Crop Production Scenarios Research Articles

Less negative impacts of climate change on crop yields in West Africa in the new CMIP6 climate simulations ensemble

Food insecurity is among one of the greatest risks posed by climate change in Africa, where 90 to 95% of African food production is rainfed and a large proportion of the population already faces chronic hunger and malnutrition. Although, several studies have found robust evidence of future crop yield losses under climate change scenarios, there is wide variation among crops and regions as well as large modeling uncertainties. A large part of this uncertainty stems from climate projections, as climate models may differ in simulating future changes in precipitation and temperature, which could lead to different future crop production scenarios. This work examines the impacts of climate change on crop yields of maize, millet and sorghum in West Africa using climate change projections from the Coupled Model Intercomparison Project 5th Phase (CMIP5) and from the new generation of climate models from the Coupled Model Intercomparison Project 6th Phase (CMIP6). We use the SIMPLACE crop modeling framework to simulate historical and future crop yields, and bootstrap techniques to evaluate projected changes in crop productivity between the CMIP5 and CMIP6 ensembles. Using the new generation of climate models CMIP6, we find that the negative crop yield projections shown by CMIP5 simulations are largely reduced, with even large increases in crop yields when the effect of atmospheric CO2 concentration is considered in the crop model. These differences in crop yield impacts between the CMIP5 and CMIP6 simulations are mainly due to different climate projections of temperature and precipitation in West Africa; CMIP6 projections being significantly wetter and cooler by mid-century and to a lesser extent by the end of the century. Such results highlight the large uncertainties that remain in assessing the impacts of climate change in the region and the consequent difficulty for end-users to anticipate adaptation strategies.

The Assessment of an Effect of Natural Origin Products on the Initial Growth and Development of Maize under Drought Stress and the Occurrence of Selected Pathogens

Poland, like other countries in the world, increasingly experiences the ongoing climate change that is a critical yield-limiting factor. The use of biostimulants in agriculture has shown tremendous potential in combating climate change-induced stresses such as drought, temperature stress, etc. They could be a promising tool in the current crop production scenario. Biostimulants are organic compounds, microbes, or amalgamation of both that could regulate plant growth behavior through molecular alteration and physiological, biochemical, and anatomical modulations. They can promote plant growth under various environmental stresses because they have a positive effect, in particular, on plant growth and resistance. There are many products of this type available on the market, including those of natural origin, which are part of the Integrated Pest Management. The ecotoxicity of chemical plant protection products, the negative effects of their use, and the change in regulations make it recommended to use low-risk chemicals and non-chemical methods, that involve the least risk to health and the environment, and at the same time ensure effective and efficient protection of crops. Natural origin biocomponents obtained by the supercritical CO2 extraction of plant material or by fermentation process in bioreactors were tested. Common maize (Zea mays L.) was selected as a test plant for growth tests at climate chambers. Results showed that the only supernatant (fermentation broth) obtained with the Paenibacillus bacteria (S2) had a positive effect on the germination index (GI > 100%) of maize seeds, compared to the obtained plant seed extracts from the crop of the legume family (Fabaceae) (E3) and from the crop of the smartweed family (Polygonaceae) (E9) (GI < 100%). The extracts E3, S1 (supernatant obtained with the use of bacteria from the genus Enterobacter) and S2 used as a single product and in combination with UAN+S, under optimal conditions of the experiment, had a positive effect on the maize root weight compared to the untreated, while under drought stress, a decrease in the root weight was observed. Moreover, on the basis of the conducted research, differences in the mycelial growth of selected fungi were found. The applied biocomponent S2 of microbial origin extract (supernatant 2) showed a mycelial growth-limiting effect on all tested Fusarium fungi isolated from the corn cobs.

Quantifying the benefits of reducing synthetic nitrogen application policy on ecosystem carbon sequestration and biodiversity

Synthetic Nitrogen (N) usage in agriculture has greatly increased food supply over the past century. However, the intensive use of N fertilizer is nevertheless the source of numerous environmental issues and remains a major challenge for policymakers to understand, measure, and quantify the interactions and trade-offs between ecosystem carbon and terrestrial biodiversity loss. In this study, we investigate the impacts of a public policy scenario that aims to halve N fertilizer application across European Union (EU) agriculture on both carbon (C) sequestration and biodiversity changes. We quantify the impacts by integrating two economic models with an agricultural land surface model and a terrestrial biodiversity model (that uses data from a range of taxonomic groups, including plants, fungi, vertebrates and invertebrates). Here, we show that the two economic scenarios lead to different outcomes in terms of C sequestration potential and biodiversity. Land abandonment associated with increased fertilizer price scenario facilitates higher C sequestration in soils (+ 1014 MtC) and similar species richness levels (+ 1.9%) at the EU scale. On the other hand, the more extensive crop production scenario is associated with lower C sequestration potential in soils (− 97 MtC) and similar species richness levels (− 0.4%) because of a lower area of grazing land. Our results therefore highlight the complexity of the environmental consequences of a nitrogen reduction policy, which will depend fundamentally on how the economic models used to project consequences.

