Repositorio Nacional

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.

Article

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

Association of specific expansins with growth in maize leaves is maintained under environmental, genetic, and developmental sources of variation

Francois Tardieu (2007)

Article

Environmental Stimuli Expansins CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CELLS CROPS GENETIC ENGINEERING PROTEINS TISSUE EPIDERMIS ZEA MAYS

Mapping crop and livestock value chain actors in Mbire and Murehwa districts in Zimbabwe

Hambulo Ngoma Moti Jaleta Frédéric Baudron (2023)

We conducted a preliminary value chain actors mapping for major crops grown and livestock kept by smallholder farmers in Mbire and Murehwa districts of Zimbabwe. Accordingly, in this report we mapped value chain actors for 11 crops and livestock commodities: namely, sorghum, cotton, sesame, maize, groundnut, sweet-potato, vegetables (tomato and onion), cattle, goats, poultry, and honey/beekeeping. Except sesame from Mbire, most of the crop and livestock commodities are channeled to the main markets in Harare and Marondera for Murehwa. Sesame is smuggled to Mozambique and the market is mainly dependent on middlemen. The Grain Market Board (GMB) is the major actor in sorghum and maize marketing in both districts. Groundnut is sold to both rural and urban consumers after processing it to peanut butter locally within the production zones. Goats and cattle are mostly supplied to the Harare market by middlemen collecting these livestock from village markets and moving door-to-door to buy enough quantity to transport to Harare. Honey production and marketing is still at its initial stage through the support of HELP from Germany and the Zimbabwe Apiculture Trust projects. Long dry season is a challenge in honey production. The Pfumvudza program supported by the Presidential free input scheme helped in introducing and scaling conservation agriculture practices in Zimbabwe. Though there is strong integration of crop-livestock systems at both districts, the level of manure use is gradually decreasing because farmers receive chemical fertilizer support from the Pfumvudza program and applying manure to crop fields is labor-intensive. The input supply system is more competitive in Murehwa district where there are quite several input suppliers in town. The possible interventions that favor agroecological transitions are: (1) honey processing plants and supply of beehives to potential areas, (2) encouraging manure use in crop production, possibly linking it to the basins preparation requirement to be eligible for the presidential input subsidy scheme, (3) support the organic vegetable production initiatives and explore market segments in Harare paying premium prices for certified organic products, (4) Expedite payment systems in sorghum and maize marketing with GMB, and (5) sesame production with agroecologically friendly agronomy and improve markets.

Working paper

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA VALUE CHAINS CROPS LIVESTOCK SMALLHOLDERS SUPPLY CHAINS

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)

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.

Article

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

KARC 2020 Experiment – The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia

Gerald Blasch (2023)

Conference object

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA REMOTE SENSING WHEAT CROPS DISEASES

Genomic prediction of hybrid crops accounting for non additive genetic effects

David González-Diéguez (2022)

Conference object

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION HYBRIDS MAIZE GENOMES GENETICS GENETIC VARIANCE CROPS