Field Crops Research

Journal: Field Crops Research

Abbreviation

Field crops res.

Publisher

Elsevier

ISSN

0378-4290
1872-6852

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Publications 1 - 10 of 33

Mehlich 3 as an indicator of grain nutrient concentration for five cereals in sub-Saharan Africa
Haefele, Stephan M.; Mossa, Abdul Wahab; Gashu, Dawd; et al. (2024)
Field Crops Research
Context or Problem: Soil testing for available nutrients is an important tool to determine fertilizer rates, however many standard methods test the availability of a single nutrient only. In contrast, Mehlich 3 (M3) is a multi-element test for predicting crop yield responses to the addition of macro and micronutrients. However, the M3 test has rarely been validated against crop nutrient concentrations, which limits its application for dietary improvement studies in sub-Saharan Africa. Objective or Research Question: The primary objective was to test how well the M3 nutrient concentrations corresponds to grain nutrient concentrations as an indicator of plant nutrient status and grain quality. A secondary objective was to compare the performance of the M3 test with other extraction tests. Methods: This study used 1096 paired soil and crop samples of five cereals: maize, rice, sorghum, teff and wheat, covering a broad range of soil types and soil properties in Ethiopia and Malawi (e.g., pH 4.5 - 8.8; Olsen P < 1 - 280 ppm). The samples were selected from a larger collection based on “high” or “low” grain nutrient concentrations in the crop, and the respective soil available nutrients were measured with M3 and other extraction tests: CaCl₂ (P, K, Mg, Mn), Ca(NO₃)₂ (K and Mg), Olsen P, sequential extraction (S), and DTPA (Mn, Fe and Zn). Results: The M3 concentrations followed the trend of the “high” and “low” grain concentrations in nearly all nutrients and crops, and this was statistically significant in teff and wheat for all nutrients. The results were best for macronutrients, and slightly less good for micronutrients, probably because the concentration of micronutrients in the selected soil samples was generally quite low. Compared to the other multi-element extractant (CaCl₂), the M3 test corresponded better to grain concentrations of K and Mg, and equally well to Olsen P, sequential extraction (S), and DTPA predictions of P, S, Zn and Fe, respectively. M3 extracted much greater concentrations than the other tests, and this was more pronounced in alkaline soils. Conclusions: Given that the M3 test corresponded well to grain nutrient concentrations across a range of soils and crops in sub-Saharan Africa (SSA), we conclude that it can be considered a universal test for plant nutrients. We also proposed thresholds for M3 values, defining below optimum, optimum and above optimum soil fertility status. Implications or Significance: These results validate the use of the M3 test to assess soil fertility and develop fertilizer recommendations for improved produce quality to enhance diets in SSA.
Performance and sensitivity to climate change of two DSSAT-CSM cassava models for the Brazilian cultivar BRS Formosa
de Figueiredo Bongiovani, Paola; Sentelhas , Paulo Cesar; Magalhães de Melo , Diego; et al. (2025)
Field Crops Research
Context or problem: Cassava is well-adapted to diverse climates, but its response to future climate conditions remains uncertain. Crop growth models are crucial for predicting climate effects on yield and evaluating strategies to mitigate or adapt to these changes. However, these models require evaluation to simulate yield accurately. Objective or research question: The goal of this study was to evaluate the performance of the of the CSM-CROPSIM-Cassava and CSM-MANIHOT-Cassava models in the DSSAT platform for simulating the yield of the drought- and bacterial blight-tolerant cassava variety BRS Formosa in Brazil's northeast climate. The objectives were: i) to calibrate and assess model performance for estimating BRS Formosa yield, and ii) to analyze the models' sensitivity to changes in temperature, rainfall, and CO2, exploring their potential for climate impact studies. Methods: Calibration was based on the irrigated treatments from Embrapa experiments conducted in Cruz das Almas (2017–2020) and Petrolina (2015/16), while for evaluation the data from rainfed treatments and additional experiments in Cruz das Almas (2012–2018), Guanambi (2013–2015), Laje (2012/13, 2015/16), and Petrolina (2013/14), were used. Calibration involved adjusting 23 genetic coefficients for CSM-CROPSIM-Cassava and 13, for CSM-MANIHOT-Cassava. Results: Model performance was evaluated using statistical indices, showing good accuracy for cassava storage root yield, with MAEs of 2195 and 2425 kg ha⁻¹ and d values of 0.92 and 0.83 for CSM-CROPSIM-Cassava and CSM-MANIHOT-Cassava, respectively. The ensemble of both models, applied to final storage root yield only, further improved performance (MAE = 1973 kg ha⁻¹; d = 0.91). Both models also simulated phenology and canopy traits (leaf number, stem and aboveground biomass) with good accuracy, and were sensitive to air temperature, rainfall, and [CO₂]. Conclusions: The ensemble provided the most reliable estimates of final storage root yield with the current DSSAT versions, whereas the individual models remain valuable for simulating phenology and canopy traits. Implications or significance: The model analyses from this study are essential for estimating future cassava yield in Northeast Brazil, assessing climate risks, and guiding adaptive strategies for sustainable production.
