Visualising the pattern of long-term genotype performance by leveraging a genomic prediction model

Vivi Arief Ian Delacy Thomas Payne Kaye Basford (2022, [Artículo])

Factor Analytic Genotype-By-Year Historical Data Relationship Matrix CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPES PLANT BREEDING SPRING WHEAT RESEARCH

On-farm assessment of yield and quality traits in durum wheat

Facundo Tabbita Iván Ortíz-Monasterios Francisco Javier Pinera-Chavez Maria Itria Ibba Carlos Guzman (2023, [Artículo])

BACKGROUND: Durum wheat is key source of calories and nutrients for many regions of the world. Demand for it is predicted to increase. Further efforts are therefore needed to develop new cultivars adapted to different future scenarios. Developing a novel cultivar takes, on average, 10 years and advanced lines are tested during the process, in general, under standardized conditions. Although evaluating candidate genotypes for commercial release under different on-farm conditions is a strategy that is strongly recommended, its application for durum wheat and particularly for quality traits has been limited. This study evaluated the grain yield and quality performance of eight different genotypes across five contrasting farmers’ fields over two seasons. Combining different analysis strategies, the most outstanding and stable genotypes were identified. RESULTS: The analyses revealed that some traits were mainly explained by the genotype effect (thousand kernel weight, flour sodium dodecyl sulfate sedimentation volume, and flour yellowness), others by the management practices (yield and grain protein content), and others (test weight) by the year effect. In general, yield showed the highest range of variation across genotypes, management practices, and years and test weight the narrowest range. Flour yellowness was the most stable trait across management conditions, while yield-related traits were the most unstable. We also determined the most representative and discriminative field conditions, which is a beneficial strategy when breeders are constrained in their ability to develop multi-environment experiments. CONCLUSIONS: We concluded that assessing genotypes in different farming systems is a valid and complementary strategy for on-station trials for determining the performance of future commercial cultivars in heterogeneous environments to improve the breeding process and resources.

Wheat Quality GGE Analysis Flour Yellowness CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FLOURS WHEAT QUALITY YIELDS FIELD EXPERIMENTATION

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Impact of adoption of heat-stress tolerant maize hybrid on yield and profitability: evidence from Terai region of Nepal

Atul Kulkarni Keshab Babu Koirala Pervez Zaidi (2023, [Artículo])

Inverse Probability Weighted Regression Heat Tolerant Maize Hybrid Partial Budget CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HEAT STRESS HEAT TOLERANCE MAIZE HYBRIDS BUDGETS YIELDS

Gene editing to accelerate crop breeding

Kanwarpal Dhugga (2022, [Artículo])

Accelerated Breeding Grain Biofortification Maize Lethal Necrosis Rust Resistance Site-Directed Nuclease Scenarios CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING BACKCROSSING DISEASE RESISTANCE GENE EDITING GRAIN BIOFORTIFICATION RUSTS

Balancing quality with quantity: a case study of UK bread wheat

Nick Fradgley Keith Gardner Stéphanie M. Swarbreck Alison Bentley (2023, [Artículo])

Grain Protein Content Environmental Sustainability End-Use Quality Modern Bread Baking Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN PROTEIN CONTENT HISTORY QUALITY WHEAT YIELDS

Nitrogen deficiency tolerance and responsiveness of durum wheat genotypes in Ethiopia

Tesfaye Geleta Aga Kebebew Assefa Bekele Abeyo (2022, [Artículo])

Low-Nitrogen Tolerance Yield Reduction Tolerant Genotypes Parental Donors CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN HARD WHEAT GENOTYPES

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

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY

Associations between endogenous spike cytokinins and grain-number traits in spring wheat genotypes

Gemma Molero Carolina Rivera-Amado Matthew Paul Reynolds John Foulkes (2024, [Artículo])

Spike Cytokinins Grain Number Fruiting Efficiency Wheat Breeding CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SPIKES CYTOKININS GRAIN FRUITING HARVEST INDEX WHEAT PLANT BREEDING