Person: Craufurd, P.
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Craufurd
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Craufurd, P.
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0000-0001-8559-0174 17 results
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- New frontiers in agricultural extension - volume 1(CIMMYT, 2019) Singh, A.K.; Craufurd, P.; Mcdonald, A.; Singh, A.K.; Kumar, A.; Singh, Randhir; Singh, B.; Singh, S.; Kumar, V.; Malik, R.India’s self-sufficiency in food is widely regarded as its greatest achievement since Independence. The green revolution has played a great supporting role in increasing the income of rural households (HHs) where farms are too small and ecologies are too diverse. The topdown scaling out process was fundamental to the accelerated adoption of green revolution technologies in late 1960s and 70s. However, with the current development of an extensive network of KVKs, Indian agriculture has the opportunity to use diagnostic surveys and analytical tools for planning and implementing scaling-up and scalingout strategies in a bottom-up approach rather than a top-down process. In this book, data based evidence has been utilised for monitoring, evaluation and learning (ME&L) of adoption patterns of technologies. The objective is to achieve accelerated adoption of technologies in different ways, wherein extension also acts as part of priority setting (testing and evaluation at scale plus learning/feedback), and the sum of these components brings the specific technological intervention to focus. This publication on “New Frontiers in Agricultural Extension”, based on a landscape diagnostic survey of approximately 8,000 fields, is the first in series of three publications from the BMGF-funded KVK-CSISA network project being implemented by Indian Council of Agricultural Research (ICAR). The publication provides evidence on how different technologies are being accepted by farmers and how to improve the delivery system of technologies. The challenge has been to analyse how technologies were modified as they diffused and became more reliable and acceptable by a larger proportion of farmers. The Agricultural Extension Division (ICAR), through its Agricultural Technology Application and Research Institutes (ATARIs), hoped to create an end-to-end feedback mechanism for research and extension, as well as a digital transformation based convergence program, that will define the impact pathways of its KVK system and change the way research and extension systems operate. The innovations include: methods to design spatially representative surveys, digital survey data collection tools that enable rapid data uploading, a web-based portal hosted by ICAR to make data visible and accessible, and data analysis packages in open-source software for analysis. Data have enabled us to increase the reach of KVKs, and once properly analysed such data sets can help KVKs and their parent institutions to serve in a better way and a much larger population of farmers. The first volume of this document “New Frontiers in Agricultural Extension” incorporates the main outcomes of landscape diagnostic survey (LDS) of wheat across 29 districts of Bihar and nine districts of Eastern Uttar Pradesh with 7,648 data points (wheat) and from Odisha with 400 data points (rice). The project has set a target to conduct the LDS in 110 districts across eight ATARIs with more than 40,000 data points. This volume contains the methodology involved in LDS, data from respondent farmers on the production practices of wheat and rice, and their relationship with existing recommendations. It also contains a priority setting exercise that can be shared with multi-disciplinary research teams in the research institutes including State Agricultural Universities (SAUs) and with Department of Agriculture (DoA) in the concerned state. This publication will help in developing a vibrant and faster cycle of research and extension, by improving the linkage with DoAs for better seasonal planning and linking it with research institutions for setting research priorities and strengthening the monitoring, evaluation and learning (ME&L) in NARES.
Publication - Options for calibrating CERES-maize genotype specific parameters under data-scarce environments(Public Library of Science, 2019) Adnan, A.A.; Diels, J.; Jibrin, J.M.; Kamara, A.Y.; Craufurd, P.; Shaibu, A.S.; Mohammed, I.B.; Tonnang, H.
Publication - Balanced nutrient requirements for maize in the Northern Nigerian Savanna: parameterization and validation of QUEFTS model(Elsevier, 2019) Shehu, B.M.; Lawan, B.A.; Jibrin, J.M.; Kamara, A.Y.; Mohammed, I.B.; Rurinda, J.; Shamie Zingore; Craufurd, P.; Vanlauwe, B.; Adam, A.M.; Merckx, R.Establishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna “NGS” and Sudan Savanna “SS”) were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone; 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone; and 35 and 79 for N, 199 and 528 for P and 24 and 124 for K when the data of the two zones were combined. There was a close agreement between observed and parameterized QUEFTS predicted yields in each of the agro-ecological zone (R2 = 0.69 for the NGS and 0.75 for the SS). Although with a slight reduction in the prediction power, a good fit between the observed and model predicted grain yield was also detected when the data for the two agro-ecological zones were combined (R2 = 0.67). Therefore, across the two agro-ecological zones, the model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 t ha−1 ), the model showed above-ground balanced nutrient uptake of 20.7, 3.4 and 27.1 kg N, P, and K, respectively, per one tonne of maize grain. These results suggest an average NPK ratio in the plant dry matter of about 6.1:1:7.9. We concluded that the QUEFTS model can be widely used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.