Evaluating DayCent and STICS in simulating the long-term impact of contrasting organic resource amendments on soil organic carbon and maize yields in sub-Saharan Africa
Couëdel , Antoine; Laub , Moritz; Ranaivomanana , Rindra; et al. (2026)
Field Crops Research
Problem: Low crop yields in sub-Saharan Africa mainly result from low soil fertility and insufficient nutrient inputs. A key component of Integrated Soil Fertility Management (ISFM), namely combining inputs of mineral fertilizers and organic resources, presents an opportunity to boost yields and maintain soil organic carbon (SOC) stocks in the long run. Soil-crop models help to assess the performance of ISFM under contrasting soil, climate, and management combinations. Yet, to date, most soil-crop models have been calibrated and tested in temperate conditions. Objective: Our objective was to evaluate and compare the performance of two different soil-crop models, DayCent and STICS, to represent crop yields and SOC dynamics under contrasting organic resource amendments. Methods: We used a large dataset representing 3384 cropping situations (site x season x treatment) from four long-term experiments in Kenya. Each experiment included the same treatments with the addition of two quantities of low- to high-quality organic resource amendments (high vs low C/N ratio, respectively), with (+N) and without (-N) mineral nitrogen fertilizer. Each treatment included a cropped and uncropped subplot, allowing for a unique stepwise calibration of soil and crop parameters. Results: Both models represented SOC and yield dynamics with similar accuracy across sites and treatments. They reproduced SOC dynamics well (nRMSE below 30 %) in the two clayey soils sites but not in the two sandy soils. Yet, in most sites they reproduced well SOC differences between high (Farmyard manure, Thithonia and Calliandra) and low-quality (maize stover and sawdust) organic resources. Models reproduced the average yield across sites and treatments similarly. They reproduced the positive effects of high-quality organic resources and the addition of mineral N on maize yield well. Models had similar inaccuracy in reproducing yield and yield variability under poor-quality organic resources and -N treatments. Conclusion: The stepwise calibration approach used in this study enabled highlighting the models’ strengths and weaknesses in soil and plant simulations. The results suggest that the two models have similar strengths and struggle with the same problems despite having different structures. Collecting detailed plant (leaf area index, plant N uptake) and soil (water, nitrogen dynamics) in-season data from long-term experiments will be critical to exploit the full model complexity and improve their accuracy for tropical conditions.
A comparative analysis of conservation agriculture systems: Benefits and challenges of rotations and intercropping in Zimbabwe
Thierfelder, Christian; Cheesman, Stephanie; Rusinamhodzi, Leonard (2012)
Field Crops Research
Maize-based conservation agriculture systems in Malawi: Long-term trends in productivity
Thierfelder, Christian; Chisui, John L.; Gama, Mphatso; et al. (2013)
Field Crops Research
Morpho-physiological and molecular evaluation of drought tolerance in cassava (Manihot esculenta Crantz)
Orek, Charles; Gruissem, Wilhelm; Ferguson, Morag; et al. (2020)
Field Crops Research
Understanding drought tolerance mechanisms of cassava is a pre-requisite to improve the performance of the crop in water-scarce regions. Several hypotheses have been formulated to suggest how cassava can withstand a prolonged period of drought. We performed field trials under drought conditions with a selection of 37 cassava genotypes to identify phenotypic and molecular patterns associated with drought tolerance. Plant morphologies varied significantly between cassava genotypes under drought conditions in Kenya, which indicates a strong genetic basis for phenotypic differences. Drought stress reduced yield by 59%, the number of edible storage roots by 43% and leaf retention by 50% on average. Over three years and in two experimental field sites, the most drought tolerant genotype bulked 7.1 (±2.1) t/ha yield while the most drought susceptible genotype yielded 3.3 (±1.4) t/ha under drought conditions. The significant positive correlation of yield under irrigated and non-irrigated conditions suggests that selection of genotypes with high yield performance under well-watered or control conditions should be prioritized to identify genotypes with superior performance under drought stress. The positive correlation between yield and leaf retention provided further evidence that leaf longevity positively contributes to yield in water-deficit conditions. Yield differences could be attributed in part to variation in stomatal conductance (gs) because selected drought tolerant genotypes maintained higher gs and delayed stomatal closure as compared to drought susceptible genotypes. Further analysis revealed that genetic or molecular differences for gs between drought tolerant and susceptible genotypes could be detected at early stages of water deficit. These differences likely involve both abscisic acid (ABA)-dependent and ABA-independent molecular pathways.
