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34 results, page 1 of 4

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

Zhenhai  Li xiuliang jin Gerald Blasch James Taylor (2024)

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

Gender, rainfall endowment, and farmers’ heterogeneity in wheat trait preferences in Ethiopia

Hom Nath Gartaula Moti Jaleta (2024)

Wheat is a vital cereal crop for smallholders in Ethiopia. Despite over fifty years of research on wheat varietal development, consideration of gendered trait preferences in developing target product profiles for wheat breeding is limited. To address this gap, our study used sex-disaggregated survey data and historical rainfall trends from the major wheat-growing regions in Ethiopia. The findings indicated heterogeneity in trait preferences based on gender and rainfall endowment. Men respondents tended to prefer wheat traits with high straw yield and disease-resistance potential, while women showed a greater appreciation for wheat traits related to good taste and cooking quality. Farmers in high rainfall areas seemed to prioritize high straw yield and disease resistance traits, while those in low rainfall areas valued good adaptation traits more highly. Most of the correlation coefficients among the preferred traits were positive, indicating that farmers seek wheat varieties with traits that serve multiple purposes. Understanding men's and women's preferences and incorporating them in breeding and seed systems could contribute to the development of more targeted and effective wheat varieties that meet the diverse needs of men and women farmers in Ethiopia.

Article

Trait Preferences Multivariate Probit Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT AGRONOMIC CHARACTERS GENDER RAINFALL PROBIT ANALYSIS