AfricaRice Sustainable Productivity Enhancement Program
Permanent URI for this collectionhttps://hdl.handle.net/10568/101111
Browse
Recent Submissions
Item Integrating rainfall index-based insurance with optimal crop management strategies can reduce financial risks for Australian dryland cotton farmers(Journal Article, 2024-12-01) Thong Nguyen-Huy; Kath, J.; Kouadio, L.; King, R.; Mushtaq, S.; Barratt, J.Drought undermines the financial sustainability of farmers. While farmers have adopted various strategies to mitigate some drought impacts, they remain exposed to substantial drought risk. Insurance could be useful in managing climatic risks and for encouraging farmers to take sensible risks (e.g., changing their sowing date to increase yield), but it can be costly. Here, we tested whether the integration of a change in sowing date with rainfall index-based insurance could improve farmer profitability and income stability. We used the Agricultural Production Systems Simulator (APSIM)-Cotton model to simulate cotton lint yields for various sowing dates, taking into account different management strategies, across three dry-land cotton research farm sites – Dalby, Goondiwindi, and Theodore – from 1940 to 2022. We designed the index-based insurance payout when the average rainfall received during the growing season falls below a predefined level, such as the 5th, 10th, or 20th percentile of rainfall. Our study, which involved 3.9 million cotton lint simulations and 3,000 rainfall indexbased insurance products, showed that combining a shift in sowing date with insurance can lead to an income improvement of up to 21.5% at some study sites. Additionally, in drought years, the income improvement for farmers who combined optimal sowing dates with rainfall index-based insurance was up to 48.0%. The framework developed in this study could aid in devising financial strategies to enhance farming resilience during climate extremes.Item Spatiotemporal performance evaluation of high-resolution multiple satellite and reanalysis precipitation products over the semiarid region of India(Journal Article, 2024-10-03) Devadarshin, E.; Bhuvaneswari, K.; Kumar, S.M.; Geethalakshmi, V.; Dhasarathan, M.; Senthil, A.; Senthilraja, K.; Mushtaq, S.; Nguyen-Huy, T.; Mai, T.; Kouadio, L.The present investigation evaluates three satellite precipitation products (SPPs), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Precipitation Climatology Centre (GPCC), Climate Hazard Infrared Precipitation with Station Data (CHIRPS), and two reanalysis datasets, namely, the ERA5 atmosphere reanalysis dataset (ERA5) and Indian Monsoon Data Assimilation and Analysis (IMDAA), against the good quality gridded reference dataset (1991–2022) developed by the India Meteorological Department (IMD). The evaluation was carried out in terms of the rainfall detection ability and estimation accuracy of the products using metrics such as the false alarm ratio (FAR), probability of detection (POD), misses, root mean square error (RMSE), and percent bias (PBIAS). Among all the rainfall products, ERA5 had the best ability to capture rainfall events with a higher POD, followed by MSWEP. Both MSWEP and ERA5 had PODs of 70–100% in more than 90% of the grids and less than 35% of missing rainfall events in the entire Tamil Nadu. In the case of the rainfall estimation accuracy evaluation, the MSWEP exhibited superior performance, with lower RMSEs and biases ranging from − 25 to 25% at the annual and seasonal scales. In northeast monsoon (NEM), CHIRPS demonstrated a comparable performance to that of MSWEP in terms of the RMSE and PBIAS. These findings will help product users select the best reliable rainfall dataset for improved research, diversified applications in various sectors, and policy-making decisions.Item Labour-saving sowing tools for direct dry seeding of rice in Madagascar(Journal Article, 2024-10-16) Andriatsiorimanana, A.; Mujawamariya, Gaudiose; Tefy, Irina Andrianina; Harison Nomenjanahary, Fifaliana; Saito, Kazuki; Senthilkumar, KalimuthuManual rainfed rice sowing is laborious and time-consuming, leading to delayed crop establishment due to labour shortage. To increase production and productivity, we