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Sorghum production in selected states of Sudan during the 2023/24 growing season
No full textThe crop assessment work presented in this report focuses on monitoring the area, yield, and production of sorghum planted during the 2023/24 growing season. Our analysis covers the states of Gedaref, Sennar, and Blue Nile, which are Sudan’s main surplus sorghum producers. Sorghum is Sudan’s staple crop and has been referred to as a banking alternative because it can be safely stored for more than a year in underground pits called Matmuras. For the analysis, we first used satellite data to identify areas (pixels in the satellite images) grown with sorghum. Next, we related the peak normalized difference vegetation index (Peak-NDVI) with yield data obtained from crop cuts. In the last step, we applied the resulting regression line to all sorghum areas. The major insights from the report include the following: ♦ Crop conditions were better than expected despite the many challenges farmers faced in 2023/24; ♦ Sorghum planted area in 2023/24 in Gedaref, Sennar, and Blue Nile States was similar to the previous two years; ♦ The 2023/24 state level average productivity of sorghum was around 1 t/ha; ♦ The 2023/24 estimated total sorghum production was 3.3 million t (by state: Gedaref, 1.70; Sennar, 0.99; and Blue Nile, 0.63 million t).12 page
Les biofabriques, nouveaux modèles de production et d’accès aux intrants agricoles en Amérique latine
No full textLa production et l’accès à des alternatives aux intrants chimiques attirent l’intérêt de nombreux acteurs liés au secteur agricole. En Amérique latine, l’essor des intrants d’origine biologique, ou biointrants - incluant biofertilisants, biocontrôle et biostimulants – offre des réponses à ces enjeux (voir Perspectives 55, mai 2021). Cet essor est le résultat d’années d’investissements publics en recherche et développement, et du dynamisme des industries pour développer des technologies à base de microorganismes, de macroorganismes ou d’extraits végétaux. Mais il passe également par un autre chemin que celui des circuits traditionnels de l’agrofourniture : des ONGs, des réseaux d’agriculteurs, des politiques publiques et même certains acteurs privés encouragent la production de biointrants au sein de biofabriques, directement au sein des exploitations agricoles ou d’installations communautaires en zone rurale. Ces biofabriques ouvrent des perspectives nouvelles, mais font face dans le même temps à des défis majeurs.1–
Mulch application as the overarching factor explaining increase in soil organic carbon stocks under conservation agriculture in two 8-year-old experiments in Zimbabwe
No full textConservation agriculture (CA), combining reduced or no tillage, permanent soil cover, and improved rotations, is often promoted as a climate-smart practice. However, our understanding of the impact of CA and its respective three principles on top- and subsoil organic carbon stocks in the low-input cropping systems of sub-Saharan Africa is rather limited. This study was conducted at two long-term experimental sites established in Zimbabwe in 2013. The soil types were abruptic Lixisols at Domboshava Training Centre (DTC) and xanthic Ferralsol at the University of Zimbabwe farm (UZF). The following six treatments, which were replicated four times, were investigated: conventional tillage (CT), conventional tillage with rotation (CTR), no tillage (NT), no tillage with mulch (NTM), no tillage with rotation (NTR), and no tillage with mulch and rotation (NTMR). Maize (Zea mays L.) was the main crop, and treatments with rotation included cowpea (Vigna unguiculata L. Walp.). The soil organic carbon (SOC) concentration and soil bulk density were determined for samples taken from depths of 0–5, 5–10, 10–15, 15–20, 20–30, 30–40, 40–50, 50–75 and 75–100 cm. Cumulative organic inputs to the soil were also estimated for all treatments. SOC stocks at equivalent soil mass were significantly (p<0.05) higher in the NTM, NTR and NTMR treatments compared with the NT and CT treatments in the top 5 cm and top 10 cm layers at UZF, while SOC stocks were only significantly higher in the NTM and NTMR treatments compared with the NT and CT treatments in the top 5 cm at DTC. NT alone had a slightly negative impact on the top SOC stocks. Cumulative SOC stocks were not significantly different between treatments when considering the whole 100 cm soil profile. Our results show the overarching role of crop residue mulching in CA cropping systems with respect to enhancing SOC stocks but also that this effect is limited to the topsoil. The highest cumulative organic carbon inputs to the soil were observed in NTM treatments at the two sites, and this could probably explain the positive effect on SOC stocks. Moreover, our results show that the combination of at least two CA principles including mulch is required to increase SOC stocks in these low-nitrogen-input cropping systems.151–16
Community-managed seed systems for improved last mile access to quality seed of common bean and groundnut by smallholder farmers in Tanzania
No full text3 page
Progress report: Quantification of carbon sequestration trough conservation agriculture in the Mexican Bajío
No full text6 page
