AIMC Topic: Seeds

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Predicting the quality of soybean seeds stored in different environments and packaging using machine learning.

Scientific reports May 25, 2022
The monitoring and evaluating the physical and physiological quality of seeds throughout storage requires technical and financial resources and is subject to sampling and laboratory errors. Therefore, machine learning (ML) techniques could help optim...
Humans Algorithms Seeds Glycine max Artificial Intelligence Machine Learning
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Screening and functional prediction of differentially expressed genes in walnut endocarp during hardening period based on deep neural network under agricultural internet of things.

PloS one Feb 24, 2022
The deep neural network is used to establish a neural network model to solve the problems of low accuracy and poor accuracy of traditional algorithms in screening differentially expressed genes and function prediction during the walnut endocarp harde...
Juglans Neural Networks, Computer Algorithms Gene Expression Regulation, Plant Lignin Seeds Agriculture Internet of Things Fruit
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Robust seed germination prediction using deep learning and RGB image data.

Scientific reports Nov 11, 2021
Achieving seed germination quality standards poses a real challenge to seed companies as they are compelled to abide by strict certification rules, while having only partial seed separation solutions at their disposal. This discrepancy results with w...
Deep Learning Seeds Vegetables Crops, Agricultural Germination Models, Biological
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Physical and chemical properties of edamame during bean development and application of spectroscopy-based machine learning methods to predict optimal harvest time.

Food chemistry Aug 8, 2021
This study aims to investigate the changes in physical and chemical properties of edamame during bean development and apply a spectroscopy-based machine learning (ML) technique to determine optimal harvest time. The edamame harvested at R5 (beginning...
Machine Learning Seeds Glycine max Spectrum Analysis Sugars
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Digital image processing technology under backpropagation neural network and K-Means Clustering algorithm on nitrogen utilization rate of Chinese cabbages.

PloS one Mar 31, 2021
The purposes are to monitor the nitrogen utilization efficiency of crops and intelligently evaluate the absorption of nutrients by crops during the production process. The research object is Chinese cabbage. The Chinese cabbage population with differ...
Nitrogen Brassica Algorithms Regression Analysis Image Processing, Computer-Assisted Agriculture Plant Leaves Neural Networks, Computer Seeds
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Hyperspectral prediction of sugarbeet seed germination based on gauss kernel SVM.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 14, 2021
How to quickly and accurately select sugarbeet seeds with reliable germination is very important to sugarbeet planting. In this study, the hyperspectral images of 3072 sugarbeet seeds of the same variety were collected, and were successively processe...
Seeds Germination Image Processing, Computer-Assisted Support Vector Machine Algorithms
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Nondestructive Classification of Soybean Seed Varieties by Hyperspectral Imaging and Ensemble Machine Learning Algorithms.

Sensors (Basel, Switzerland) Dec 7, 2020
During the processing and planting of soybeans, it is greatly significant that a reliable, rapid, and accurate technique is used to detect soybean varieties. Traditional chemical analysis methods of soybean variety sampling (e.g., mass spectrometry a...
Hyperspectral Imaging Glycine max Algorithms Support Vector Machine Seeds Machine Learning
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Classification of Watermelon Seeds Using Morphological Patterns of X-ray Imaging: A Comparison of Conventional Machine Learning and Deep Learning.

Sensors (Basel, Switzerland) Nov 26, 2020
In this study, conventional machine learning and deep leaning approaches were evaluated using X-ray imaging techniques for investigating the internal parameters (endosperm and air space) of three cultivars of watermelon seed. In the conventional mach...
Machine Learning Algorithms Seeds Citrullus Deep Learning X-Rays
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Interactive machine learning for soybean seed and seedling quality classification.

Scientific reports Jul 9, 2020
New computer vision solutions combined with artificial intelligence algorithms can help recognize patterns in biological images, reducing subjectivity and optimizing the analysis process. The aim of this study was to propose an approach based on inte...
Glycine max Seedlings Reproducibility of Results Software False Positive Reactions Artificial Intelligence Seeds Image Processing, Computer-Assisted Principal Component Analysis Machine Learning Germination Algorithms
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Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture Jul 3, 2020
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...
Machine Learning Droughts Genotype Stress, Physiological Plant Breeding Algorithms Seeds Quantitative Trait Loci Fabaceae Phenotype
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