Climate change, rising global food demand, and shrinking resources require transformative innovations in crop breeding. This review outlines recent advances in new breeding technologies (NBTs), including molecular markers, genome-wide association stu...
Over the last couple of decades, tremendous progress has been made in legume genomics. Genomics information generated for legume crops is being explored through molecular breeding and transgenic approaches. However, the gap between knowledge generati...
The development of accurate and efficient plant disease classification systems is vital for addressing the challenges of climate change and the growing global demand for food. This study presents [Formula: see text]PlantNet, a novel lightweight multi...
Recent advancements in precision agriculture have introduced innovative approaches to addressing plant stress, a critical factor influencing crop productivity and agricultural sustainability. Accurate, real-time prediction of plant stress has become ...
The prevalence of diseases in wheat crops poses a significant threat to global food security, as it reduces yield and quality. Addressing these challenges is critical for sustainable agriculture. This study proposes and evaluates a hybrid deep learni...
Agricultural productivity remains seriously threatened by the attacks of plant diseases, even though it is the bedrock of global food security. These diseases, if ignored, can lead to massive crop losses and economic setbacks. Therefore, the developm...
Crop leaf disease detection plays a crucial role in ensuring healthy crop growth and improving food security. Disease features are often small and have blurry edges, while background interference is strong, making precise detection a significant chal...
Agricultural production is still quite susceptible to plant diseases, despite the fact that it is essential to both economic growth and food security. Yellow rust can lower wheat yields by 20-30%, red rust by 5-10%, and anthracnose by up to 60% in cr...
The integration of advanced tools and techniques has significantly boosted agricultural productivity. Wheat crops, which are vital for global food security, are often susceptible to various bacterial and viral diseases, considerably impacting both yi...
Genomic Prediction (GP) uses dense whole-genome marker sets from lines of a crop to predict agronomic traits for untested genotypes. In recent years, deep learning (DL) approaches for genomic prediction have demonstrated state-of-the-art results. How...
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