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Wei Zhou - One of the best experts on this subject based on the ideXlab platform.
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Methodology of fertilizer recommendation based on Yield Response and agronomic efficiency for rice in China
Field Crops Research, 2017Co-Authors: Fuqiang Yang, Mirasol F. Pampolino, Adrian M. Johnston, Wei ZhouAbstract:Abstract A science-based, reliable, and cost-effective fertilizer recommendation method is needed to solve problems of low nutrient use efficiency and Yield brought about by inappropriate fertilization practices in rice ( Oryza sativa L.). We collated results from 2218 on-farm experiments conducted between 2000 and 2013 in major rice-producing regions of China to establish scientific principles and develop a methodology that would support fertilizer recommendations for rice. The study analyzed the relationships among Yield Response, agronomic efficiency (AE), relative Yield (the ratio of the Yield without N or P or K to the Yield of the full NPK), and soil indigenous nutrient supply. On average, Yield Responses to nitrogen (N), phosphorus (P), and potassium (K) fertilizer applications were 2.4, 0.9, and 1.0 t ha −1 , and the AE of N, P, and K application were 13.0, 12.7, and 8.4 kg kg −1 , respectively. Relative Yield was used to classify the soil indigenous nutrient supply; average relative Yields related to N, P, and K were 0.71, 0.89, and 0.89, respectively. A significant negative linear correlation was observed between Yield Response and relative Yield, and a significant quadratic relationship was seen between Yield Response and AE. These findings allowed us to build the Nutrient Expert (NE) for Rice decision support system. With continuous optimization of the NE system in each cropping season, results confirmed the effectiveness of this method in improving rice Yields and profits. Compared with farmers’ practices (FP), NE significantly increased grain Yield in early, middle, and late rice and increased gross profit in middle and late rice during the third year (2015) of field validation. In addition, with NE, there was greater improvement in the recovery efficiency of N (REN) in early, middle, and late rice and the AE of N and partial factor productivity of N (PFPN) in middle rice as compared with FP and soil testing (ST). Results of this study showed good agreement between simulated and observed AE of N application, indicating that NE is a promising nutrient decision support tool that can be used in China.
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Fertilizer recommendation for maize in China based on Yield Response and agronomic efficiency
Field Crops Research, 2014Co-Authors: Mirasol F. Pampolino, Adrian M. Johnston, Shaojun Qiu, Shicheng Zhao, Limin Chuan, Wei ZhouAbstract:Abstract A generic but flexible and location-specific fertilizer recommendation method is necessary due to inappropriate fertilization in China. A new fertilizer recommendation method, Nutrient Expert (NE) for Hybrid Maize , was developed using maize datasets from 2000 to 2010 in main maize production areas. The results showed that the average of indigenous nutrient supply were 130, 41 and 124 kg/ha, the mean of Yield Response were 2.1, 1.2, and 1.2 t/ha, and the average agronomic efficiency were 11.4, 15.7, and 11.8 kg/kg for N, P, and K, respectively. There was a significantly negative exponential relationship between Yield Response and indigenous nutrient supply, and a significant negative linear relationship between Yield Response and relative Yield. Analysis also indicated that the quadratic curve relation was obvious between Yield Response and agronomic efficiency. NE system was established based on Yield Response and agronomic efficiency (AE) through above analysis, and on-farm field experiments were conducted in 408 farmers’ fields to validate this system at seven provinces in China. The results showed that fertilizer recommendation based on NE method could maintain grain Yield and profitability and improve nutrient use efficiency through 4R nutrient stewardship and it is proved to be a promising approach for fertilizer recommendation when soil testing is not timely or not available.
