Leveraging multi-omics and machine learning approaches in malting barley research: From farm cultivation to the final products

Current Plant Biology, Journal Year: 2024, Volume and Issue: 39, P. 100362 - 100362

Published: June 22, 2024

This study focuses on the potential of multi-omics and machine learning approaches in improving our understanding malting processes cultivation systems barley. The omics approach has been used to explore biomarkers associated with desired sensory characteristics barley, enabling applications specific treatments modify diastatic power, enzyme activity, color, aroma compounds. Moreover, integration barley researches significantly enhanced knowledge physiology, cultivation, processing for more efficient sustainable production industry. cutting-edge vision high-throughput phenotyping technologies additionally revolutionize assessment physical biochemical traits In addition, harnessing integrative predict consumer acceptability, assess physicochemical colorimetric properties malt extracts discussed. Current survey showed that ML-driven predictive maintenance is revolutionizing industry by not only enhancing equipment performance but also minimizing operational costs reducing unplanned downtime. promises advancements opens avenues future

Language: Английский

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Advantages and limitations of using near infrared spectroscopy in plant phenomics applications

Computers and Electronics in Agriculture, Journal Year: 2023, Volume and Issue: 212, P. 108078 - 108078

Published: July 30, 2023

Language: Английский

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Unlocking the nutritional potential of chickpea: strategies for biofortification and enhanced multinutrient quality

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: June 7, 2024

Chickpea ( Cicer arietinum L.) is a vital grain legume, offering an excellent balance of protein, carbohydrates, fats, fiber, essential micronutrients, and vitamins that can contribute to addressing the global population’s increasing food nutritional demands. protein offers balanced source amino acids with high bioavailability. Moreover, due its nutrients affordable price, chickpea alternative animal formidable tool for combating hidden hunger malnutrition, particularly prevalent in low-income countries. This review examines chickpea’s profile, encompassing acids, fatty vitamins, antioxidant properties, bioactive compounds significance health pharmaceutical domains. Emphasis placed on incorporating chickpeas into diets their myriad benefits richness, aimed at enhancing human micronutrient nutrition. We discuss advances plant breeding genomics have facilitated discovery diverse genotypes key genomic variants/regions/quantitative trait loci contributing enhanced macro- contents other quality parameters. Furthermore, we explore potential innovative tools such as CRISPR/Cas9 profile. Envisioning nutritionally smart crop, endeavor safeguard security, combat promote dietary diversity within sustainable agrifood systems.

Language: Английский

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Advances in Plant Phenotyping for Climate-Resilient Oilseeds Breeding

Published: Jan. 1, 2025

Language: Английский

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Integrating phenomic selection using single-kernel near-infrared spectroscopy and genomic selection for corn breeding improvement

Theoretical and Applied Genetics, Journal Year: 2025, Volume and Issue: 138(3)

Published: Feb. 26, 2025

Phenomic selection using intact seeds is a promising tool to improve gain and complement genomic in corn breeding. Models that combine phenomic data maximize the predictive ability. (PS) cost-effective method proposed for predicting complex traits enhancing genetic breeding programs. The statistical procedures are similar those utilized (GS) models, but molecular markers replaced with data, such as near-infrared spectroscopy (NIRS). However, use of NIRS applied PS typically destructive sampling or collected after establishment experiments field. Here, we explored application nondestructive, single-kernel sweet program, focusing on future, unobserved field-based economic importance, including ear vegetative traits. Three models were employed diversity panel: best linear unbiased prediction which used relationship matrices based SNP respectively, combined model. evaluated varying numbers SNPs. Additionally, model trained panel was select doubled haploid (DH) lines germination before planting, predictions validated observed data. findings indicate generated good ability (e.g., 0.46 plant height) distinguished between high low rates untested DH lines. Although GS generally outperformed PS, combining both information yielded highest ability, higher accuracies than when marker densities used. This study highlights NIRS's potential achieve where may not be feasible maintain/improve accuracy SNP-based while reducing genotyping costs.

Language: Английский

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Nondestructive Single Seed Scale Phenomic Platform: Chickpea Quality Traits Based on SKNIR Spectroscopy

Published: Jan. 1, 2025

Language: Английский

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Development of a NIRS-based prediction model for measurement of whole wheat flour arabinoxylan content to aid rapid germplasm screening

Journal of Cereal Science, Journal Year: 2025, Volume and Issue: unknown, P. 104173 - 104173

Published: April 1, 2025

Language: Английский

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Quantitative assessment of phytochemicals in chickpea beverages using NIR spectroscopy

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Journal Year: 2023, Volume and Issue: 307, P. 123623 - 123623

Published: Nov. 8, 2023

Language: Английский

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Major abiotic stresses on quality parameters in grain legumes: impacts and various strategies for improving quality traits

Environmental and Experimental Botany, Journal Year: 2024, Volume and Issue: unknown, P. 105978 - 105978

Published: Sept. 1, 2024

Language: Английский

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X-ray-μCT: nondestructively identifying hidden microphenotypes inside living crop seeds

Trends in Plant Science, Journal Year: 2023, Volume and Issue: 29(1), P. 99 - 100

Published: Nov. 15, 2023

Language: Английский

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