AIMC Topic: Zea mays

Clear Filters Showing 1 to 10 of 132 articles

Enhanced residual-attention deep neural network for disease classification in maize leaf images.

Scientific reports Aug 12, 2025
Disease classification in maize plant is necessary for immediate treatment to enhance agricultural production and assure global food sustainability. Recent advancements in deep learning, specifically convolutional neural networks, have shown outstand...
Image Processing, Computer-Assisted Plant Leaves Zea mays Reproducibility of Results Deep Learning Plant Diseases Neural Networks, Computer
View on PubMed DOI

A machine learning approach for estimating forage maize yield and quality in NW Spain.

PloS one Aug 12, 2025
Crop models simulate crop growth and development according to different climatic, soil and crop management conditions. The CSM-CERES-Maize model (DSSAT) was adapted to simulate forage maize yields by calibrating the genetic parameters of six cultivar...
Zea mays Crops, Agricultural Spain Machine Learning
View on PubMed DOI

YOLO-LeafNet: a robust deep learning framework for multispecies plant disease detection with data augmentation.

Scientific reports Aug 5, 2025
Plant diseases significantly harm crops, resulting in significant economic losses across the globe. In order to reduce the harm that these diseases produce, plant diseases must be diagnosed accurately and timely manner. In this work, a YOLO-LeafNet a...
Zea mays Image Processing, Computer-Assisted Capsicum Vitis Plant Leaves Algorithms Plant Diseases Deep Learning
View on PubMed DOI

Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China.

Scientific reports Jul 31, 2025
As a typical pest affecting corn yield and safety, corn borer causes serious economic losses worldwide. Climate warming has intensified the occurrence of pest outbreaks in recent years, but the associated risk has not been precisely assessed or under...
Machine Learning Algorithms Animals Cluster Analysis Zea mays Moths Risk Assessment China
View on PubMed DOI

Evaluating crop yield prediction models in illinois using aquacrop, semi-physical model and artificial neural networks.

Scientific reports Jul 28, 2025
Crop yield is important for agricultural productivity and the country's economy. While crop yield estimation is an essential aspect of modern agriculture, it continues to be one of the most challenging tasks to manage effectively. Corn and soybean ar...
Glycine max Illinois Neural Networks, Computer Agriculture Zea mays Crops, Agricultural Models, Theoretical
View on PubMed DOI

A novel framework GRCornShot for corn disease detection using few shot learning with prototypical network.

Scientific reports Jul 21, 2025
Precision and timeliness in the detection of plant diseases are important to limit crop losses and maintain global food security. Much work has been performed to detect plant diseases using deep learning methods. However, deep learning techniques dem...
Zea mays Plant Diseases Algorithms Deep Learning Neural Networks, Computer
View on PubMed DOI

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

Scientific reports Jul 16, 2025
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...
Temperature Models, Theoretical Crops, Agricultural Bangladesh Rain Adaptation, Physiological Triticum Seasons Fuzzy Logic Climate Change Zea mays
View on PubMed DOI

Enhancing corn industry sustainability through deep learning hybrid models for price volatility forecasting.

PloS one Jun 9, 2025
The fluctuations in corn prices not only increase uncertainty in the market but also affect farmers' planting decisions and income stability, while also impeding crucial investments in sustainable agricultural practices. Collectively, these factors j...
Deep Learning Agriculture Zea mays Forecasting Models, Economic Commerce
View on PubMed DOI

Enabling malic acid production from corn-stover hydrolysate in Lipomyces starkeyi via metabolic engineering and bioprocess optimization.

Microbial cell factories May 21, 2025
BACKGROUND: Lipomyces starkeyi is an oleaginous yeast with a native metabolism well-suited for production of lipids and biofuels from complex lignocellulosic and waste feedstocks. Recent advances in genetic engineering tools have facilitated the deve...
Lipomyces Zea mays Malate Dehydrogenase Bioreactors Hydrolysis Pyruvate Carboxylase Metabolic Engineering Malates Fermentation Aspergillus oryzae
View on PubMed DOI

Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.

BMC genomics May 1, 2025
Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's ...
Metabolome Quantitative Trait Loci Plant Leaves Genome, Plant Genome-Wide Association Study Phenotype Zea mays Gene Expression Regulation, Plant Transcriptome Genomics
View on PubMed DOI
Popular Topics
Recent Journals