Xin Pan, Ya Gao, Fang Zeng, Chunmei Zheng, Wenxuan Ge, Yan Wan, Yanxia Sun, Xiaoyong Wu^*

Phyton-International Journal of Experimental Botany, Vol.92, No.10, pp. 2921-2936, 2023, DOI:10.32604/phyton.2023.029853

Abstract Pre-harvest sprouting (PHS) will have a serious effect both on the yield and quality of quinoa (Chenopodium quinoa Willd.). It is crucial to select and breed quinoa varieties with PHS resistance and excellent agronomic traits for guidance production and utilization of quinoa. A comprehensive evaluation of the PHS resistance and agronomic traits of 37 species of quinoa resources was conducted in Chengdu Plain. The evaluation used various methods, including grain germination rate (GR), grain germination index (GI), total spike germination rate (SR), total grain germination index (SI), grey correlation analysis (GCA), cluster analysis and correlation analysis. Results showed significant differences… More >

K. R. Naveen Kumar¹, Husam Lahza², B. R. Sreenivasa^3,*, Tawfeeq Shawly⁴, Ahmed A. Alsheikhy⁵, H. Arunkumar¹, C. R. Nirmala¹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3239-3260, 2023, DOI:10.32604/csse.2023.036629

Abstract Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making information. Precision agriculture uses data mining to advance agricultural developments. Many farmers aren’t getting the most out of their land because they don’t use precision agriculture. They harvest crops without a well-planned recommendation system. Future crop production is calculated by combining environmental conditions and management behavior, yielding numerical and categorical data. Most existing research still needs to address data preprocessing and crop categorization/classification. Furthermore, statistical analysis receives less attention, despite producing more accurate and valid results. The study was conducted on a dataset about Karnataka state,… More >

Luli Li^1,2, Nigel G. Halford³, Huihui Wang⁴, Yingjie Zong¹, Zhenzhu Guo¹, Ruiju Lu¹, Chenghong Liu¹, Zhiwei Chen^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1275-1287, 2023, DOI:10.32604/phyton.2023.026946

Abstract Barley (Hordeum vulgare L.) is an important economic crop for food, feed and industrial raw materials. In the present research, 112 barley landraces from the Shanghai region were genotyped using genotyping-by-sequencing (GBS), and the genetic diversity and population structure were analyzed. The results showed that 210,268 Single Nucleotide Polymorphisms (SNPs) were present in total, and the average poly-morphism information content (PIC) was 0.1642. Genetic diversity and population structure analyses suggested that these barley landraces were differentiated and could be divided into three sub-groups, with morphological traits of row-type and adherence of the hulls the main distinguishing factors between groups. Genotypes… More >

Jianyi Zhu¹, Hui Peng^1,2, Xiaoning Lu^1,2, Jianxiong Lyu^1,2,3, Tianyi Zhan^1,2,*

Journal of Renewable Materials, Vol.11, No.3, pp. 1425-1437, 2023, DOI:10.32604/jrm.2022.023464

Abstract Many tree species are planted in China with variable properties and usage. Toward exploring the structure-properties relationships of wood and classifying the species more reasonably, the physiomechanical properties of the domestic wood species in China were analyzed statistically. According to the correlation analysis, the mechanical properties were closely related to the wood density. Except impact toughness and cleavage strength, the correlation coefficients between mechanical properties and densities were more than 0.8. However, shrinkage properties showed fewer correlations with densities, and the coefficient was no more than 0.7. Primary component analysis was proved to be feasible to explore the information of… More >