When does no-till yield more? A global meta-analysis
Pittelkow, Cameron M.; Linquist, Bruce A.; Lundy, Mark E.; et al. (2015)
Field Crops Research
No-till agriculture represents a relatively widely adopted management system that aims to reduce soil erosion, decrease input costs, and sustain long-term crop productivity. However, its impacts on crop yields are variable, and an improved understanding of the factors limiting productivity is needed to support evidence-based management decisions. We conducted a global meta-analysis to evaluate the influence of various crop and environmental variables on no-till relative to conventional tillage yields using data obtained from peer-reviewed publications (678 studies with 6005 paired observations, representing 50 crops and 63 countries). Side-by-side yield comparisons were restricted to studies comparing conventional tillage to no-till practices in the absence of other cropping system modifications. Crop category was the most important factor influencing the overall yield response to no-till followed by aridity index, residue management, no-till duration, and N rate. No-till yields matched conventional tillage yields for oilseed, cotton, and legume crop categories. Among cereals, the negative impacts of no-till were smallest for wheat (−2.6%) and largest for rice (−7.5%) and maize (−7.6%). No-till performed best under rainfed conditions in dry climates, with yields often being equal to or higher than conventional tillage practices. Yields in the first 1–2 years following no-till implementation declined for all crops except oilseeds and cotton, but matched conventional tillage yields after 3–10 years except for maize and wheat in humid climates. Overall, no-till yields were reduced by 12% without N fertilizer addition and 4% with inorganic N addition. Our study highlights factors contributing to and/or decreasing no-till yield gaps and suggests that improved targeting and adaptation, possibly including additional system modifications, are necessary to optimize no-till performance and contribute to food production goals. In addition, our results provide a basis for conducting trade-off analyses to support the development of no-till crop management and international development strategies based on available scientific evidence.
Predicting seed admixture in maize combining flowering characteristics and a Lagrangian stochastic dispersion model
Dietiker, Dominique; Stamp, Peter; Eugster, Werner (2011)
Field Crops Research
Agronomic gain: Definition, approach, and application
Saito, Kazuki; Six, Johan; Komatsu, Shota; et al. (2021)
Field Crops Research
Meeting future global staple crop demand requires continual productivity improvement. Many performance indicators have been proposed to track and measure the increase in productivity while minimizing environmental degradation. However, their use has lagged behind theory, and has not been uniform across crops in different geographies. The consequence is an uneven understanding of opportunities for sustainable intensification. Simple but robust key performance indicators (KPIs) are needed to standardize knowledge across crops and geographies. This paper defines a new term ‘agronomic gain’ based on an improvement in KPIs, including productivity, resource use efficiencies, and soil health that a specific single or combination of agronomic practices delivers under certain environmental conditions. We apply the concept of agronomic gain to the different stages of science-based agronomic innovations and provide a description of different approaches used to assess agronomic gain including yield gap assessment, meta-data analysis, on-station and on-farm studies, impact assessment, panel studies, and use of subnational and national statistics for assessing KPIs at different stages. We mainly focus on studies on rice in sub-Saharan Africa, where large yield gaps exist. Rice is one of the most important staple food crops and plays an essential role in food security in this region. Our analysis identifies major challenges in the assessment of agronomic gain, including differentiating agronomic gain from genetic gain, unreliable in-person interviews, and assessment of some KPIs at a larger scale. To overcome these challenges, we suggest to (i) conduct multi-environment trials for assessing variety × agronomic practice × environment interaction on KPIs, and (ii) develop novel approaches for assessing KPIs, through development of indirect methods using remote-sensing technology, mobile devices for systematized site characterization, and establishment of empirical relationships among KPIs or between agronomic practices and KPIs.
Crop water use under Swiss pedoclimatic conditions – Evaluation of lysimeter data covering a seven-year period
Oberholzer, Simon; Prasuhn, Volker; Hund, Andreas (2017)
Field Crops Research

Publications 1 - 10 of 33

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