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- ItemIFDC’s fifty years of research and development on the use of phosphate rock as fertilizer(SpringerNature Link, 2026-01-20) Hellums, Deborah T; Chien, S.H.; Prochnow, Luis I; Demiss, Mulugeta; Upendra, SinghPhosphate rock (PR) is the key raw material in phosphatic fertilizers. However, the phosphorus (P) in PR is generally unavailable for crop nutrition. Currently, direct application of PR (DAPR) to crops accounts for less than 1% of the global annual P consumption of 21.4 million metric tons (Mt) of P equivalent. This paper reviews the International Fertilizer Development Center’s (IFDC) fifty years of research on DAPR as an alternative or supplement to water-soluble phosphate (WSP) fertilizers in acidic soils of the sub-humid and humid tropics. It highlights the significant advancements IFDC made in identifying basic principles determining the effectiveness of PR fertilizers including mineralogy, chemical reactivity, surface area and influential soil and crop factors. It also summarizes agronomic outcomes and identified economic factors impacting PR use. Examples of the use of the PR decision support system (PRDSS) developed by IFDC to integrate soil, crop, PR source and site factors to predict the relative agronomic effectiveness (RAE) and economic feasibility of the PR source are presented. Finally, the paper summarizes specific farming strategies and ongoing research that will influence the direct application of PR in the future.
- ItemRealizing Soil Health for Food Security in Africa(2024) Sieg Snapp; Jordan Chamberlin; Leigh Winowiecki; Tilahun Amede; Ermias Betemariam; Samuel Gameda; Jeffrey E. Herrick; Rattan Lal; Paswel Marenya; Latha Nagarajan; Zachary P. Stewart; Tor VågenDramatic improvements in soil health are necessary to increase agricultural production and reduce crop failures. We provide recommendations for scaling of soil health and fertility management in Africa through practical approaches to prioritization,evidence-based policy and effective extension.
- ItemIs Seed Aid Distribution Still Justified in South Sudan?(2024-09) Esther Smits; Rob Kuijpers; Justin Amos Miteng; David Deng Chol; Turo Thomas Mono; Nicola FrancesconiSeed aid—or free distribution of seeds to farmers—is a popular intervention to simultaneously reduce food insecurity and dependency on food aid in fragile countries. However, seed aid distribution also has the potential to hinder or distort the development of local seed markets. In this study we analyze the targeting and impact of seed aid across the green belt (cutting across the southern/equatorial states) of South Sudan. Using a primary and unique dataset on 1,990 farm households, we find that seed aid is widely rather than selectively distributed. Almost a third of farm households receive seed aid despite the general availability of locally recycled seed varieties. Seed aid distribution does not seem to favor particularly poor, vulnerable and food insecure households, but those that are embedded in community networks, organizations and institutions. Using a double robust methodology based on Inverse Probability Weighted Regression Adjustment (IPWRA), we also find that the adoption of seed aid by farm households does not result in increased maize production, as it is neither associated with agricultural intensification nor with the expansion of cultivated land. Seed aid seems to substitute rather than supplement local seed varieties. These findings emphasize a lack of intentionality in seed aid distribution. Still, it must be noted that the effectiveness of seed aid distribution may be greater outside our study area, above the green belt, where conflicts and natural disasters remain more frequent and intense, and where farmers are more likely to be seed insecure. But overall, this study supports the widespread perception that South Sudan is ready for a transition towards a market-based seed distribution system.
- ItemRandom Forest Machine Learning for Maize Yield and Agronomic Efficiency Prediction in Ghana(2024-08) Eric Asamoah; Gerard B.M. Heuvelink; Ikram Chairi; Bindraban, Prem S.; Vincent LogahMaize (Zea mays) is an important staple crop for food security in Sub-Saharan Africa. However,there is need to increase production to feed a growing population. In Ghana, this is mainly done by increasing acreage with adverse environmental consequences, rather than yield increment per unit area. Accurate prediction of maize yields and nutrient use efficiency in production is critical to making informed decisions toward economic and ecological sustainability. We trained the random forest machine learning algorithm to predict maize yield and agronomic efficiency in Ghana using soil, climate, environment, and management factors, including fertilizer application. We calibrated and evaluated the performance of the random forest machine learning algorithm using a 5 × 10-fold nested cross-validation approach. Data from 482 maize field trials consisting of 3136 georeferenced treatment plots conducted in Ghana from 1991 to 2020 were used to train the algorithm, identify important predictor variables, and quantify the uncertainties associated with the random forest predictions. The mean error, root mean squared error, model efficiency coefficient and 90 % prediction interval coverage probability were calculated. The results obtained on test data demonstrate good prediction performance for yield (MEC = 0.81) and moderate performance for agronomic efficiency (MEC = 0.63, 0.55 and 0.54 for AE-N, AE-P and AE-K, respectively). We found that climatic variables were less important predictors than soil variables for yield prediction, but temperature was of key importance to yield prediction and rainfall to agronomic efficiency. The developed random forest models provided a better understanding of the drivers of maize yield and agronomic efficiency in a tropical climate and an insight towards improving fertilizer recommendations for sustainable maize production and food security in Sub-Saharan Africa.
- ItemImpact of Tillage and Crop Establishment Methods on Crop Yields, Profitability and Soil Physical Properties in Rice –Wheat System of Indo-Gangetic Plains of India(2014) Vivak Kumar; Yashpal Singh Saharawat; Mahesh K. Gathala; C.M. Parihar; Rajeev Kumar; Robin Kumar; Mangi Lal Jat; A. S. Jat; D.M. Mahala; Lalit Kumar; Hari Sankar Nayak; M.D. Parihar; V.Rai; H.R. Jewlia; B.R. KuriConservation agriculture (CA) based on best-bet crop management practices may increase crop and water productivity, as well as conserve and sustain soil health and natural resources. In a 2-year profitability and soil physical properties in a rice –wheat (RW) system. The six TCE treatments were used to study the impact, which are puddled transplanted rice followed by conventionally tilled wheat (CTPR –CTW), direct seeded rice on the flat followed by zero till wheat (CTDSR –ZTW), zero till direct seeded rice with residue followed by zero till wheat with residue (ZTDSR+R –ZTW+R), transplanted rice after rotavator puddling followed by zero till wheat (RTTPR –ZTW), transplanted rice after rotavator puddling followed by rotary till wheat (RTTPR –RTW) and farmer practice rice – wheat (FP – RW). Result of the study revealed that mean rice yield was not significantly affected by different TCE methods. Wheat planted with ZTDSR+R –ZTW+R gave 30% larger grain yield than FP. Overall, among all the TCE treatments the RW system yields and net returns were maximum under ZTDSR+R –ZTW+R. The fastest mean infiltration rate (0.10 cm/h) was registered in ZTDSR+R –ZTW+R plots, whereas the slowest was in FP plots (0.05 cm/h). Bulk density at 15 –20-cm soil depth was least in ZTDSR+R –ZTW+R (1.70 Mg/m 3 ) and greatest in FP (1.73 Mg/m 3 ). Results from this study revealed that conventionally tilled (CT) and transplanting of rice could be successfully replaced by adoption of the profitable double ZT–RW system.