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• Methods of Principal Component Analysis and Cluster Analysis in Multi-Dimension Statistics Data Processing

  Nguyen Huu Du

  Received: 06-05-2014 / Accepted: 15-07-2014

   Abstract PDF (VIETNAMESE)

  A crucial issue posed in practical research is analyzing and processing of collected data. If collected data is large, examining the information will be relatively complex and troublesome. This article presented two efficient methods in multi-dimension data processing, principal component analysis and cluster analysis. These methods were successfully tested to analyze a set of data from a research project in agronomy.

• Seasonal Variation of Soil Quality in My Phuoc Melaleuca Forest, Soc Trang Province

  Nguyen Thanh Giao, Tran Thi Kim Hong

  Received: 31-08-2020 / Accepted: 07-10-2020

   Abstract PDF (VIETNAMESE)

  The study was conducted to evaluate seasonal variation in soil quality in My Phuoc melaleuca forest, Soc Trang province through the indicators of pH, conductivity (EC), total nitrogen (TN), total phosphorus (TP), organic matter (OM), total iron (Fet), aluminum exchange (Al) using multivariate statistics. Cluster Analysis (CA), Principal Component Analysis (PCA) and Discriminant Analysis (DA) were used to assess seasonal variation in soil quality. The findings indicated that soil environment in the study area had very low pH, medium Al, EC and high Fet, low TP, medium OM, and high TN. All soil quality indicators (except EC, Al) tended to increase in the rainy season. CA results showed that 28 locations were divided into 6 groups in dry season and 4 groups in rainy season indicating highly seasonally varied in soil quality. PCA results presented that Fet, Al, OM significantly influenced on soil quality in the dry season, while pH, TN, and TP significant affected on soil quality in the rainy season. DA indicated that EC, OM and TP were the main variables causing the difference in soil quality between the two seasons. The results of the study provided important information serving the management of soil environment quality in My Phuoc Melaleuca Forest Reserve.

• Assessment of Genetic Diversity of Yellow Waxy Corn Germplasm Based on Phenotype and SSR Markers

  Nguyen Trung Duc, Pham Quang Tuan, Nguyen Thi Nguyet Anh, Nguyen Quoc Trung, Le Thi Tuyet Cham, Vu Van Liet

  Received: 21-12-2022 / Accepted: 05-10-2023

   Abstract PDF (VIETNAMESE)

  This study aimed to assess the genetic diversity of 15 yellow waxy corn genotypes with 3 check lines using 18 agronomic traits and 14 SSR markers. The field experiment was arranged in a randomized complete block design with 3 replicates in 2022 Spring season in Hanoi. The results showed that single plant grain yield was strongly positively correlatedwith cob diameter (r = 0.72), 100 grains weight (r = 0.62), and number of kernels per row (r = 0.61). Total soluble solids were negatively correlated (P <0.01) with pericarp thickness (r = -0.62). Principal component analysis showed that all of the investigated traits could be used for phenotypic diversity analysis. PIC values ranged from 0.10 (phi072and phi1277) to 0.32 (phi2276). Corn genotypes were classified into 3 groups at the similarity coefficient 45.3 based on phenotype, and into 5 groups at the similarity coefficient 0.21 based on SSR markers. Seven lines viz., YW01, YW03, YW4, YW7, YW12, YW13, YW14 and two checks viz., SWsyn1, UV showed consistent in phenotypic and genotypic grouping. Five promising lines were selected viz., YW10, YW13, YW12, YW07, and YW01 based on MGIDI index with 40% selection pressure.

• Building and Applying TheZ-Score Model in Risk Management of Poultry Production Farm in Thai Binh Province

  Nguyen Thi Thu Trang, Nguyen Quoc Chinh, Vu Quoc Hung

  Received: 10-10-2016 / Accepted: 10-01-2017

   Abstract PDF (VIETNAMESE)

  Z-score model was well-known as an application for enterprises risk forecasting. Nevertheless, there ithas been few application and useshort of empirical researches using Z- score model in agricultural farms, includung animal production farms. The survey was conducted on a database of 220 poultry production farms in Thai Binh province,using Principal Component Analysis (CPA)fortechnical analysis of five basic groups to caculate Z- score model, with the support of SPSS 20.0.The results of this research: Firstly, buildingTheZ- score model was constructed for the poultry production farmsin Thai Binh province. Besides, this research hasveapplied theismodel on a district in the study to calculate the density and zoning. TheisRresultsshowed that 34% of farms were in the healthy zone, 59% of inthe area is unclear zone,and 7% in the bankruptcy zone. To Rreduceingthe risk of bankruptcy of farms in Thai Binh province, theshould adopt following measuresshould be taken: (1) Raise awarenessraisingabout technical ranchers, markets and risks; (2) Having Self-insurance in the production; (3) Improving Aaccessibilityto agricultural insurance in the same animal stock assurance;and(4) Linkingproduction and consumption linkage to ensuring regulate production.

• Solutions to Enhancing the Quality of Soft Skills Training at the Vietnam National University of Agriculture

  Ngo Tri Duong, Nguyen Thi Thu Huyen, Le Thi Quynh Trang, Nguyen Minh Duc, Nguyen Tho Quang Anh

  Received: 04-06-2023 / Accepted: 05-10-2023

   Abstract PDF (VIETNAMESE)

  Soft skills are considered essential for individual success. Teaching soft skills in universities helps students enhance their soft skills and provides necessary complement to hard skills. This study aimed to assess the current status of soft skills training quality at the Vietnam National University of Agriculture and propose solutions to enhance the quality of soft skills training. The study conducted survey from 493 students, 23 lecturers, and 32 employers, and employed descriptive statistical methods, particularly principal component analysis, to analyze the current situation and factors influencing the improvement of the quality of soft skills training. The research revealed that the Vietnam National University of Agriculture has been offering soft skills training since 2016, covering 10 skills according to the learning outcome standards. Over 6 years training, more than 61,000 students were trained for soft skills. Based on evaluation from employers, teachers, and students, 70% of them were rated good or excellent for the quality of soft skills training. However, to further improve the quality of soft skills training at the university, it is necessary to focus on solutions related to program design, training organization, evaluation methods, infrastructure, teaching faculty, teaching methods, policies, and financial support. These efforts will contribute to enhancing the overall training quality.