Assessing the Impacts of Recent Crop Expansion on Water Quality in the Missouri River Basin Using the Soil and Water Assessment Tool.

The Missouri River Basin (MORB) has experienced a resurgence of grassland conversion to crop production, which raised concerns on water quality. We applied the Soil and Water Assessment Tool (SWAT) to address how this conversion would impact water quality. We designed three crop production scenarios representing conversion of grassland to: (a) continuous corn; (b) corn/soybean rotation; and (c) corn/wheat rotation to assess the impact. The SWAT model results showed: (a) the lower MORB produced high total nitrogen (TN) and total phosphorus (TP) load before conversion (baseline) due mainly to high precipitation and high agricultural activity; (b) the greatest percentage increases of TN and TP occurred in the North and South Dakotas, coinciding with the highest amount of grassland conversion to cropland; and (c) grassland conversion to continuous corn resulted in the greatest increase in TN and TP loads, followed by conversion to corn/soybean and then conversion to corn/wheat. Although the greatest percentage increases of TN and TP occurred in the North and South Dakotas, these areas still contributed relatively low TN and TP to total basin loads after conversion. However, watersheds, predominantly in the lower MORB continued to be “hotspots” that contributed the greatest amounts of TN and TP to the total basin loads—driven by a combination of grassland conversion, high precipitation, and loading from pre-existing cropland. At the watershed outlet, the TN and TP loads were increased by 6.4% (13,800 t/yr) and 8.7% (3,400 t/yr), respectively, during the 2008–2016 period for the conversion to continuous corn scenario.

ABIOTIC STRESS MODERATION AND CROP PRODUCTION IN CHANGING CLIMATE: BENEFICIALTRACE ELEMENTS: REVIEW

Concerns around food security have emerged in recent years, with rising food demand and the options to meet. The FAO projections indicate that global food demand may increase by 70 percent by 2050, with much of the projected increase in demand for major food crops expectedly coming from soaring population and their dietary changes.Moreover, various abiotic stresses accentuated with changing climate has jeopardized the crop production scenario. Ensuring secured food production in the face of climate change is a formidable challenge. Furthermore, in the post-green revolution period, practice of intensive cultivationand extravagant usage of high analysis fertilizers to over-responsive high yielding cultivars have caused havoc micronutrient mining from the soil itself and thus backfired on sustainable food production. In addition to micronutrients, certain beneficial elements are found to be very useful withbetter plant physiology led crop production and nutritive value of the consumables. These elements are collectively referred to as beneficial-trace elements and play a stellar role in moderating various abiotic stresses. Therefore, the application of beneficial-trace elementsas soil and foliar application is needed to be focusedon toassure quality food production through ensuring their effects on crop physiology

Identifying the resource use and circularity in farm systems: Focus on the energy analysis of agroecosystems

An innovative method is described, assessing the energy flows in farm systems. These systems represent both a socio-economic activity and an agroecosystem. Both market and ecosystem flows are inventoried, focusing on farm agroecosystem circularity of the reinvested biomass. An original system representation is proposed, where process and energy storage sub-systems are distinguished. Biotic energy storage, identified as an Associated Ecosystem (AE) is included. Soil mineralization, reflecting soil activity, was selected as a proxy for services provided by the AE. The present approach was tested on an existing French mixed farm case study. Contrasting scenarios were proposed to test the model and the two sets of selected indicators. EROIs (Energy Return On Energy Invest) evaluate the current system performance through resource use efficiency. Circularities reflect the system resilience. Circin (Inflow Circularity) indicates the system self-sufficiency and the extent to which the farm activity is based on the AE. Temporal stability is assessed by the steadiness of the Circin versus Circout (Outflow Circularity) relationship. The Crop production scenario presents best performance. Specialized and intensive systems present lower Circin values. Furthermore, contrasting Circularities were observed for the intensive breeding scenario, while homogenous results were obtained for the extensive mixed-farming scenario. This method takes a new step towards the integration of circularity and ecosystem support functions in the energy analysis of farm systems. Firstly, it provides indicators of performance and resilience. Secondly, as a key feature for sustainable agriculture, it highlights the relationship between agricultural activity and its associated ecosystem.