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establishing a scientific basis for fertilizer recommendations for wheat in china Yield Response and agronomic efficiency
Field Crops Research, 2013Co-Authors: Limin Chuan, Mirasol F. Pampolino, Adrian M. Johnston, Shaojun Qiu, Shicheng Zhao, Jiyun Jin, Wei ZhouAbstract:Abstract The inappropriate application of fertilizer has become a common phenomenon in wheat production systems in China and has led to nutrient imbalances, inefficient use and large losses to the environment. However, defining an appropriate fertilization rate remains the foundation to science-based nutrient management. This paper described a new fertilizer recommendation method for wheat in China based on Yield Response and agronomic efficiency using datasets from 2000 to 2011. The results showed that the mean Yield Responses of wheat to N, P and K were 1.7, 1.0 and 0.8 t/ha, respectively. Nitrogen was the nutrient most limiting Yield, followed by P and then K. The soil indigenous nutrient supplies were 122.6 kg N/ha, 38.0 kg P/ha, and 120.2 kg K/ha. The mean agronomic efficiencies were 9.4, 10.2 and 6.5 kg/kg for N, P and K, respectively. There was a significant negative exponential relationship between Yield Response and indigenous nutrient supply, and a significant negative linear correlation between Yield Response and relative Yield. It was also demonstrated a quadratic equation between Yield Response (x) and agronomic efficiency (y) (P
J. B. Prendergast - One of the best experts on this subject based on the ideXlab platform.
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A model of crop Yield Response to irrigation water salinity: theory, testing and application
Irrigation Science, 1993Co-Authors: J. B. PrendergastAbstract:A relationship between crop Yield and irrigation water salinity is developed. The relationship can be used as a production function to quantify the economic ramifications of practices which increase irrigation water salinity, such as disposal of surface and sub-surface saline drainage waters into the irrigation water supply system. Guidelines for the acceptable level of irrigation water salinity in a region can then be established. The model can also be used to determine crop suitability for an irrigation region, if irrigation water salinity is high. Where experimental work is required to determine crop Yield Response to irrigation water salinity, the model can be used as a first estimate of the Response function. The most appropriate experimental treatments can then be allocated. The model adequately predicted crop Response to water salinity, when compared with experimental data.
Eila Turtola - One of the best experts on this subject based on the ideXlab platform.
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Yield Response models to phosphorus application: a research synthesis of Finnish field trials to optimize fertilizer P use of cereals
Nutrient Cycling in Agroecosystems, 2011Co-Authors: Elena Valkama, Risto Uusitalo, Eila TurtolaAbstract:Fertilizer applications should be based on relevant Yield Response models and be economically justified. In this study, we defined the Yield Response models of cereals to phosphorus (P) fertilization on the major Finnish soil types by the means of a research synthesis and meta-analysis. We also calculated economically optimum P rates under different price combinations of P fertilizer (1–3 € kg^−1) and cereal Yields (100–300 € tn^−1), for 1-year decision interval of P applications. Our material consisted of data on P fertilizer experiments conducted in Finland during the last 60 years on clay, coarse-textured mineral and organic soils, with variable soil test P (STP) status at the start of the experiments. The cereals cultivated were spring barley, oats, spring and winter wheat, and winter rye. The applied P rates ranged between 6 and 100 kg ha^−1. For low STP classes, Mitscherlich-type exponential models were appropriate for all soil groups, predicting 17–27% higher maximum Yields when compared to the controls without added P. In contrast, for medium and high STP classes, the Yield Responses to increasing P rates were scattered around zero in most soils. Phosphorus fertilization had also negligible effect on 1,000-seed and test weights. On Finnish cereal farms, when P fertilizer is purchased, the present P rates allowed by the Agri-Environmental Programme are uneconomically high. It appears that P fertilization can be substantially reduced on majority of Finnish fields, or even omitted for years, without economic loss under current (2 € kg^−1) or higher P fertilizer prices.
Dirk Raes - One of the best experts on this subject based on the ideXlab platform.
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Yield Response of sugar beets to water stress under western european conditions
Agricultural Water Management, 2010Co-Authors: Nirman Shrestha, Dirk Raes, Sam Geerts, Stefaan Horemans, Sarah Soentjens, Fabienne Maupas, Philippe ClouetAbstract:The average Yield of sugar beet has almost doubled within the last 30 years. With the raise in average Yields and the increase in sensitivity to water stress of sugar beets, the Yield Response factor (Ky) derived by Doorenbos and Kassam (1979) needs an update. In this article, the soil water balance model BUDGET (Raes et al., 2006) was calibrated and validated to obtain correct estimations of the evapotranspiration deficit (1-ETa/ETc, where ETa=actual crop evapotranspiration and ETc=maximum crop evapotranspiration under standard conditions) of sugar beets in two locations in France. Datasets of observed soil water contents of several years and different irrigation treatments were used. The simulated evapotranspiration deficits and observed Yields were used to derive a seasonal Ky. The obtained linear and polynomial Yield Response relation between observed Yield decline and evapotranspiration deficit showed a high goodness-of-fit. The coefficient of determination (R2)=0.83, the Nash-Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.26 for linear; the coefficient of determination (R2)=0.85, the Nash-Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.25 for polynomial). The results suggested a more pronounced Response of sugar beet to water stress in Europe as compared to the values previously reported by Doorenbos and Kassam (1979). The comparison between the observed and simulated Yields (with the updated Ky) for another site in France confirmed the findings.