XIAOJUN ZHOU^*, XIAOYU LU, XUBO WANG

BIOCELL, Vol.46, No.11, pp. 2489-2495, 2022, DOI:10.32604/biocell.2022.020311

Abstract Euptelea pleiosperma is a characteristic species of East Asian flora with both ornamental and scientific values. Based on the reduced-representation sequencing (RRS) technology of RAD-Seq, this study conducted high-throughput Illumina paired-end sequencing to find SSR marker information in the genome of E. pleiosperma, and to screen and verify polymorphism of SSR markers. We obtained 5.5G of high-quality data using RAD-Seq. The total number of contigs of the RAD tags was 299,376, with the maximum contig length of 2,062 bp and the average length of 445 bp. From these sequences, we identified 20,718 SSR loci, with a distribution density of one… More >

Kun Du, Zhen Wei^*

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 751-760, 2022, DOI:10.32604/fdmp.2022.019577

Abstract Improving drilling efficiency is the best way to reduce drilling costs and the choice of the drilling mode is instrumental in doing so. At present, however, a standard approach for the optimization of these processes does not exists yet. Through a comparative statistical analysis of the rock-breaking mechanisms and the characteristics of different drilling methods, this research proposes a set of cues to achieve this objective. Available statistical data are classified by means of a fuzzy cluster analysis according to the anti-drilling characteristic parameters of formation. The results show that different drilling methods rely on their own rock breaking mechanisms… More >

Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2435-2458, 2022, DOI:10.32604/cmc.2022.022414

Abstract Cluster analysis in spectroscopy presents some unique challenges due to the specific data characteristics in spectroscopy, namely, high dimensionality and small sample size. In order to improve cluster analysis outcomes, feature selection can be used to remove redundant or irrelevant features and reduce the dimensionality. However, for cluster analysis, this must be done in an unsupervised manner without the benefit of data labels. This paper presents a novel feature selection approach for cluster analysis, utilizing clusterability metrics to remove features that least contribute to a dataset's tendency to cluster. Two versions are presented and evaluated: The Hopkins clusterability filter which… More >

Tossapon Boongoen, Natthakan Iam-On^*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1993-2011, 2022, DOI:10.32604/cmc.2022.019776

Abstract A mix between numerical and nominal data types commonly presents many modern-age data collections. Examples of these include banking data, sales history and healthcare records, where both continuous attributes like age and nominal ones like blood type are exploited to characterize account details, business transactions or individuals. However, only a few standard clustering techniques and consensus clustering methods are provided to examine such a data thus far. Given this insight, the paper introduces novel extensions of link-based cluster ensemble, and that are accurate for analyzing mixed-type data. They promote diversity within an ensemble through different initializations of the k-prototypes algorithm… More >

Ting Wang¹, Zhiqiang Wang^1,*, Yin Yang¹, Jianhui Zhou^2,*

Journal of Renewable Materials, Vol.10, No.2, pp. 527-540, 2022, DOI:10.32604/jrm.2022.017955

Abstract The acoustic emission (AE) technique can perform non-destructive monitoring of the internal damage development of bamboo and wood materials. In this experiment, the mechanical properties of different bamboo and wood (bamboo scrimber, bamboo plywood and SPF (Spruce-pine-fir) dimension lumber) during four-point loading tests were compared. The AE activities caused by loadings were investigated through the single parameter analysis and K-means cluster analysis. Results showed that the bending strength of bamboo scrimber was 3.6 times that of bamboo plywood and 2.7 times that of SPF dimension lumber, respectively. Due to the high strength and toughness of bamboo, the AE signals of… More > Graphic Abstract

Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1945-1965, 2021, DOI:10.32604/cmc.2021.018517

Abstract Supervised machine learning techniques have become well established in the study of spectroscopy data. However, the unsupervised learning technique of cluster analysis hasn’t reached the same level maturity in chemometric analysis. This paper surveys recent studies which apply cluster analysis to NIR and IR spectroscopy data. In addition, we summarize the current practices in cluster analysis of spectroscopy and contrast these with cluster analysis literature from the machine learning and pattern recognition domain. This includes practices in data pre-processing, feature extraction, clustering distance metrics, clustering algorithms and validation techniques. Special consideration is given to the specific characteristics of IR and… More >