AIMC Topic: Triticum

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Virtual screening of salty peptides from enzymatic and fermented products of wheat gluten and its molecular mechanism of interaction with TMC4 receptor.

Food chemistry
The health risks associated with excessive sodium intake have prompted an exploration of natural salt substitutes. This study was oriented to explore the salty peptides from enzymatic and fermented products of wheat gluten (WG) with different degrees...

Predicting crop disease severity using real time weather variability through machine learning algorithms.

Scientific reports
Integrating disease severity with real-time meteorological variables and advanced machine learning techniques has provided valuable predictive insights for assessing disease severity in wheat. This study emphasizes the potential of machine learning m...

Haplotype stacking to improve stability of stripe rust resistance in wheat.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Genotype-by-environment interaction analysis and haplotype-level characterisation provide novel insights into the stability of stripe rust resistance. Breeding selection strategies are proposed to achieve rapid and stable genetic gains across environ...

Predicting wheat yield using deep learning and multi-source environmental data.

Scientific reports
Accurate forecasting of crop yields is essential for ensuring food security and promoting sustainable agricultural practices. Winter wheat, a key staple crop in Pakistan, faces challenges in yield prediction because of the complex interactions among ...

Efficient wheat variety identification using Raman hyperspectral imaging in combination with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat (Triticum aestivum L.) is recognized as a globally important staple crop, with its varietal differences influencing food processing, nutritional value, and agricultural productivity. Traditional identification methods are often considered ineff...

Modeling impacts of climate-induced yield variability and adaptations on wheat and maize in a sub-tropical monsoon climate - using fuzzy logic.

Scientific reports
Climate change is causing more frequent and extraordinary extreme weather events that are already negatively affecting crop production. There is a need for improved climate risk assessment by developing smart adaptation strategies for sustainable fut...

AI-Accelerated Identification of Novel Antimicrobial Peptides for Inhibiting .

Journal of agricultural and food chemistry
Fusarium head blight caused by threatens global wheat production, causing substantial yield reduction and mycotoxin accumulation. This study harnessed machine learning to accelerate the discovery of antifungal peptides targeting this phytopathogen. ...

Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms.

Scientific reports
Wheat lodging is a recurrent phenomenon that significantly affects grain yield and impedes the harvesting efficiency. Therefore, the precise and rapid assessment of wheat lodging is crucial in minimizing its impact on grain yield and quality. Recentl...

Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.

Scientific reports
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...

Predicting land suitability for wheat and barley crops using machine learning techniques.

Scientific reports
Ensuring food security to meet the demands of a growing population remains a key challenge, especially for developing countries like Ethiopia. There are various policies and strategies designed by the government and stakeholders to confront the chall...