soil and rainy periods, except in 1992 when considerable nitrate leaching was observed during the crop season due to the high drainage. Nitrate leaching was not so high during the bare soil period as might have been expected because of the brought during the experimental period. A reduction of N-fertilization thus strongly decreased nitrate leaching without decreasing yield.     

Flexible delivery schedules to improve farm irrigation and reduce pressure on groundwater: a case study in southern Italy

This study was conducted on an irrigated area of southern Italy to analyze the current operation of a large-scale irrigation delivery system and the effects of the operation procedures on crop irrigation management and aquifer salinity increase. The area is characterized by relatively high levels of groundwater salinity in the summer that are probably due to intensive groundwater pumping by farmers during periods of peak irrigation demand, with the resulting seawater intrusion. Two alternative delivery schedules, namely the rotation delivery schedule and the flexible delivery schedule, referred to as RDS and FDS, respectively, were simulated using a soil-water balance model under different combinations of crop, soil and climatic conditions. The first set of simulations concerned the farm irrigation management constrained by the rotational delivery used by the local water management organization. The second scenario simulated the farm irrigation schedule most commonly used by growers in the area for maximizing crop yields. Based on crop irrigation management under RDS and FDS, two alternative operational scenarios were also developed at the scheme level and then compared for evaluation. Winter and summer salinity maps of the aquifer were developed by interpolating salinity measurements of the groundwater samples collected during the 2006 irrigation season. From these maps, a close relationship can be inferred among delivery schedule, aquifer exploitation and salinity increase, which justifies the need for implementing FDS that might reduce the groundwater demand for irrigation.     

A rule-based method for the development of crop management systems applied to grain sorghum in south-western France

A generic approach is proposed for the development and testing of crop management systems in contrasting situations of water availability. Ecophysiological knowledge, expertise, regional references and simulation models are combined to devise management strategies adapted to production targets and constraints. The next stage consists of converting these crop management strategies into logical and consistent sets of decision rules. Each rule describes the reasoning which is used to apply a technical decision by taking account of observed or simulated environmental conditions or predicted agronomic risks.

This approach was applied to design crop management systems for grain sorghum (Sorghum bicolor L. Moench.) in south-western France. For spring-sown crops, management (sowing date, plant density, varietal choice, N fertilizer rate and timing) was based on water availability, both for economic and environmental reasons. Specific sets of decision rules were written for irrigated and rainfed conditions. The establishment of rules was based on agronomic principles (e.g. for plant density) or on the application of a simulation model (e.g. for sowing date, variety). N fertilization and irrigation were applied using combined N and water dynamic models.

A novel methodology combining crop diagnosis, analytical trials and crop simulation was developed to evaluate the management systems. An irrigated and a rainfed rule-based management system were compared near Toulouse (S.W. France) from 1995 to 2002. The profitability of rainfed low-input management was confirmed for sorghum in spite of high yields under irrigation (up to 10 t ha⁻¹). The adaptation of sorghum management in rainfed conditions was mainly achieved through early maturing cultivars and by reducing N applications by 65%.     

A new stochastic optimization model for deficit irrigation

Deficit irrigation has been suggested as a way to increase system benefits, at the cost of individual benefits, by decreasing the crop water allocation and increasing the total irrigated land. Deterministic methods are common for determining optimal irrigation schedules with deficit irrigation because considering the inherent uncertainty in crop water demands while including the lower and upper bounds on soil moisture availability is a hard problem. To deal with this, a constraint state formulation for stochastic control of the weekly deficit irrigation strategy is proposed. This stochastic formulation is based on the first and second moment analysis of the stochastic soil moisture state variable, considering soil moisture as bounded between a maximum value and a minimum value. As a result, an optimal deficit irrigation scheduling is determined using this explicit stochastic model that does not require discretization of system variables. According to the results, if irrigation strategy is based on deterministic predictions, achievement of high, long-term expected relative net benefits by decreased crop water allocation and increased irrigated land may have a higher failure probability.     