proposed introducing single-row rotary seeders (for dibbling seeds) and fertiseeders (for simultaneous dibbling seeds and fertilizer) for smallholders. We evaluated ‘CFFAMMA seeder’ (already developed seeder by CFFAMMA), ‘New seeder’ (a newly designed seeder), and a fertiseeder in terms of sowing time, crop establishment, and yield in Madagascar. We also obtained farmers’ feedback on the machines’ effectiveness, desirability, their willingness to use, and to pay for it (farmer participatory approach). Finally, we evaluated the profitability of using these machines under rainfed conditions. On-farm experiments across four locations in the central highlands of Madagascar revealed up to 82% time savings using seeders and fertiseeder over two seasons compared with manual methods. The CFFAMMA seeder outperformed the other two, with similar numbers of missing hills, yield, and benefit–cost (B:C) ratios to manual sowing. Despite farmers’ desire to adopt seeders (96%), high cost of equipment acquisition remains a significant obstacle: farmers’ willingness to pay per unit of the equipment (US$8–11); actual price ($68–81). Addressing this financial burden is crucial for wider adoption. Though the seeders and fertiseeder achieved >80% time reduction for sowing and comparable yields to manual methods, fine-tuning of the tools for technical efficiency is also required for wider adoption.Item Leveraging edge artificial intelligence for sustainable agriculture(Journal Article, 2024-06-10) El Jarroudi, M.; Kouadio, L.; Delfosse, P.; Bock, C. H.; Mahlein, A. K.; Fettweis, X.; Mercatoris, B.; Adams, F.; Lenné, J. M.; Hamdioui, S.Effectively feeding a burgeoning world population is one of the main goals of sustainable agricultural practices. Digital technology, such as edge artificial intelligence (AI), has the potential to introduce substantial benefits to agriculture by enhancing farming practices that can improve agricultural production efficiency, yield, quality and safety. However, the adoption of edge AI faces several challenges, including the need for innovative and efficient edge AI solutions and greater investment in infrastructure and training, all compounded by various environmental, social and economic constraints. Here we provide a roadmap for leveraging edge AI at the intersection of food production and sustainability.Item Paddy rice yield and greenhouse gas emissions: Any trade-off due to co-application of biochar and nitrogen fertilizer? A systematic review(Journal Article, 2023-11-11) Iboko, M.P.; Dossou-Yovo, Elliott Ronald; Obalum, S.E.; Oraegbunam, C.J.; Diedhiou, S.; Brümmer, C.C.; Teme, N.G.Combined application of biochar and nitrogen (N) fertilizer could offer opportunities to increase rice yield and reduce methane emissions from paddy fields. However, this strategy may increase nitrous oxide (N2O) emissions, hence its interactive effects on GHG emissions, global warming potential (GWP) and GHG intensity (GHGI) remained poorly understood. We conducted a systematic review to i) evaluate the overall effects of combined application of biochar and N fertilizer rates on GHGs emissions, GWP, rice yield, and GHGI, ii) determine the quantities of biochar and N-fertilizer application that increase rice yield and reduce GHGs emissions and GHGI, and iii) examine the effects of biochar and different types of nitrogen fertilizers on rice yield, GHGs, GWP, and GHGI using data from 45 research articles and 183 paired observations. The extracted data were grouped based on biochar and N rates used by researchers as well as N fertiliser types. Accordingly, biochar rates were grouped into low (≤9 tons/ha), medium (>9 and ≤ 20 ton/ha) and high (>20 tons/ha), while N rates were grouped into three categories: low (≤140 kg N/ha), medium (>140 and ≤ 240 kg N/ha), and high (>240 kg N/ha). For fertiliser types, N rates were grouped as: low (≤150 kg N/ha), medium (>150 and ≤250 kg N/ha), and high (>250 kg N/ha) and N types into: urea, NPK, NPK plus urea (NPK_urea) and NPK plus (NH4)2SO4 (NPK_(NH4)2SO4). Results showed that biochar and N fertiliser significantly affected GHGs emissions, GWP, GHGI and rice yield. Compared to control (i.e., sole N application), co-application