Climate Smart Agriculture, need for 21st century to achieve socioeconomic and climate resilience agriculture in India: A geospatial perspective

Climate change is now widely recognized as the major environmental threat occurring mainly due to increasing greenhouse gases in the atmosphere and causing the extinction of biodiversity and enhances disruptions to ecosystems. Climate change risks are found to be very significant and would have a profound impact on the livelihoods of millions of poor people in India. In the present study, we have analyzed datasets of agriculture Greenhouse gases (GHGs) emission (1990-2016), poverty, anthropogenic biomes, agriculture crop production scenario (2008-2017), seasonal soil moisture status present (2006-2015) and deficit (compared with 20 years’ time periods), present (1970-2000) annual mean, future (2050) precipitation and temperature scenario of India and investigated the spatial pattern and relationship incorporating in remote sensing and GIS for the better comprehension of the impact of climate changes on the socio-economic dimension of the people. The total GHGs emissions (CO2 equivalent) from agriculture in India were showing the increasing trend (approximately 1% annually) whereas the increasing trend has decreased notably in the last five years. The states of Bihar, Uttar Pradesh, West Bengal, Assam, Punjab, and Tamil Nadu and Andhra Pradesh of India were found producing higher GHGs emissions from agriculture. The present soil moisture and the deficit during the Kharif, Rabi, and Zaid seasons vary geographically whereas soil moisture deficit during the Kharif season was found very significant over most of the districts of Ganga and Brahmaputra basin. The present mean annual temperature and precipitation patterns were found very significant in arid and semiarid regions which are known as the farmer’s suicide hotspot and are predicted to threaten more in the future (2050). The evaluation highlights the need for synergic approaches such as climate-smart agriculture (CSA) to address the impact of climate change in food production and farmers’ livelihood. Such an investigation gives a solid understanding of a paradigm shift in the adaptation of CSA an approach in prevailing new climate change reality at country or regional levels for achieving socio-economic and climate resilience agriculture in India.

Agronomic and Environmental Aspects of Conservation Agriculture on Wheat Crop Production

Potato (Solanum tuberosum L.) is one of the major vegetable crops of Nepal. Potato is grown all over the globe and consumed as either vegetable or staple food depending upon the crop production scenario. It is also an integral part of human diet. Potato is a high nutrient mining crop and needs higher fertilization for economic tuber production. Despite sufficient application of Nitrogen (N) and Phosphorus (P2O5), low replenishment and widespread potassium deficiency are limiting the potato production in Nepalese condition. Growth parameters such as plant height, leaf area and chlorophyll% was positively correlated with potassium application. Potassium alleviated stresses of frost and drought and reduced incidence of diseases like late blight, black scurf and hollow heart. Potassium also decreased the reducing sugar content and improved chips color and quality. Similarly, potassium application before harvest was found to increase storage life of potato tubers. Furthermore, potassium application significantly increased the yield of potato tubers and quality parameters such as Vitamin C content and specific gravity. Source of potassium and method of potassium application also affected growth, yield and quality parameters. Soil application of potassium in splits coupled with foliar spay was found to perform better. Optimum dose of potassium was recommended for economic tuber production
 Int. J. Appl. Sci. Biotechnol. Vol 7(2): 161-166

Potassium Fertilization in Potato

Potato (Solanum tuberosum L.) is one of the major vegetable crops of Nepal. Potato is grown all over the globe and consumed as either vegetable or staple food depending upon the crop production scenario. It is also an integral part of human diet. Potato is a high nutrient mining crop and needs higher fertilization for economic tuber production. Despite sufficient application of Nitrogen (N) and Phosphorus (P2O5), low replenishment and widespread potassium deficiency are limiting the potato production in Nepalese condition. Growth parameters such as plant height, leaf area and chlorophyll% was positively correlated with potassium application. Potassium alleviated stresses of frost and drought and reduced incidence of diseases like late blight, black scurf and hollow heart. Potassium also decreased the reducing sugar content and improved chips color and quality. Similarly, potassium application before harvest was found to increase storage life of potato tubers. Furthermore, potassium application significantly increased the yield of potato tubers and quality parameters such as Vitamin C content and specific gravity. Source of potassium and method of potassium application also affected growth, yield and quality parameters. Soil application of potassium in splits coupled with foliar spay was found to perform better. Optimum dose of potassium was recommended for economic tuber production.
 Int. J. Appl. Sci. Biotechnol. Vol 7(2): 153-160

Examining the impacts of increased corn production on groundwater quality using a coupled modeling system.

