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Ventrella, D., Stellacci, A. M., Castrignanò, A., Charfeddine, M., & Castellini, M. (2016). Effects of crop residue management on winter durum wheat productivity in a long term experiment in Southern Italy. European Journal of Agronomy, 77, 188–198.
Abstract: A long-term experiment comparing different crop residue (CR) managements was established in 1977 in Foggia (Apulia region, southern Italy). The objective of this study was to investigate the long-term effects of different types of crop residue management on main yield response parameters in a continuous cropping system of winter durum wheat. In order to correctly interpret the results, models accounting for spatial error autocorrelation were used and compared with ordinary least square models. Eight crop residue management treatments, based on burning of wheat straw and stubble or their incorporation with or without N fertilization and irrigation, were compared. The experimental design was a complete randomized block with five replicates. Results indicated that the dynamics of yield, grain protein content and hectolitric weight of winter durum wheat did not show any decline as usually expected when a monoculture is carried out for a long time. In addition, the temporal variability of productivity was more affected by meteorological factors, such as air temperature and rainfall, than CR management treatments. Higher wheat grain yields and hectolitric weights quite frequently occurred after burning of wheat straw compared with straw incorporation without nitrogen fertilization and autumn irrigation and this was attributed to temporary mineral N immobilization in the soil. The rate of 50 kg ha(-1) of N seemed to counterbalance this negative effect when good condition of soil moisture occurred in the autumn period, so yielding the same productive level of straw burning treatment. (C) 2016 Elsevier B.V. All rights reserved.
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Dumont, B., Basso, B., Bodson, B., Destain, J. - P., & Destain, M. - F. (2016). Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium. Env. Model. Softw., 79, 184–196.
Abstract: Future progress in wheat yield will rely on identifying genotypes & management practices better adapted to the fluctuating environment Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic & environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 & 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers. (C) 2016 Elsevier Ltd. All rights reserved.
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Constantin, J., Raynal, H., Casellas, E., Hoffman, H., Bindi, M., Doro, L., et al. (2019). Management and spatial resolution effects on yield and water balance at regional scale in crop models. Agricultural and Forest Meteorology, 275, 184–195.
Abstract: Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.
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Siczek, A., Horn, R., Lipiec, J., Usowicz, B., & Łukowski, M. (2015). Effects of soil deformation and surface mulching on soil physical properties and soybean response related to weather conditions. Soil and Tillage Research, 153, 175–184.
Abstract: A field experiment was conducted on Haplic Luvisol developed from loess to assess the effects of soil deformation and straw mulch on soil water status (matric potential), temperature, penetration resistance, soybean growth, seed yield and yield components including straw, protein and oil in 2006-2008. Water use efficiencies related to the amount of rainfall during the growing seasons were calculated for seeds and total above ground biomass. The soil deformation levels (main plots) comprised the following trials: non-compacted (NC, 0 tractor pass), moderately compacted (MC, 3 passes), and strongly compacted (SC, 5 passes). A uniform seedbed in all plots was prepared by harrowing before planting. The main plots included sub-plots without and with surface wheat straw mulch (0.5 kg m(-2)) and the corresponding trials were NC + M, MC + M, SC + M. The amount and distribution of rainfall during the growing season differed among the experimental years with extended drought at bloom-full seed (R2-R6) stages in 2006, good water supply in 2007, and alternative periods with relatively high and low rainfalls in 2008. The effect of soil deformation on matric potential was influenced by weather conditions, soybean growth phase, mulching and depth. The differences were greatest in 2007 and 2008 at R7-R8 growth stages. With increasing deformation level from NC to SC matric potential for 0-15 cm depth during these stages significantly decreased from -401 to -1184 kPa in 2007 and from -1154 to -1432 kPa in 2008. On mulched soil, the corresponding ranges were from -541 to -841 klpa and from -748 to -1386 kPa, respectively. In the dry summer 2006, the differences were smaller and less consistent. Irrespective of soil deformation level, mulching reduced soil temperature in most growth phases but most pronounced initially. Most yield components increased from NC to MC during the experiments which could be attributed to enhanced root water and nutrient uptake rates and decreased from MC to SC due to high soil strength that restrained root growth down to deeper depth. The yields of seeds, straw, protein and oil as well as water productivity of soybean seed and biomass were improved by mulching in 2007-2008. This improvement was more pronounced in 2007 when the mean yield of seeds, protein and oil were significantly greater by 16, 29 and 11%, respectively and was attributed to positive alterations in soil water retention. These results indicate the possibilities of improvement in soybean performance by identifying allowable amount of traffic and mulching practices at planting depending on weather fluctuations during the growing season. Since rainfall and air temperature distribution in 2007 are close to those averaged over a long period of time, the use of straw mulch may positively affect soybean performance and yields excluding anomalously dry years. The positive effect of straw mulch can be enhanced by moderate soil deformation combined with seedbed loosening before planting to avoid constraining effect of soil structure on crop establishment. (C) 2015 Elsevier B.V. All rights reserved.
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Rötter, R. P., Höhn, J. G., & Fronzek, S. (2012). Projections of climate change impacts on crop production: A global and a Nordic perspective. Acta Agriculturae Scandinavica, Section A – Animal Science, 62(4), 166–180.
Abstract: Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few known unknowns’ affecting crop impact projections.
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