of high biochar and medium N rates significantly decreased CH4 emission (82 %) while low biochar with low N rates enhanced CH4 emission (114 %). In contrast, high biochar combined with low N decreased N2O emission by 91 % whereas medium biochar and high N rates resulted in 82 % increase in N2O emission relative to control. The highest GWP and GHGI were observed under co-application of medium biochar and low N rates. Highest rice yield was observed under low biochar rate and high N rate. Regardless of N fertiliser type and biochar rates, increasing N rates increased rice yield and N2O emissions. The highest GWP and GHGI were recorded under sole NPK application. Combination of low biochar and medium N produced low GHGs emissions, high grain yield, and the lowest GHGI, and could be recommended to smallholder farmers to increase rice yield and reduce greenhouse gas emissions from paddy rice field. Further studies should be conducted to evaluate the effects of biochar properties on soil characteristics and greenhouse gas emissions.Item Farmer segmentation methodology training(Report, 2024-02-29) Andriatsiorimanana, A.; Assefa, B.; Senthilkumar, K.Item RiceAdvice Lite boosts agronomic gains key performance indicators in irrigated rice in Nigeria(Report, 2024-10-15) Ibrahim, Ali; Alvari, C.; Awio, T.; Saito, Kazuki; Senthilkumar, KalimuthuItem Agronomic and economic evaluation of ratoon rice cropping systems with perennial rice varieties in West Africa(Journal Article, 2024) Dossou-Yovo, E.R.; Ibrahim, A.; Akpoffo, M.A.Y.; Belko, N.; Ndindeng, S.A.; Saito, K.; Futakuchi, K.Context: With rapid population increase, labour scarcity, and soil nutrient depletion, agricultural lands must be used sustainably to meet the ever-increasing demands for food and livelihood. Perennial rice varieties show promise in meeting the conflicting needs for reducing input use while increasing agricultural production. But, little is known about their agronomic and economic performances and the suitable cropping system in West Africa. Objective: The objective of this study was to evaluate the effects of the cropping system and perennial rice variety on grain yield, labour productivity, and profitability in irrigated lowlands in West Africa. Methods: Experiments were conducted over two years at two sites: Mbe in Cote ˆ d′Ivoire and Ndiaye in Senegal located in the sub-humid and Sahelian climatic zones, respectively. The treatments consisted of three cropping systems [one transplanting and two ratoons per year (rice–ratoon–ratoon), one transplanting and all other ratoons (rice–ratoon continuous), and transplanting twice a year (rice–rice)], and six varieties (five perennial rice varieties: PR101, PR107, PR23, PR24, and PR25 and a local check variety, which was WITA9 and Sahel108 in Mbe and Ndiaye, respectively. Results: There were significant effects of the cropping system and variety, and their interaction on grain yield, labour productivity, and profitability at both sites. In the rice–ratoon–ratoon system, the cumulative grain yield over two years of PR23 and PR25 at Mbe (28.8 t/ha) and PR107 at Ndiaye (22.1 t/ha) was similar to that of the local check in the rice–rice system. The average cumulative grain yield across varieties over two years was the lowest in rice–ratoon continuous system at both sites. Grain yield declined with an increased number of ratoon cropping seasons in the rice–ratoon continuous system. Crop duration and the percentage of regrowth rates (ratio of the number of panicles of the ratoon crop to the number of panicles of the main crop in percentage) were the main drivers of grain yield in the ratoon cropping seasons. At Mbe, the highest labour productivity (39.6 – 39.9 kg/day) and profit (5814 – 5844 USD/ha) were achieved with PR23 and PR25 in the rice–ratoon–ratoon system, while at Ndiaye, the highest labour productivity (24.3 kg/day) and profit (2689 USD/ha) were achieved with PR107 in the rice–ratoon–ratoon system, as they had lower labour input and production costs than those in the rice–rice system with the local check. Conclusions: Grain yield could not be sustained in two years of the continuous ratoon cropping system with perennial rice. The