This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirectional and Environmental Policy Integrated Climate modeling system incorporates agricultural management practices and N exchange processes between the soil and atmosphere to estimate levels of N that may volatilize into the atmosphere, re-deposit, and seep or flow into surface and groundwater. Simulated values from this modeling system were used in a land-use regression model to examine associations between groundwater nitrate-N measurements and a suite of factors related to N fertilizer and groundwater nitrate contamination. Multi-variable modeling analysis revealed that the N-fertilizer rate (versus total) applied to irrigated (versus rainfed) grain corn (versus other crops) was the strongest N-related predictor variable of groundwater nitrate-N concentrations. Application of this multi-variable model considered groundwater nitrate-N concentration responses under two corn production scenarios. Findings suggest that increased corn production between 2002 and 2022 could result in 56% to 79% increase in areas vulnerable to groundwater nitrate-N concentrations ≥ 5 mg/L. These above-threshold areas occur on soils with a hydraulic conductivity 13% higher than the rest of the domain. Additionally, the average number of animal feeding operations (AFOs) for these areas was nearly 5 times higher, and the mean N-fertilizer rate was 4 times higher. Finally, we found that areas prone to high groundwater nitrate-N concentrations attributable to the expansion scenario did not occur in new grid cells of irrigated grain-corn croplands, but were clustered around areas of existing corn crops. This application demonstrates the value of the coupled modeling system in developing spatially refined multi-variable models to provide information for geographic locations lacking complete observational data; and in projecting possible groundwater nitrate-N concentration outcomes under alternative future crop production scenarios.

Watershed‐scale impacts of bioenergy crops on hydrology and water quality using improvedSWATmodel

AbstractCellulosic bioenergy feedstock such as perennial grasses and crop residues are expected to play a significant role in meetingUSbiofuel production targets. We used an improved version of the Soil and Water Assessment Tool (SWAT) to forecast impacts on watershed hydrology and water quality by implementing an array of plausible land‐use changes associated with commercial bioenergy crop production for two watersheds in the MidwestUSA. Watershed‐scale impacts were estimated for 13 bioenergy crop production scenarios, including: production ofMiscanthus × giganteusandupland Shawneeswitchgrass on highly erodible landscape positions, agricultural marginal land areas and pastures, removal of corn stover and combinations of these options. Water quality, measured as erosion and sediment loading, was forecasted to improve compared to baseline when perennial grasses were used for bioenergy production, but not with stover removal scenarios. Erosion reduction with perennial energy crop production scenarios ranged between 0.2% and 59%. Stream flow at the watershed outlet was reduced between 0 and 8% across these bioenergy crop production scenarios compared to baseline across the study watersheds. Results indicate that bioenergy production scenarios that incorporate perennial grasses reduced the nonpoint source pollutant load at the watershed outlet compared to the baseline conditions (0–20% for nitrate‐nitrogen and 3–56% for mineral phosphorus); however, the reduction rates were specific to site characteristics and management practices.

Hydrologic and water quality impacts and biomass production potential on marginal land

Marginal land is proposed as viable land resources for biofuel production. However, environmental impacts of perennial biomass production on marginal lands is not clear. This study defined three marginal land types and assessed their availability and potential for biofuel production in the St. Joseph River watershed. The potential impacts were evaluated using the Agricultural Policy/Environmental eXtender (APEX) model. The total area of marginal land was estimated to be 611 km2 covering 21.7% of the watershed. 161 and 207 million liters of bioethanol could be produced from the marginal land utilizing switchgrass and Miscanthus, respectively. Converting marginal land currently under corn/soybean production to switchgrass and Miscanthus reduced water yield by 13.4–36.3% and improved water quality by reducing soil erosion by 27%–98%. Similarly, total nitrogen losses were reduced by 30–91% and total phosphorus losses were reduced by 65–76%, respectively, at the field scales under various energy crop production scenarios.

Streamflow impacts of biofuel policy-driven landscape change.

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.