Monitoring water and NO3-N in irrigated maize fields in the Sorraia Watershed, Portugal

The Sorraia Watershed has a long history of continuous irrigated maize. Imprecise water and fertiliser management has contributed to increase nitrate in the groundwater. Solving this problem requires the identification of problem sources and the definition of alternate management practices. This can be performed by an interactive use of selective experimentation and modelling. This paper presents the experimentation phase, where the field experiments were conducted under the irrigation and fertilisation management commonly found in the watershed. Two different soil representatives of the watershed were selected, presenting different water and solute transport properties. One is a silty loam alluvial soil, with a shallow water table, and the other is a sandy soil with a very low water retention capacity. The various terms of the water (consumption, drainage, soil storage) and nitrogen balance (plant uptake, mineralisation and leaching) were obtained from intensive monitoring in the soil profile up to 80 cm, corresponding to the crop root zone. The results showed that in the alluvial soil, up to 70 kg N ha⁻¹ was produced by mineralisation. Current fertiliser management fail in that it does not consider the soil capability to supply mineral nitrogen from the organic nitrogen stored in the profile at planting. This leads to a considerable amount of NO₃-N stored in the soil at harvesting, which is leached during the winter rainy season. In the sandy soil, the poor irrigation management (45% losses by deep percolation), leads to NO₃-N leaching during the crop season and to inefficient nitrogen use by the crop.     

Impact of fertilisation practices on nitrogen leaching under irrigation

Field experiments were carried out over a 2-year period on a loamy soil plot under corn in Montpellier (south-east France). The effectiveness of improved irrigation practices in reducing the adverse impact of irrigation on the environment was assessed. Different irrigation and fertiliser treatments were applied to identify the best irrigation and fertilisation strategy for each technique (furrow and sprinkler) to ensure both good yields and lower NO₃^- leaching. No significant differences in corn yield and NO₃^- leaching were found for the climatic scenario of 1999 between sprinkler and furrow irrigation during the irrigation season. Following the rainy events occurring after plant maturity (and the irrigation season), differences in N leaching were observed between the treatments. The study shows that both the fertiliser method, consisting of applying a fertiliser just before ridging the furrows, and the two-dimensional (2D) infiltration process, greatly influence the N distribution in the soil. N distribution seems to have a beneficial impact on both yield and N leaching under heavy irrigation rates during the cropping season. But, under rainy events (particularly those occurring after harvesting), the N, stored in the upper part of the ridge and not previously taken up by plants, can be released into the deeper soil layers in a furrow-irrigated plot. In contrast, the 1D infiltration process occurring during sprinkler irrigation events affects the entire soil surface in the same way. As a result the same irrigation rate would probably increase N leaching under sprinkler irrigation to a greater extent than under furrow-irrigation during an irrigation period. In order to assess the robustness of these interpretations derived from soil N-profile analysis, a modelling approach was used to test the irrigation and fertilisation strategies under heavy irrigation rates such as those occurring at the downstream part of closed-end furrows. The RAIEOPT and STICS models were used to simulate water application depths, crop yield and NO₃^- leaching on three measurement sites located along the central furrow of each treatment. The use of a 2D water- and solute-transport model such as HYDRUS-2D enabled us to strengthen the conclusions derived from the observations made on the N distribution under a cross-section of furrow. This model helped to illustrate the risk of over-estimation of N leaching when using a simplified 1D solute-transport model such as STICS.     

河套灌区节水灌溉对土壤盐分累积规律的模拟研究

在内蒙古河套实施农业节水对引黄灌区水资源可持续利用具有非常重要的意义。通过河套灌区土壤水盐动态的原位监测,并应用水盐运移和作物耦合模型HYDRUS-EPIC对不同灌溉条件下葵花土壤盐分累积规律进行分析。研究结果表明:现状滴灌条件下葵花生育期土壤表层(0~10cm)盐分呈累积趋势,全盐含量分别比传统地面灌溉和等量地面灌高115%和37%;葵花生育期0~100cm增加的全盐量(ΔC)滴灌比传统地面灌溉高305%,比等量地面灌溉低23%,淋洗是灌区滴灌不可或缺的抑盐措施;滴灌条件下葵花的产量比传统地面灌小6.5%;滴灌产量比等量地面灌高11.7%,增产效果明显。     

Water resources and water use efficiency in the North China Plain: Current status and agronomic management options