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simulating Yield Response of quinoa to water availability with aquacrop
Agronomy Journal, 2009Co-Authors: Sam Geerts, Dirk Raes, Magali Garcia, Roberto Miranda, Jorge Cusicanqui, Cristal Taboada, Jorge Mendoza, Ruben Huanca, Armando Mamani, Octavio CondoriAbstract:The modeling of Yield Response to water is expected to play an increasingly important role in the optimization of crop water productivity (WP) in agriculture. During 3 yr (2004―2007), field experiments were conducted to assess the crop Response to water stress of quinoa (Chenopodium quinoa Willd.) in the Bolivian Altiplano (4000 masl) under different watering conditions (from rain fed, RF, to full irrigation, FI). Crop physiological measurements and comparisons between simulated and observed soil water content (SWC), canopy cover (CC), biomass production, and final seed Yield of a selected number of fields were used to calibrate the AquaCrop model. Subsequently, the model was validated for different locations and varieties using data from other experimental fields and from farmers' fields. Additionally, a sensitivity analysis was performed for key input variables of the parameterized model. AquaCrop simulated well the decrease of the harvest index (HI) of quinoa in Response to drought during early grain filling as observed in the field. Further-on, the procedure for triggering early canopy senescence was deactivated in the model as observed in the field. Biomass WP (g m ―2 ) decreased by 9% under fully irrigated conditions compared with RF and deficit irrigation (DI) conditions, most probably due to severe nutrient depletion. Satisfactory results were obtained for the simulation of total biomass and seed Yield [validation regression R 2 = 0.87 and 0.83, and Nash-Sutcliff efficiency (EF) = 0.82 and 0.79, respectively]. Sensitivity analysis demonstrated the robustness of the AquaCrop model for simulation ofquinoa growth and production, although further improvements of the model for soil nutrient depletion, pests, diseases, and frost are also possible.
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Transformation of Yield Response factor into Jensen's sensitivity index
Irrigation and Drainage Systems, 2002Co-Authors: E.c Kipkorir, Dirk RaesAbstract:Selection of crop production models for use in economicevaluation and optimization of irrigation systems is limitedby the complex nature of these models and the availability ofmodel parameters. Therefore there is need for simplerestimation models, such as the Doorenbos and Kassam's modeland Jensen's model. In this study a function for transformingthe readily available Yield Response factors of Doorenbos andKassam's model to the sensitivity index of Jensen model isderived. The derived function can be used to estimate with theJensen's model, the effect of water stress during particularperiods on relative Yield.
Arild Vold - One of the best experts on this subject based on the ideXlab platform.
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A generalization of ordinary Yield Response functions
Ecological Modelling, 1998Co-Authors: Arild VoldAbstract:Abstract In an integrated model study of economics and ecology by Vatn et al. (1996) , year specific expressions for crop Yield Response as a function of N-fertilization constituted an important link between the economic and ecological models. It was recognized, however, that data were too few to uniquely estimate Yield Response functions in all desired simulation scenarios. In future model studies of this type, however, this problem can be reduced by using a generalization of ordinary Yield Response functions. An ordinary Yield function and a generalized Yield function were based on a modified version of the Michaelis–Menten equation, where the generalized type of Yield function is taking account of the observed differences between years as to how the Yield respond to nitrogen fertilizer. Measurements of dry matter in harvested barley grain from field experiments in south-east Norway (1970–1988) were used for parameter estimation and the predictive power was evaluated by cross validation. Based on the prize of grains and nitrogen fertilizers, both Yield functions were used to calculate the expected economic optimum amount of N-fertilizer. The particular advantage of using a physiologically grounded functional relationship like the Michaelis–Menten equation, drawbacks and strengths of the two types of Yield functions, and the use of dynamic crop-growth models to generate simulated data points of Yield dry weight, for use in situations where real observations are few or completely unavailable, are discussed.