4.7 Article

Locality Preserved Selective Projection Learning for Rice Variety Identification Based on Leaf Hyperspectral Characteristics

Related references

Note: Only part of the references are listed.
Article Agronomy

Selection of Agronomic Parameters and Construction of Prediction Models for Oleic Acid Contents in Rapeseed Using Hyperspectral Data

Junwei Lu et al.

Summary: This study investigates the prediction of oleic acid content in high oleic acid oilseed rape. The results show that the oleic acid content in oilseed rape leaves can better explain the relationship between the reflection spectrum of the leaf and the oleic acid content in rapeseed.

AGRONOMY-BASEL (2023)

Article Chemistry, Multidisciplinary

Identification of Rice Seed Varieties Based on Near-Infrared Hyperspectral Imaging Technology Combined with Deep Learning

Baichuan Jin et al.

Summary: This study successfully established variety identification models for rice seeds using NIR hyperspectral technology combined with deep learning methods. The results showed that deep learning methods, especially the ResNet model, performed the best in classification accuracy. By visualizing the saliency map method to identify the bands with the largest data contribution, the study provided an effective way to distinguish rice seeds of different varieties.

ACS OMEGA (2022)

Article Agriculture, Multidisciplinary

Establishment and application of an SNP molecular identification system for grape cultivars

Wang Fu-qiang et al.

Summary: The study aimed to develop a set of SNP markers for distinguishing cultivated grape cultivars in China, providing technical support for protection, registration, and market rights. Through sequencing 304 grape accessions, 517 high-quality loci were obtained and designed as KASP markers. Population structure analysis identified two main populations among 348 grape accessions, with six subpopulations. A core set of 25 KASP markers successfully distinguished 95.69% of the grape accessions.

JOURNAL OF INTEGRATIVE AGRICULTURE (2022)

Article Computer Science, Artificial Intelligence

Rice Variety Identification Based on the Leaf Hyperspectral Feature via LPP-SVM

Tian Hu et al.

Summary: This paper proposes a method for rice variety identification based on the hyperspectral characteristics of leaves. Hyperspectral data of rice leaves were collected and locality preserving projections (LPP) was used to extract low-dimensional features. Support vector machine (SVM) was then used for rice variety identification. The experimental results showed high identification rates for both early and late rice varieties.

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (2022)

Article Computer Science, Artificial Intelligence

Supervised Feature Selection With Orthogonal Regression and Feature Weighting

Xia Wu et al.

Summary: The researchers proposed a novel supervised orthogonal least square regression model with feature weighting for feature selection, and solved the optimization problem using generalized power iteration and augmented Lagrangian multiplier methods. Experimental results demonstrate that this method outperforms traditional methods in reducing feature dimensionality and achieving better classification results, with the convergence of the iterative method also being proven.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Agriculture, Multidisciplinary

Establishment and application of an accurate identification method for fragrant soybeans

Zhang Yong-fang et al.

Summary: A new method was established to quantify the content of 2-acetyl-1-pyrroline (2-AP) in soybeans using gas chromatography-mass spectrometry, providing an accurate identification technique for fragrant soybeans. Analysis of 101 soybean genotypes revealed seven elite genotypes classified as grade one fragrant soybeans, offering important insights for gene discovery and quality breeding in soybeans.

JOURNAL OF INTEGRATIVE AGRICULTURE (2021)

Article Engineering, Electrical & Electronic

Locality Preserving Robust Regression for Jointly Sparse Subspace Learning

Ning Liu et al.

Summary: In this paper, a novel regression method called Locality Preserving Robust Regression (LPRR) is proposed to address the issues encountered by conventional L-2, L-1 norm regression methods. Experimental results demonstrate that LPRR outperforms some famous subspace learning methods in classification tasks.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2021)

Article Food Science & Technology

Identification of rice-weevil (Sitophilus oryzae L.) damaged wheat kernels using multi-angle NIR hyperspectral data

Liu Zhang et al.

Summary: This study proposed a novel method to identify sound wheat kernels and RW-damaged wheat kernels using multi-angle near-infrared hyperspectral data calibration model. The best hybrid model SNV-SPA-LDA was found through multivariate data analysis, with an accuracy of 97%, sensitivity of 98%, and specificity of 96%. The results indicated the reliability of the calibrated model based on hyperspectral data from four sides of wheat kernel.

JOURNAL OF CEREAL SCIENCE (2021)

Article Spectroscopy

Hyperspectral imaging technology combined with deep forest model to identify frost-damaged rice seeds

Liu Zhang et al.

SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY (2020)

Article Instruments & Instrumentation

Non-destructive classification of defective potatoes based on hyperspectral imaging and support vector machine

Yamin Ji et al.

INFRARED PHYSICS & TECHNOLOGY (2019)

Article Engineering, Electrical & Electronic

Hyperspectral Band Selection via Adaptive Subspace Partition Strategy

Qi Wang et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)

Article Engineering, Electrical & Electronic

Attend in Bands: Hyperspectral Band Weighting and Selection for Image Classification

Jing Wang et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)

Article Agriculture, Multidisciplinary

SSR fingerprinting of 203 sweetpotato (Ipomoea batatas (L.) Lam.) varieties

Meng Yu-sha et al.

JOURNAL OF INTEGRATIVE AGRICULTURE (2018)

Article Computer Science, Information Systems

L2,1-Norm Discriminant Manifold Learning

Yang Liu et al.

IEEE ACCESS (2018)

Article Biochemistry & Molecular Biology

Variety Identification of Raisins Using Near-Infrared Hyperspectral Imaging

Lei Feng et al.

MOLECULES (2018)

Article Geochemistry & Geophysics

Unsupervised Hyperspectral Band Selection by Dominant Set Extraction

Guokang Zhu et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2016)

Article Agriculture, Multidisciplinary

Development of a core set of SNP markers for the identification of upland cotton cultivars in China

Kuang Meng et al.

JOURNAL OF INTEGRATIVE AGRICULTURE (2016)

Editorial Material Multidisciplinary Sciences

Rice breeding: never off the table

Jiayang Li

NATIONAL SCIENCE REVIEW (2016)

Article Food Science & Technology

Use of Hyperspectral Imaging to Discriminate the Variety and Quality of Rice

Lu Wang et al.

FOOD ANALYTICAL METHODS (2015)

Article Computer Science, Artificial Intelligence

Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction

Feiping Nie et al.

PATTERN RECOGNITION LETTERS (2012)

Article Computer Science, Artificial Intelligence

Outlier-resisting graph embedding

Yanwei Pang et al.

NEUROCOMPUTING (2010)