Climate smart bread wheat (Triticum aestivum L.) variety development for optimum moisture areas of Ethiopia

Bekele Abeyo Ayele Badebo Huluka (2023, [Artículo])

GGE Biplot AMMI Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT ENVIRONMENT GENOTYPES GRAIN YIELDS

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

Variation in grain zinc and iron concentrations, grain yield and associated traits of biofortified bread wheat genotypes in Nepal

Vinod Mishra arun joshi Ravi Singh Govindan Velu (2022, [Artículo])

Biofortified Wheat HarvestPlus Grain Yield Grain Iron Concentration Grain Zinc Concentration CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOFORTIFICATION WHEAT GRAIN YIELDS ZINC IRON

Identification of genetic loci for grain yield-related traits in the wheat population Zhongmai 578/Jimai 22

Jingyang Tong Ming Li xianchun xia Zhonghu He Yong Zhang (2023, [Artículo])

Grain Yield KASP Marker QTL Mapping SNP Chip CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN YIELDS QUANTITATIVE TRAIT LOCI MAPPING SINGLE NUCLEOTIDE POLYMORPHISMS WHEAT BREEDING

Editorial: Model organisms in plant science: Maize

Manje Gowda (2023, [Artículo])

Model Organism Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE PLANT SCIENCES RESEARCH CROP IMPROVEMENT PLANT PHYSIOLOGY PLANT BREEDING

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

Soil moisture content and maize grain yield under conventional and conservation agriculture practices - results of short term field tests in liselo, Namibia

Christian Thierfelder (2023, [Artículo])

This article focuses on the results from trials developed to monitor the short-term effects of conventionally tilled systems versus CA on soil quality and crop productivity under conditions of the major cropping systems in central, north-central and north-eastern regions of Namibia. Conventional tillage (CT), Minimum tillage (MT), Minimum tillage, mulch (MT-M), Minimum tillage, rotation (MT-R) and Minimum tillage, mulch and rotation (MT-MR) were the primary treatments tested. Significant differences (p≤0.000) among the treatments were observed in the 0-60 cm soil profiles where MT-M plots had the highest soil moisture content (39.8 mm, Standard Error of Mean 0.2815) over the study period. A significant difference (p=0.0206) in grain yield was observed in the second season with CT plots yielding the highest grain yield (3852.3 kg ha-1, standard error of mean 240.35). Results suggest that CA has the potential to increase water conservation and contribute to reduction of the risk of crop failure. Climate change driven degradation under conventional tillage necessitate alternative sustainable tillage methods. Conservation tillage methods and conservation agricultural practices that minimize soil disturbance while maintaining soil cover need to be adopted more locally as viable alternatives to conventional tillage.

Grain Yield Soil Moisture Content CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CONSERVATION AGRICULTURE CONVENTIONAL TILLAGE GRAIN YIELDS SOIL WATER CONTENT MAIZE

Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat

Jose Crossa Osval Antonio Montesinos-Lopez Morten Lillemo (2024, [Artículo])

Multispectral Imaging Grain Yield Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN YIELDS HIGH-THROUGHPUT PHENOTYPING SPRING WHEAT