Digitalisation in agriculture: a scoping review of technologies in practice, challenges, and opportunities for smallholder farmers in sub-saharan africa
No full textDigitalisation in agriculture is transforming the way farming is practised worldwide, and its potential benefits for smallholder farmers in sub-Saharan Africa (SSA) are particularly promising. Yet, scientific evidence on the digital technologies utilised by smallholder food producers in SSA and the associated challenges still needs improvement. This review attempts to provide a thorough overview of the technologies currently being employed by smallholder farmers in SSA while also exploring the associated challenges and opportunities. Through a systematic literature search, 27 relevant studies were analysed to identify the region-wise current technologies, challenges, and opportunities. Results show that various digital technologies are employed, including digital extension services and digital marketing of agricultural products. These technologies improve access to information and markets and enhance productivity. However, challenges hinder widespread adoption. Limited internet connectivity, low digital literacy, inadequate infrastructure, and affordability issues impede progress. Gender disparities further limit the equitable distribution of digitalisation benefits. Despite these challenges, significant opportunities arise from adopting digital technologies. The potential advantages are market access, better decision-making capabilities, and increased income and livelihoods. Digitalisation offers transformative possibilities for smallholder farmers in SSA. Overcoming barriers such as limited connectivity and low digital literacy is crucial. By harnessing the opportunities digital technologies can offer, the livelihoods of smallholder farmers can be uplifted, contributing to the growth of agriculture in SSA
Combined use of improved maize hybrids and nitrogen application increases grain yield of maize, under natural Striga hermonthica infestation
No full textStriga hermonthica (Del.) Benth infestation is one of the major constraints to maize production in the Nigeria savannas. The application of nitrogen fertilizer to Striga-resistant hybrids may reduce Striga infection and increase grain yields. The objective of this study was to assess the performance of six maize hybrids at low (30 kg ha−1) and high (120 kg ha−1) nitrogen application under natural infestation with Striga in northern Nigeria in 2014 and 2015. The two nitrogen rates and the six hybrids were arranged in a split-plot design with three replications. The nitrogen treatment was assigned to the main plot while the maize hybrids were assigned to the subplot. Data were collected on number of emerged Striga plants, Striga damage score, total dry matter and grain yield. Results showed that the application of nitrogen at 120 kg ha−1 reduced the number of Striga plants by 58% compared to application at 30 kg N ha−1 in Kafin Madaki and by 48% in Tudun Wada. Nitrogen application at 120 kg N ha−1 also reduced Striga damage rating by 22% in Kafin Madaki and by 33% in Tudun Wada. Both the commercial hybrid (OBASUPER 1) and the susceptible hybrid (8338-1) exhibited higher Striga damage ratings compared to the new hybrids at both locations. Grain yield was 86 and 98% higher in Kafin Madaki and Tudun Wada, respectively, when N was applied at 120 kg N ha−1 than at 30 kg N ha−1. The hybrids M1124-3 and M1227-14 produced grain yields that were significantly higher than those of the other hybrids in all locations. Our results showed that the application of 120 kg N ha−1 to Striga-resistant maize hybrids will reduce Striga infection and increase grain yield
Youth and women quality centers change behavior and improve access to dryland crop seed
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A Bayesian approach to analyzing long-term agricultural experiments
No full textEffective and flexible statistical analyses are key to getting the most out of long-term experiments (LTEs). Here, we aim to introduce Bayesian analysis to the wider LTE community and show how the modelling process differs from traditional statistical analyses. Bayesian methods have become increasingly popular due to more flexibility in model development with better access to statistical software and sampling algorithms. Using Bayes' Theorem, model coefficients are estimated by incorporating any prior knowledge we may have on model terms. Including prior knowledge in this way requires a different estimating procedure for a fitted model. Bayesian model coefficients are usually sampled from thousands of samples from one or more runs of a Markov Chain. We present the use of Bayesian analyses through three examples. Example 1 illustrates a single regression with and without factors using the Broadbalk Long-Term Experiment, showing how the estimated model changes with more uncertainty in our prior knowledge of model coefficients. Example 2 demonstrates the use of multiple regression, predicting grain yield from factor variables and seasonal weather variables. Example 3 shows an estimation of soil carbon changes under crop rotation and fertilization treatments with a hierarchical time series model using a Swedish soil fertility experiment