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1. Excellence in Agronomy 2030: A new CGIAR-wide initiative to deliver agronomy solutions at scaleRequired increases in crop production and productivity in sub-Saharan Africa (SSA) will not happen without the increased use of appropriate agronomic practices. While several thousand new varieties of nearly all key crops have been produced in the past decade, recent increases in yields in specific countries have only happened when such varieties received the right agro-inputs and management. That said, agronomy is often highlighted as an area that has not delivered impact at scale in SSA, or... B. Vanlauwe, T. Amede, F. Baudron, P. Chivenge, M. Devare, K. Saito, J. Kihara, V. Nangia, P. Pypers, K. Shepherd, E. Vandamme |
2. Spectral assessment of chickpea morpho-physiological traits from space, air and groundChickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The current... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg |
3. Development of Lodging Direction Determination System Using Image ProcessingIn this study, image processing system was developed for application on rice plants to determine lodging condition, which was contributing factor to declining harvester efficiency by using combine harvester. Therefore, We developed a system for determination of the lodging direction by algorithm based on convolutional neural network (CNN). As for deep learning framework, Pytorch1.1.0 were used to train and test the judging direction. GoogLeNet was used as a pre-trained CNN model. Lodging... E. Morimoto, Y. Arai, K. Nonami, T. Ito |
4. A geostatistical approach to define a soil fertility index based on the main soil macronutrientsSoil fertility is greatly affected by main soil macronutrients such as nitrogen (N), phosphorus (P), and potassium (K). These macronutrients can be used to define a synthetic fertility index to support soil fertilization. The study was aimed to propose a geostatistical approach to define a synthetic fertility index based on factorial cokriging. It consists in quantifying and reducing the spatial variability of multivariate data to only a few factors, related to different spatial scales. Such factors... H. Aboelkhier, A. Nasrallah, S. Shaddad, G. Buttafuoco |
5. DIGITAL MAPPING OF EXCHANGEABLE CATIONS IN SOILS OF SOUTHWESTERN NIGERIASoil acidity and low exchangeable cation are the major soil fertility challenges resulting in low crop productivity in Southwest Nigeria. Digital soil mapping is an effective way to achieve precision agriculture. However, most of the research work on soil exchangeable cations as soil information was not geo-referenced, The study created geo-database and developed a digitized map of soil exchangeable cations Indicating the spatial distribution in soils of southwestern Nigeria. Secondary data... O.E. Awosiyan, I.K. Mary, F.A. Adesina |
6. Climate Smart Agriculture: Constraints, Challenges and Opportunities to Promote the System in EthiopiaAgriculture is vital to the economy of Ethiopia and its development has significant implications for food security and poverty reduction. An increase in agricultural production over the past decades has been due to land area expansion, with a modest change in production techniques and improvement in yields. Yet, the substantial reliance of the sector on rain-fed systems has made it particularly vulnerable to variability in rainfall and temperature and climate change. Climate change may decrease... G. Agegnehu, T. Amede |
7. Modelling Fertigation and Micro-Climate Parameters for Greenhouse Tomato (Solanum Lycopersicum L.)Amidst the hiking price of fertilizer and projected water scarcity across the world, it is imperative to explore the interaction between fertilizer, irrigation and genotype notwithstanding the micro-climate parameters so as to maximize yield while protecting the environment. The Decision Support System for Agrotechnology Transfer (DSSAT) is a model which employs all these input factors to help predict yield and thereby make an informed decision. The study sort to calibrate and validate the... Y.K. Agbemabiese, P. Abubakari, P.K. Dzomeku, I. Shaibu |
8. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear RegressionTraditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud |