Data Mining Techniques: New Method to Identify the Effects of Aquaculture Binder with Sardine on Diets of Juvenile Litopenaeus vannamei

Abstract

In this research, a dataset of growth performances and nutritional composition of juvenile Litopenaeus vannamei after being fed two diets that include aquaculture binder with sardine for 7 weeks was analyzed using data mining techniques: the K-Means Clustering Algorithm and PCA Biplot, to have a visualization of each parameter (vector) measured. The parameters evaluated were: weight gain, specific growth rate, feed efficiency, protein efficiency ratio, survival percent, moisture content, crude protein, crude lipid, and ash content. Data mining tools showed the juvenile Litopenaeus vannamei fed with mixture 2 (pellets mixed with the binder of sardine subproducts) presented the highest growth performances and nutritional composition, 23 juvenile L. vannamei shrimps showed higher relation with crude protein and crude lipid, 30 L. vannamei shrimps presented higher relation with ash, and 37 juvenile L. vannamei shrimps showed higher relation with ash and moisture. The results obtained in experimental procedures indicate that the use of a binder of sardine subproducts in shrimp diets improves the commercial parameters, improving the aquaculture field.

Multivariate Statistical Techniques: A New Approach to Identify the Commercial Properties of Mixtures of Flours of Lentinula edodes and Cocoa Pod Husk

“…Inertia allows a quick and accurate evaluation of the most important points (flour samples) of the factorial plane. Figure 1a indicates that eight samples of the flours of mixture 1 (5,6,8,13,20,26,28,36,41) presented the highest content of protein, moisture and fat; four samples of the flours of mixture 1 (1,17,24,37) showed the highest content of total dietary fiber (TDF); eight samples of mixture 1 (10,18,21,31,32,34,46,47) presented the highest values of carbohydrates; and one sample of mixture 1 (30) indicated highest value of ash. On the other hand, Figure 1b points out that 13 samples of the flours of mixture 2 (2,4,5,7,13,14,27,30,32,37,44,45,48) presented the highest content of protein, moisture and fat, and 13 samples of the flours of mixture 2 (3,12,18,20,22,25,26,28,29,…”

“…Figure 2a indicates the presence of three important groups of samples in mixture 1: Cluster 1, "color blue", formed by 11 samples (10,16,28,31,32,33,34,35,38,45,46), that indicated the highest relation with the antimicrobial activity; Cluster 2, "color red", formed from 28 samples (1,2,5,7,11,12,14,15,18,21,22,23,24,25,27,29,30,36,37,39,41,42,43,44,47,48,49,50), which presented the highest values of antioxidant activity, pH and water activity (a w ); and Cluster 3, "color green", formed of 11 samples (3,4,6,8,9,13,17,19,20,…”

“…Biplots allow the study of sets of variables in a population of individuals and the determination of data sets with the same characteristics through the use of mathematical operations derived from geometry, matrix calculus and multivariate distributions [21]. These multivariate methods allow the extraction of new principal components that have greater variance compared to the original components.…”

Avances en la Economía Circular del Ecuador. Una estrategia para la sostenibilidad basada en Métodos BIPLOT

“…Los Biplots permiten estudiar conjuntos de variables en una población de individuos y determinar conjuntos de datos con las mismas características mediante el uso de operaciones matemáticas derivadas de la geometría, cálculo matricial y distribuciones Capítulo I: Introducción y Objetivos 5 multivariantes (Guevara-Viejó et al, 2022a). Estos métodos multivariantes permiten extraer nuevos componentes principales que tienen una mayor varianza en comparación con los componentes originales.…”