Serious water deficits and deteriorating environmental quality are threatening agricultural sustainability in the North China Plain (NCP). This paper addresses spatial and temporal availability of water resources in the NCP, identifies the effects of soil management, irrigation timing and amounts, and crop genetic improvement on water use efficiency (WUE), and then discusses knowledge gaps and research priorities to further improve WUE. Enhanced irrigation and soil nutrient (mainly nitrogen) management are the focal issues in the NCP for enhancing WUE, which are shown to increase WUE by 10-25% in a wheat-maize double cropping system. Crop breeding has also contributed to increased of WUE and is expected to play an important role in the future as genetic and environmental interactions are understood better. Agricultural system models and remote sensing have been used to evaluate and improve current agronomic management practices for increasing WUE at field and regional scales. The low WUE in farmer's fields compared with well-managed experimental sites indicates that more efforts are needed to transfer water-saving technologies to the farmers. We also identified several knowledge gaps for further increasing WUE in the NCP by: (1) increasing scientific understanding of the effects of agronomic management on WUE across various soil and climate conditions; (2) quantifying the interaction between soil water and nitrogen in water-limited agriculture for improving both water and nitrogen-use efficiency; (3) improving irrigation practices (timing and amounts) based on real-time monitoring of water status in soil-crop systems; and (4) maximizing regional WUE by managing water resources and allocation at regional scales.     

Application of epic model to nitrogen cycling in irrigated processing tomatoes under different management systems

Vegetable crops such as processing tomatoes (Lycopersicon esculentum Mill.) are usually complex in terms of nitrogen (N) dynamics because of the large amounts absorbed by the crop, the short growing season and the use of irrigation. Complexity increases when N is supplied from an organic source. A crop simulation model could be very useful to improve N management in this crop. Processing tomatoes were grown on raised beds and furrow irrigated in 1994 and 1995 in the Sacramento Valley of California. Fertilizer N and/or purple vetch (Vicia sativa L.) as green manure and composted turkey manure were used as sources of N. The Erosion Productivity Impact Calculator (EPIC) model was calibrated with 1994 data and validated with 1995 data. Plant growth was accurately simulated in the conventional systems that used fertilizer N and in the low input system that used fertilizer N plus vetch. The model accurately simulated above-ground biomass in a system that used vetch and no synthetic fertilizer N, but it over-predicted Leaf Area Index (LAI). Nitrogen deficiency was observed in the plants in this system. The model simulated nitrogen deficiency mainly as a reduction in biomass production but in the real world the reduction of leaf area was the first effect of nitrogen deficiency in the vegetative phase. Yields were accurately predicted except when diseases affected plant growth. A simple reduction factor of nitrate movement in the bed adequately addressed the movement of nitrate. In general, the model accurately predicted the evolution of inorganic nitrogen in different soil layers during the crop season. However, simulated inorganic N in the upper 15 cm was underestimated in the last part of the crop season and consequently N uptake at harvest was slightly over-predicted in some cases. Nitrogen distribution and access of the roots to inorganic nitrogen are discussed as causes of this discrepancy between model simulated and observed values.     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model

InfoCrop, a generic crop model, simulates the effects of weather, soils, agronomic management (planting, nitrogen, residues and irrigation) and major pests on crop growth, yield, soil carbon, nitrogen and water, and greenhouse gas emissions. This paper presents results of its evaluation in terms of its validation for rice and wheat crops in contrasting agro-environments of tropics, sensitivity to the key inputs, and also illustrates two typical applications of the model. Eleven diverse field experiments, having treatments of location, seasons, varieties, nitrogen management, organic matter, irrigation, and multiple pest incidences were used for validation. Grain yields in these experiments varied from 2.8 to 7.2 ton ha⁻¹ in rice and from 3.6 to 5.5 ton ha⁻¹ in wheat. The results indicated that the model was generally able to explain the differences in biomass, grain yield, emissions of carbon dioxide, methane and nitrous oxides, and long-term trends in soil organic carbon, in diverse agro-environments. The losses in dry matter and grain yield due to different pests and their populations were also explained satisfactorily. There were some discrepancies in the simulated emission of these gases during first few days after sowing/transplanting possibly because of the absence of tillage effects in the model. The sensitivity of the model to change in ambient temperature, crop duration and pest incidence was similar to the available field knowledge. The application of the model to quantify multiple pests damage through iso-loss curves is demonstrated. Another application illustrated is the use of InfoCrop for analyzing the trade-offs between increasing crop production, agronomic management strategies, and their global warming potential.