MLN disease diagnostics, surveillance, MLN disease-free seed production, and MLN disease management

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASES DISEASE MANAGEMENT SEED PRODUCTION MAIZE NECROSIS YIELD LOSSES ECONOMIC IMPACT SURVEILLANCE SYSTEMS TRAINING

Appropriate surveillance and diagnostics tools in preventing the spread of Maize Lethal Necrosis (MNL) to Southern Africa

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE DISEASES SEED PRODUCTION MONITORING SYSTEMS TRAINING

Population and food in the early twenty-first century: meeting future food demand of an increasing population

Nurul Islam (1995, [Libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FOOD POLICIES FOOD PRODUCTION FOOD SUPPLY FORECASTING

Remote sensing of quality traits in cereal and arable production systems: A review

Zhenhai  Li xiuliang jin Gerald Blasch James Taylor (2024, [Artículo])

Cereal is an essential source of calories and protein for the global population. Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers, grading harvest and categorised storage for enterprises, future trading prices, and policy planning. The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits. Many studies have also proposed models and methods for predicting such traits based on multi-platform remote sensing data. In this paper, the key quality traits that are of interest to producers and consumers are introduced. The literature related to grain quality prediction was analyzed in detail, and a review was conducted on remote sensing platforms, commonly used methods, potential gaps, and future trends in crop quality prediction. This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.

Quality Traits Grain Protein CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA REMOTE SENSING QUALITY GRAIN PROTEINS CEREALS PRODUCTION SYSTEMS

Digital artifacts reveal development and diffusion of climate research

Bia Carneiro Tek Sapkota (2022, [Artículo])

Accessible Knowledge Impact of Outputs Traditional Bibliometric Analyses Hyperlink Analysis CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE DIFFUSION MAIZE MINING ORGANIZATION SOCIAL MEDIA SOCIAL NETWORK ANALYSIS WHEAT TEXT MINING

Point placement of late vegetative stage nitrogen splits increase the productivity, N-use efficiency and profitability of tropical maize under decade long conservation agriculture

Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])

Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT

Expanding the WOFOST crop model to explore options for sustainable nitrogen management: A study for winter wheat in the Netherlands

João Vasco Silva Pytrik Reidsma (2024, [Artículo])

Nitrogen (N) management is essential to ensure crop growth and to balance production, economic, and environmental objectives from farm to regional levels. This study aimed to extend the WOFOST crop model with N limited production and use the model to explore options for sustainable N management for winter wheat in the Netherlands. The extensions consisted of the simulation of crop and soil N processes, stress responses to N deficiencies, and the maximum gross CO2 assimilation rate being computed from the leaf N concentration. A new soil N module, abbreviated as SNOMIN (Soil Nitrogen for Organic and Mineral Nitrogen module) was developed. The model was calibrated and evaluated against field data. The model reproduced the measured grain dry matter in all treatments in both the calibration and evaluation data sets with a RMSE of 1.2 Mg ha−1 and the measured aboveground N uptake with a RMSE of 39 kg N ha−1. Subsequently, the model was applied in a scenario analysis exploring different pathways for sustainable N use on farmers' wheat fields in the Netherlands. Farmers' reported yield and N fertilization management practices were obtained for 141 fields in Flevoland between 2015 and 2017, representing the baseline. Actual N input and N output (amount of N in grains at harvest) were estimated for each field from these data. Water and N-limited yields and N outputs were simulated for these fields to estimate the maximum attainable yield and N output under the reported N management. The investigated scenarios included (1) closing efficiency yield gaps, (2) adjusting N input to the minimum level possible without incurring yield losses, and (3) achieving 90% of the simulated water-limited yield. Scenarios 2 and 3 were devised to allow for soil N mining (2a and 3a) and to not allow for soil N mining (2b and 3b). The results of the scenario analysis show that the largest N surplus reductions without soil N mining, relative to the baseline, can be obtained in scenario 1, with an average of 75%. Accepting negative N surpluses (while maintaining yield) would allow maximum N input reductions of 84 kg N ha−1 (39%) on average (scenario 2a). However, the adjustment in N input for these pathways, and the resulting N surplus, varied strongly across fields, with some fields requiring greater N input than used by farmers.

Crop Growth Models WOFOST CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS NITROGEN-USE EFFICIENCY WINTER WHEAT SOIL WATER

How diverse are farming systems on the Eastern Gangetic Plains of South Asia? A multi-metric and multi-country assessment

Brendan Brown Pragya Timsina Emma Karki (2023, [Artículo])

While crop diversification has many benefits and is a stated government objective across the Eastern Gangetic Plains (EGP) of South Asia, the complexity of assessment has led to a rather limited understanding on the progress towards, and status of, smallholder crop diversification. Most studies focus on specific commodities or report as part of a singular index, use outdated secondary data, or implement highly localized studies, leading to broad generalisations and a lack of regional comparison. We collected representative primary data with more than 5000 households in 55 communities in Eastern Nepal, West Bengal (India) and Northwest Bangladesh to explore seasonally based diversification experiences and applied novel metrics to understand the nuanced status of farm diversification. While 66 crops were commercially grown across the region, only five crops and three crop families were widely grown (Poaceae, Malvaceae, and Brassicaceae). Non-cereal diversification across the region was limited (1.5 crops per household), though regional differentiation were evident particularly relating to livestock and off-farm activities, highlighting the importance of cross border studies. In terms of farmer's largest commercial plots, 20% of systems contained only rice, and 57% contained only rice/wheat/maize, with substantial regional diversity present. This raises concerns regarding the extent of commercially oriented high value and non-cereal diversification, alongside opportunities for diversification in the under-diversified pre-monsoon and monsoon seasons. Future promotional efforts may need to focus particularly on legumes to ensure the future sustainability and viability of farming systems.

Agricultural Production Systems Farming Systems Change CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRODUCTION CROPPING SYSTEMS DIVERSIFICATION FARMING SYSTEMS SUSTAINABLE INTENSIFICATION

Planting rice at monsoon onset could mitigate the impact of temperature stress on rice–wheat systems of Bihar, India

Carlo Montes Anton Urfels Eunjin Han Balwinder-Singh (2023, [Artículo])

Rainy Season TIMESAT APSIM Agricultural Production Systems Simulator Climate Adaptation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RICE WHEAT MONSOONS WET SEASON CROP MODELLING CLIMATE CHANGE ADAPTATION

The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia

Gerald Blasch David Hodson Francelino Rodrigues (2023, [Artículo])

Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.

Very High Resolution Imagery Disease Detection Methods Early Growth Stages CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA UNMANNED AERIAL VEHICLES STEM RUST PHENOTYPING HIGH-THROUGHPUT PHENOTYPING WHEAT