AIMC Topic: Zea mays

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Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN.

PloS one Jan 1, 2025
Leaf diseases in Zea mays crops have a significant impact on both the calibre and volume of maize yield, eventually impacting the market. Prior detection of the intensity of an infection would enable the efficient allocation of treatment resources an...
Zea mays Neural Networks, Computer Plant Leaves Crops, Agricultural Plant Diseases
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Identification of biomarker genes from multiple studies for abiotic stress in maize through machine learning.

Journal of biosciences Jan 1, 2024
Abiotic stresses are major limiting factors for maize growth. Therefore, exploration of the mechanisms underlying the response to abiotic stress in maize is of great interest. Toward this end, we performed integration of the feature selection method ...
Biomarkers Bayes Theorem Zea mays Machine Learning Stress, Physiological
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[Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China].

Ying yong sheng tai xue bao = The journal of applied ecology Dec 1, 2023
Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong...
Zea mays China Triticum Remote Sensing Technology Edible Grain
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Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability.

Journal of experimental botany Sep 3, 2022
Despite efforts to collect genomics and phenomics ('omics') and environmental data, spatiotemporal availability and access to digital resources still limit our ability to predict plants' response to changes in climate. Our goal is to quantify the imp...
Deep Learning Zea mays Climate Change Agriculture Climate
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Deep learning-based high-throughput phenotyping accelerates gene discovery for stomatal traits.

Plant physiology Nov 3, 2021
Plant Stomata Water Zea mays Quantitative Trait Loci Droughts Sorghum Phenotype Deep Learning Genome-Wide Association Study Neural Networks, Computer Algorithms
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Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping.

Plant physiology Nov 3, 2021
Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping ep...
Phenotype Zea mays Quantitative Trait Loci Machine Learning Botany Plant Stomata Genes, Plant Chromosome Mapping
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Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms.

Plant physiology Nov 3, 2021
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but ...
Unmanned Aerial Devices Plant Leaves Zea mays Crops, Agricultural Farms China Machine Learning
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Effect of postweaning heifer development system on average daily gain, pregnancy rates, and subsequent feed efficiency as a pregnant heifer.

Journal of animal science Dec 1, 2017
A 3-yr study utilized 300 Angus-based, spring-born heifers to evaluate postweaning heifer development systems on gain, reproductive performance, and feed efficiency as a pregnant heifer. Heifers were blocked by BW and randomly assigned to graze corn ...
Acclimatization Maternal Nutritional Physiological Phenomena Zea mays Eating Body Weight Cattle Pregnancy Rate Reproduction Pregnancy Random Allocation Female Breeding Animal Feed Seasons Diet Animals Animal Husbandry
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Use of in vitro dry matter digestibility and gas production to predict apparent total tract digestibility of total dietary fiber for growing pigs.

Journal of animal science Dec 1, 2017
In vitro DM disappearance (IVDMD) and gas production methods have been developed and used to measure in vivo nutrient digestibility of feed ingredients, but further validation is needed for ingredients containing high concentrations of insoluble fibe...
Zea mays Triticum Animal Feed Fermentation Dietary Fiber Animals Diet Swine Glycine max Gastrointestinal Tract Digestion
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Discrimination of Maize Haploid Seeds from Hybrid Seeds Using Vis Spectroscopy and Support Vector Machine Method.

Guang pu xue yu guang pu fen xi = Guang pu Nov 1, 2015
Doubled haploid (DH) lines are routinely applied in the hybrid maize breeding programs of many institutes and companies for their advantages of complete homozygosity and short breeding cycle length. A key issue in this approach is an efficient screen...
Support Vector Machine Color Breeding Principal Component Analysis Zea mays Seeds Haploidy Spectrum Analysis
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