AIMC Topic: Plant Breeding

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Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery.

Sensors (Basel, Switzerland) May 12, 2022
The total boll count from a plant is one of the most important phenotypic traits for cotton breeding and is also an important factor for growers to estimate the final yield. With the recent advances in deep learning, many supervised learning approach...
Deep Learning Gossypium Plant Breeding
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Cereal grain 3D point cloud analysis method for shape extraction and filled/unfilled grain identification based on structured light imaging.

Scientific reports Feb 24, 2022
Cereals are the main food for mankind. The grain shape extraction and filled/unfilled grain recognition are meaningful for crop breeding and genetic analysis. The conventional measuring method is mainly manual, which is inefficient, labor-intensive a...
Image Processing, Computer-Assisted Edible Grain Machine Learning Cloud Computing Plant Breeding
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Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.

PloS one Nov 29, 2021
The present study evaluated the importance of auxiliary traits of a principal trait based on phenotypic information and previously known genetic structure using computational intelligence and machine learning to develop predictive tools for plant bre...
Genotype Artificial Intelligence Phenotype Plant Breeding Quantitative Trait Loci Computer Simulation Genetic Linkage Machine Learning
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Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology Nov 10, 2021
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...
Artificial Intelligence Computational Biology Nutrients Horticulture Climate Change Vegetables Plant Breeding Crops, Agricultural Trees Flowers Interdisciplinary Research Fruit Bioengineering
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Towards Automated Analysis of Grain Spikes in Greenhouse Images Using Neural Network Approaches: A Comparative Investigation of Six Methods.

Sensors (Basel, Switzerland) Nov 9, 2021
Automated analysis of small and optically variable plant organs, such as grain spikes, is highly demanded in quantitative plant science and breeding. Previous works primarily focused on the detection of prominently visible spikes emerging on the top ...
Image Processing, Computer-Assisted Plant Leaves Neural Networks, Computer Edible Grain Plant Breeding
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Advances in for Abiotic Stress Resilience: From 'Omics' to Artificial Intelligence.

International journal of molecular sciences Sep 29, 2021
Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely ...
Artificial Intelligence Plant Breeding Fabaceae Stress, Physiological Genomics Crops, Agricultural Quantitative Trait Loci
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LightGBM: accelerated genomically designed crop breeding through ensemble learning.

Genome biology Sep 20, 2021
LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performa...
Plant Breeding Zea mays Crops, Agricultural Software Machine Learning Genomics Genome-Wide Association Study Polymorphism, Single Nucleotide Decision Trees
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Multitrait machine- and deep-learning models for genomic selection using spectral information in a wheat breeding program.

The plant genome Sep 5, 2021
Prediction of breeding values is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine- and deep-learning algorithms applied to complex traits in plants can improve prediction accuracies. Beca...
Plant Breeding Deep Learning Genomics Triticum Genome, Plant Bayes Theorem Artificial Intelligence
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Crop yield prediction integrating genotype and weather variables using deep learning.

PloS one Jun 17, 2021
Accurate prediction of crop yield supported by scientific and domain-relevant insights, is useful to improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop producti...
Genotype Weather Neural Networks, Computer Deep Learning Plant Breeding Crops, Agricultural Glycine max
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A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits.

Plant communications Jan 29, 2021
Lodging is a common problem in rice, reducing its yield and mechanical harvesting efficiency. Rice architecture is a key aspect of its domestication and a major factor that limits its high productivity. The ideal rice culm structure, including major_...
Plant Breeding Disease Resistance X-Ray Microtomography Phenotype Oryza Plant Diseases Deep Learning
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