rice–ratoon–ratoon system with PR23 and PR25 at Mbe and PR107 at Ndiaye offers alternative options to the conventional rice–rice system for increasing labour productivity and profitability but may require more water due to the longer crop duration. Implications: Realizing the full potential of perennial rice requires the identification of the causes of rapid yield decline and the development of agronomic practices for enhancing grain yield under ratoon cropping systems in West Africa.Item Maize-grain zinc and iron concentrations as influenced by agronomic management and biophysical factors: a meta-analysis(Journal Article, 2024-08-05) Kihara, Job; Sileshi, Gudeta W.; Bolo, Peter; Mutambu, Dominic; Senthilkumar, Kalimuthu; Sila, Andrew; Devkota, Mina; Saito, KazukiHuman Zn and Fe deficiencies can be reduced through agronomic biofortification, but information on factors influencing maize grain-Zn and -Fe levels remain scanty. This analysis: (1) Establishes the global distribution of Zn and Fe concentrations in maize grain; (2) assess the contribution of different agronomic practices to the effectiveness of Zn fertilizers for increasing grain yields, and Zn and Fe levels in maize grain; and (3) identify key biophysical factors and metrics to more effectively guide agronomic biofortification of Zn. Using 5874 data points in 138 published papers from 34 countries, we estimated a 7.5% probability of grain-Zn concentrations exceeding the benchmark target of 38 mg kg −1 . Using 3187 data points from 65 studies across 27 countries we estimated a 8.5% probability of grain-Fe concentrations exceeding the target of 60 mg kg −1 . Our 70-paper meta-analysis revealed that applying Zn and/or Fe in combination with inorganic NPK fertilizer can increase maize-grain-Zn and-Fe concentrations by 31% ( p < 0.01) relative to the control (NPK only). In 52% and 37.5% of the studies respectively, grain-Zn and -Fe levels showed significant and concomitant increase with grain-yield increases. Soil organic matter, pH, soil-available Zn, organic input applications, and N, Zn and Fe application rates and methods were among the key factors influencing grain Zn and Fe. We conclude there is substantial room for increasing maize-grain Zn and Fe concentrations, and applying Zn, especially in combined soil and foliar applications, gives substantial increases in grain-Zn and -Fe concentrations. This global review reveals large data gaps on maize-grain nutrient levels, and we call for routine collection of such information in future research.Item Assessing the spatial distribution patterns of suitable inland valleys for rice development: a case study of two contrasting regions in Benin(Journal Article, 2024-05-17) Djagba, J. F.; Dossou‑Yovo, E. R.; Sintondji, L. O.; Vissin, E. W.; Zwart, Sander JaapTo increase rice production in Africa, both intensification and area expansion are needed. Inland valley (IV) agroecosystems are important for rice production due to their relatively high water availability and soil fertility. However, the spatial distribution of suitable IVs remains uncertain. The objective of this study was to model spatial distribution patterns of suitable IV areas for rice production. Biophysical, socioeconomic and management practice data were collected from 242 IVs in two contrasting regions in Benin, namely, the Departments of Mono and Couffo (Mono-Couffo) and the Upper Ouémé River catchment (Upper Ouémé). Geographically weighted regression (GWR) and ordinary least squares (OLS) models were used to predict the spatial distribution of suitable IV areas for rice production. The results showed that the GWR model performed better than the OLS model in assessing the IV suitability spatial distribution. There were 177,714 ha (46%) and 431,954 ha (31%) of highly suitable IVs for rice production in Mono-Couffo and Upper Ouémé, respectively. The most significant variables for predicting suitable IV areas for rice production were irrigation water resources, soil fertility management and total nitrogen in topsoil in Mono-Couffo and the number of male farmers in the IV, shallow water table duration at the IV bottom, and elevation in Upper Ouémé. These results demonstrated the