Pollination services provided to small and large highbush blueberry fields by wild and managed bees

Summary 1. Plantings of pollinator‐dependent crops vary from large, intensively managed fields to small fields that are managed less intensively, yet there is relatively little information on how pollinator populations and their contribution to crop productivity vary across this gradient. 2. We determined the relative importance of wild bees and managed honey bees Apis mellifera L. for crop pollination in the blueberry Vaccinium corymbosum L. system of Michigan, USA, by comparing bee communities in small, isolated blueberry fields with those in large blueberry fields (stocked with managed honey bee hives) and measuring the difference in yields of open‐pollinated and pollinator‐excluded clusters of flowers. We combined these assessments to calculate the contribution of bees to crop production in this system. 3. Wild bees were the dominant pollinators in small fields, comprising 58% of flower‐visiting bees, whereas 97% of bees in large fields were honey bees. Large fields had four times as many bees visiting flowers than small fields, but only one‐tenth as many bumble bees as small fields. 4. Levels of fruit set exceeded 85% in all fields and were similar between field sizes. Berry weight increased with flower exposure to pollinators and was positively correlated with bee abundance. Berry weights from open‐pollinated flowers were twice as high in large fields compared with small fields. 5. By combining berry weight increases attributable to honey bees and wild bees in blueberry fields with measurements of the bee community adjusted for pollinator efficiency, we calculated the relative contributions of honey bees and wild bees to pollination of Michigan blueberries. We estimate that wild bees provide 82% of the pollination in small fields but only 12% of the total pollination services across this system, mostly through their secondary role in large fields. 6. Synthesis and applications. Wild bees are the primary pollinators of small blueberry fields, but these insects are at low abundance in large fields, perhaps due to a lack of nesting resources or competition for resources with honey bees. Our findings highlight the dependence of commercial fruit producers on honey bees and suggest that increasing the pollination contribution of other bees, particularly bumble bees, in large fields will require that growers adopt wild bee conservation strategies or stock their fields with managed colonies. Quantifying the contributions of managed and wild pollinating bees across the range of crop production scenarios will help to direct development of integrated crop pollination strategies to minimize the risk of pollination deficits affecting food production.

Coupling GIS and LCA for biodiversity assessments of land use

Geospatial details about land use are necessary to assess its potential impacts on biodiversity. Geographic information systems (GIS) are adept at modeling land use in a spatially explicit manner, while life cycle assessment (LCA) does not conventionally utilize geospatial information. This study presents a proof-of-concept approach for coupling GIS and LCA for biodiversity assessments of land use and applies it to a case study of ethanol production from agricultural crops in California. GIS modeling was used to generate crop production scenarios for corn and sugar beets that met a range of ethanol production targets. The selected study area was a four-county region in the southern San Joaquin Valley of California, USA. The resulting land use maps were translated into maps of habitat types. From these maps, vectors were created that contained the total areas for each habitat type in the study region. These habitat compositions are treated as elementary input flows and used to calculate different biodiversity impact indicators in a second paper (Geyer et al., submitted). Ten ethanol production scenarios were developed with GIS modeling. Current land use is added as baseline scenario. The parcels selected for corn and sugar beet production were generally in different locations. Moreover, corn and sugar beets are classified as different habitat types. Consequently, the scenarios differed in both the habitat types converted and in the habitat types expanded. Importantly, land use increased nonlinearly with increasing ethanol production targets. The GIS modeling for this study used spatial data that are commonly available in most developed countries and only required functions that are provided in virtually any commercial or open-source GIS software package. This study has demonstrated that GIS-based inventory modeling of land use allows important refinements in LCA theory and practice. Using GIS, land use can be modeled as a geospatial and nonlinear function of output. For each spatially explicit process, land use can be expressed within the conventional structure of LCA methodology as a set of elementary input flows of habitat types.

Patterns of bird abundance along the agricultural gradient of the Pampean region

Bird and land-use surveys were conducted along the agricultural gradient covering from pure croplands through mixed-farming to pure pastoral-farming scenario in the Pampean region of Argentina. Simple regression analyses were performed to analyse the responses of bird abundance to the percentage of land devoted to crop-production. The specific variables associated to bird abundance within both the crop and pastoral-farming landscapes were identified by running redundancy analyses (RDA). The abundance of 20 out of 43 species (47%) was significantly related to the percentage of cropland, finding negative (65%), positive (25%) unimodal (5%) and bimodal (5%) responses of birds to increasing intensity of crop production. The results showed three types of negative and two types of positive responses of bird abundance to the agricultural gradient. RDA revealed the importance of crop-field types in the crop-production scenario and of cattle presence and grass height in the pastoral-farming scenario for the structuring of the grassland bird community. As most species were negatively affected by crop production, the current land-use homogenisation towards high-intensity croplands will most likely result in population decline of many birds in the region.