Publication - Farmers’ preferences for high-input agriculture supported by site-specific extension services: evidence from a choice experiment in Nigeria(Elsevier, 2019) Oyakhilomen Oyinbo; Chamberlin, J.; Vanlauwe, B.; Liesbet Vranken; Kamara, A.Y.; Craufurd, P.; Maertens, M.Agricultural extension to improve yields of staple food crops and close the yield gap in Sub-Saharan Africa often entails general recommendations on soil fertility management that are distributed to farmers in a large growing area. Site-specific extension recommendations that are better tailored to the needs of individual farmers and fields, and enabled by digital technologies, could potentially bring about yield and productivity improvements. In this paper, we analyze farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. We use a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results. We find that farmers have strong preferences to switch from general to ICT-enabled site-specific soil fertility management recommendations which lend credence to the inclusion of digital technologies in agricultural extension. We find heterogeneity in preferences that is correlated with farmers' resource endowments and access to services. A first group of farmers are strong potential adopters; they are better-off, less sensitive to risk, and are more willing to invest in a high-input maize production system. A second group of farmers are weak potential adopters; they have lower incomes and fewer productive assets, are more sensitive to yield variability, and prefer less capital and labor intensive production techniques. Our empirical findings imply that improving the design of extension tools to enable provision of information on the riskiness of expected outcomes and flexibility in switching between low-risk and high-risk recommendations will help farmers to make better informed decisions, and thereby improve the uptake of extension advice and the efficiency of extension programs.
Publication - Maize crop nutrient input requirements for food security in sub-Saharan Africa(Elsevier, 2019) Berge, H.F.M. ten; Hijbeek, R.; Van Loon, M.P.; Rurinda, J.; Tesfaye, K.; Shamie Zingore; Craufurd, P.; Heerwaarden, J. van; Brentrup, F.; Schröder, J.J.; Boogaard, H.; De Groote, H.; Ittersum, M.K. vanNutrient limitation is a major constraint in crop production in sub-Saharan Africa (SSA). Here, we propose a generic and simple equilibrium model to estimate minimum input requirements of nitrogen, phosphorus and potassium for target yields in cereal crops under highly efficient management. The model was combined with Global Yield Gap Atlas data to explore minimum input requirements for self-sufficiency in 2050 for maize in nine countries in SSA. We estimate that yields have to increase from the current ca. 20% of water-limited yield potential to approximately 50–75% of the potential depending on the scenario investigated. Minimum nutrient input requirements must rise disproportionately more, with N input increasing 9-fold or 15-fold, because current production largely relies on soil nutrient mining, which cannot be sustained into the future.
Publication - A spatial framework for ex-ante impact assessment of agricultural technologies(Elsevier, 2019) Andrade, J.F.; Rattalino Edreira, J.I.; Farrow, A.; Van Loon, M.P.; Craufurd, P.; Rurinda, J.; Shamie Zingore; Chamberlin, J.; Claessens, L.; Adewopo, J.; Ittersum, M.K. van; Cassman, K.G.; Grassini, P.Traditional agricultural research and extension relies on replicated field experiments, on-farm trials, and demonstration plots to evaluate and adapt agronomic technologies that aim to increase productivity, reduce risk, and protect the environment for a given biophysical and socio-economic context. To date, these efforts lack a generic and robust spatial framework for ex-ante assessment that: (i) provides strategic insight to guide decisions about the number and location of testing sites, (ii) define the target domain for scaling-out a given technology or technology package, and (iii) estimate potential impact from widespread adoption of the technology(ies) being evaluated. In this study, we developed a data-rich spatial framework to guide agricultural research and development (AR&D) prioritization and to perform ex-ante impact assessment. The framework uses “technology extrapolation domains”, which delineate regions with similar climate and soil type combined with other biophysical and socio-economic factors that influence technology adoption. We provide proof of concept for the framework using a maize agronomy project in three sub-Saharan Africa countries (Ethiopia, Nigeria, and Tanzania) as a case study. We used maize area and rural population coverage as indicators to estimate potential project impact in each country. The project conducted 496 nutrient omission trials located at both on-farm and research station sites across these three countries. Reallocation of test sites towards domains with a larger proportion of national maize area could increase coverage of maize area by 79–134% and of rural population by 14–33% in Nigeria and Ethiopia. This study represents a first step in developing a generic, transparent, and scientifically robust framework to estimate ex-ante impact of AR&D programs that aim to increase food production and reduce poverty and hunger.
Publication - Maize-Seed-Area Mobile agronomic advice for smallholder maize farmers(CIMMYT, 2018) Andersson, J.A.; Craufurd, P.
Publication - Maize-Seed-Area Mahindi-Mbegu-Eneo kwa Kiswahili na kwa Kiingereza Mwongozo wa agronomia ya kilimo cha mahindi kwa kutumia simu janja kwa wakulima wadogo barani Afrika(CIMMYT, 2018) Andersson, J.A.; Craufurd, P.
Publication - Maize-Variety- Selector Identify the best adapted varieties for your location(CIMMYT, 2018) Craufurd, P.; Andersson, J.A.
Publication - Maize-Seed-Area Mobile agronomic advice for smallholder maize farmers(CIMMYT, 2018) Andersson, J.A.; Craufurd, P.Smallholder farmers often do not know accurately the area of the field they want to plant and, consequently, they don’t know how much seed to purchase. Most seed packets do not provide information on the numberof seeds in the pack. Yet, the size of seeds can vary from variety to variety— almost twofold. Maize-Seed-Area can calculate the amount of seedrequired for different varieties and help farmers buy the correct quantity.
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