effectiveness of the GWR model in assessing the distribution of highly suitable IVs.Item Intensifying rice production to reduce imports and land conversion in Africa(Journal Article, 2024-01-27) Yuan, Shen; Saito, Kazuki; van Oort, Pepijn A. J.; Ittersum, Martin K. van; Peng, Shaobing; Grassini, PatricioAfrica produces around 60% of the rice the continent consumes, relying heavily on rice imports to fulfill the rest of the domestic demand. Over the past 10 years, the rice-agricultural area increased nearly 40%, while average yield remained stagnant. Here we used a process-based crop simulation modelling approach combined with local weather, soil, and management datasets to evaluate the potential to increase rice production on existing cropland area in Africa and assess cropland expansion and rice imports by year 2050 for different scenarios of yield intensification. We find that Africa can avoid further increases in rice imports, and even reduce them, through a combination of cropland expansion following the historical trend together with closure of the current exploitable yield gap by half or more. Without substantial increase in rice yields, meeting future rice demand will require larger rice imports and/or land conversion than now.Item Assessing genetic and agronomic gains in rice yield in sub-Saharan Africa: A meta-analysis(Journal Article, 2022-10-15) Ibrahim, A.; Saito, KazukiResearch for development efforts for increasing rice yield in sub-Saharan Africa (SSA) have largely concentrated on genetic improvement and agronomy for more than 50 years. Here we perform the first meta-analysis to quantify genetic gain - yield increase through use of new variety and calculated by yield difference between new variety and variety popularly grown in the target site, and agronomic gain - difference in yield between improved agronomic practices and the control in SSA using 208 paired observations from 40 studies across 12 countries. Among the studies, 41 %, 34 %, and 25 % were from irrigated lowland, rainfed lowland, and rainfed upland rice, respectively. Seventy percent of the studies reported in this paper were conducted on research stations. In agronomic practices, inorganic fertilizer management practices accounted for 78 % of the studies, of which 48 % were nitrogen (N) management. In each study, we identified four types of varieties: check variety (VC), variety with highest yield in the control (VHC), variety with highest yield under improved agronomic practices (VHT), and variety with largest yield difference between improved agronomic practices and control (VHR). VHT was the same as VHC in 35 % of observations, whereas VHR and VHT were the same in 51 %. These indicate that it is possible to develop varieties adapted to different agronomic practices and high-yielding varieties tend to be responsive to improved agronomic practices. On average, total gain in yield with improved agronomic practices and VHT was 1.6 t/ha. Agronomic practice accounted for 75 % of the total variation in total yield gain with variety and agronomic practice by variety interaction responsible for 19 % and 6 %, respectively. Genetic gains in yield with VHC, VHT, and VHR were 0.7, 0.3, and −0.3 t/ha in control, and 0.4, 0.9, and 0.5 t/ha in improved agronomic practices. Agronomic gain in yield averaged 0.5, 0.8, 1.4, and 1.6 t/ha in VHC, VC, VHT, and VHR, respectively. Agronomic gain in yield of VHT was higher than genetic gain under improved agronomic practices in 54 % of observations. Agronomic gain was highest in irrigated lowland rice, followed by rainfed lowland rice. Higher agronomic gain in yield was also associated with larger difference in N application rate between improved agronomic practices and control. Whereas agronomic practices had larger contribution to total gain in yield than genetic improvement in this study, future assessment of agronomic and genetic gains in yield is warranted. Such assessment should focus more on rainfed rice systems, where agronomic gain was small, take into account genetic improvement rate over time and integrated agronomic practices rather than single intervention like nutrient management practice only, and be conducted in farmers’ fields.