COUPLING SOYBEAN CYST NEMATODE DAMAGE TO CROPGRO–SOYBEAN

The soybean cyst nematode (SCN) Heterodera glycines Ichinohe is responsible for substantial economic losses in soybean (Glycine max L. Merr.) production throughout the U.S. Results from past efforts to quantify the severity of crop damage resulting from SCN are often subject to variable experimental conditions resulting from differences in weather, soil type, and cultivar. Because of the difficulty in accounting for these variables, a process–oriented crop growth simulation model was chosen as a platform for studying the dynamics of SCN damage and for transferring knowledge between crop production scenarios. The objective of this study was to develop and evaluate hypotheses for coupling SCN damage to the process–oriented crop growth model CROPGRO–Soybean. A monomolecular function was used to relate daily SCN damage to initial population density of SCN eggs. The equation was incorporated into the crop model in order to test two hypotheses of how SCN damage occurs. The first hypothesis was that SCN reduce daily photosynthesis (Pg), while the second hypothesis was that SCN reduce daily potential root water uptake (RWU). Canopy biomass data collected in 1997 and 1998 from a site in Iowa were used to estimate damage function parameters for two distinct coupling points, one applied to reduce daily photosynthesis (Pg) and the other applied to reduce daily potential root water uptake (RWU). Function parameters were estimated by minimizing the log transformation of root mean square error (RMSE) between predicted and measured canopy biomass collected every 2 weeks during the season in Iowa. Biomass data collected in 1997 and 1998 from an independent site in Missouri were used to validate the SCN damage models. The minimum root mean squared errors (RMSE) of canopy and grain biomass were 0.245 and 0.198 log10(kg ha –1 ), respectively, for the RWU coupling point, and 0.238 and 0.193 log10(kg ha –1 ), respectively, for the Pg coupling point at the independent site in Missouri. The damage functions transferred very well to the independent site. Validation showed that the Pg coupling point represented the variability of both canopy and final yield data slightly better than the RWU coupling point.

An Internet-based simulation model for nitrogen management in agricultural settings.

Complex chemical, physical, and biological processes mediate nitrogen (N) transformations and movement during agricultural production, making the optimization of fertilizer use and environmental protection exceedingly difficult. Various computer models have been developed to simulate the site-specific fate and transport of N resulting from different crop production scenarios, but these models are very complex and difficult to use for most farmers, consultants, and conservationists. In an effort to facilitate access and simplify the use of sophisticated models, the U.S. Department of Agriculture (USDA) has developed an Internet-based nitrogen analysis tool. Based on the Nitrate Leaching and Economic Analysis Package (NLEAP), the Web site allows a user to conduct multiyear N simulation modeling specific to a crop field. Servers handle much of the required data assembly and formatting, thus sparing the user's resources. Model runs are executed on the servers and the results are transmitted to the user. This new tool is presented along with early implementation results.

Using Nutrient Uptake Patterns to Develop Efficient Nitrogen Management Strategies for Vegetables

Nitrogen (N) in a soil that is not immediately taken up by a crop is subject to leaching, denitrification and other mechanisms of loss. Nitrogen uptake studies identify the total amount of N accumulated by the crop and the period of peak demand. This information can be used to devise management strategies aimed at supplying N preceding anticipated uptake. Split sidedress application, fertigation, and use of controlled release fertilizers (CRN) are all viable options for N management, depending on the crop production scenario and available infrastructure. Soil and plant tissue testing can be useful feedback tools for adjusting N applications for soil contributions of N and unexpected N losses. Efficient irrigation is of paramount importance in achieving efficient N fertilization regardless of management practice.

Using Nutrient Uptake Patterns to Develop Efficient N Management Strategies for Vegetables

Nitrogen in a soil that is not immediately taken up by a crop is subject to leaching, denitrification, and other mechanisms of loss. Generally, split applications of N throughout the growing season reduce the potential for N loss compared to a single preplant application. Timing of N application should account for the characteristic N uptake patterns of the crop and the lag time between application of fertilizers and plant availability. N uptake studies allow one to identify total amount of N accumulated by the crop and periods of peak nitrogen demand. This information can then be used to devise management strategies aimed at supplying N preceding anticipated N uptake. Split sidedress N application, fertigation, and the use of controlled-release fertilizers are all viable options, depending on the crop production scenario and available infrastructure.