Genetic Diversity and Selection of High Performing Cultivars for Grain Yield and Yield Components Improvement in Rice |Chapter 6 | Food Science and Agriculture: Research Highlights Vol. 2

Background: Understanding the genetic diversity of the available rice germplasm could lead to the use of the best donors for the development of improved varieties with large genetic background.

 

Aim: This study aimed to estimate the genetic diversity for grain yield and yield components among one hundred rice genotypes and select the best performing for grain yield and grain characteristics improvement.

 

Study Design: The experiment was conducted in a 10 × 10

-lattice design in three replications under lowland field conditions.

 

Place and Duration of Study: This experiment was conducted at the Council for Scientific and Industrial Research-Crops Research Institute (CSRI-CRI), Fumesua-Kumasi, Ghana, during the major planting season from March to September 2018.

 

Methodology: Data were collected on grain yield (GY), tiller number (Ti), days to flowering (DTF), plant height (PH), panicle length (PL), kernel length (KL), and kernel length-to-width ratio (KLW). One hundred rice genotypes were used to estimate the genetic variability, including genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV), broad-sense heritability and genetic advance among the traits under study. The correlation, principal components, cluster and regression analysis were conducted to quantify the relationships among the traits. Data were analysed following a mixed model with genotypes as random effects and repetitions as fixed effects. Genotypes were selected using the multi-trait genotype-ideotype distance index (MGIDI).

 

Results: The GCV ranged from 4.3% for PL to 17.9% for GY. High heritability and moderate genetic advances were observed for DTF, PH, KL, and KLW. In general, the magnitudes of genetic correlations were higher than phenotypic correlations. GY showed a positive association with DTF and PL at both genetic and phenotypic levels, and with PH and KW at the genetic level only. The genotypes clustered into three groups and the first three principal components explained about 70.3% of the total variation with KLW, DTF, KL, PL, KL and GY being the principal discriminatory characters in descending order. Ten high-performing genotypes (CRI-AgraRice, T-MARSHAL, NERICA-L 19, CRI-AMANKWATIA, ART58-66-1-1-B-B, ART108-2-1-1-B-B, ART112-74-1-1-B-B, CRI-1-11-15-21, FAROX 508-3-10-F43-1-1 and Local_Sokwai) were identified through MGIDI index.

 

Conclusion: There was adequate genetic variability in the germplasm to support breeding for improved grain yield and indirect selection for high yield can be done in early generations using DTF, PH, and PL.

 

Author (s) Details

Maxwell Darko Asante
Council for Scientific and Industrial Research – Crops Research Institute (CSRI-CRI), Fumesua-Kumasi, Ghana and CSIR College of Science and Technology, Department of Plant Resources, P.O. Box 3785, Fumesua-Kumasi, Ghana.

 

Kossi Lorimpo Adjah
Africa Rice Center (AfricaRice), M’bé Research Station, 01 BP 2551 Bouaké 01, Côte d’Ivoire.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/fsarh/v2/4320

Determining the Relationship between Body Weight and Body Dimensions in Adult Domestic Cavy, Using Principal Component Analysis | Chapter 6 | Research Aspects in Agriculture and Veterinary Science Vol. 4

 The study used principal component analysis (PCA) to evaluate the association between body weight and several morphological characteristics in adult domestic cavies with the goal of predicting body weight from morpho-structural traits. The association between body weight and body dimensions in adult domestic cavy was studied using body weight and eleven (11) morpho-structural features from 300 adult cavies collected from three states in Northern Nigeria. The least squares analysis and main components analysis procedures were used to analyse the data acquired on bodyweight and body dimension. Adult cavies had a mean body weight of 495.007.35g, according to the findings. The average body dimensions were 2.570.02cm for the femur radius (FR) and 27.170.16cm for the body length (BL). Two main components were identified, accounting for 64.47 percent of the total variance in body dimensions. The first principal component (PC1) explained 49.25 percent of the overall variation by loading significantly on belly girth (BG), neck circumference (NC), heart girth (HG), body length (BL), shoulder length (SL), head length (HL), and trunk length (TL). The second main component (PC2), which was loaded on hind leg length (HLL), fore leg length (FLL), and hip to kneel length, accounted for 15.214 percent of the generalised variance (HKL). The orthogonal body shape features determined from the component analysis explained 52.5 percent of the variation in adult cavies' body weight. It was determined that linear body measurements could be used to accurately forecast adult cavies' live body weights.

Author(S) Details

T. E. Zetang
Department of Animal Breeding and Physiology, Federal University of Agriculture Makurdi Benue State, Nigeria.

O. M. Momoh
Department of Animal Breeding and Physiology, Federal University of Agriculture Makurdi Benue State, Nigeria.

P. A. Addass
Department of Animal Breeding and Physiology, Federal University of Agriculture Makurdi Benue State, Nigeria.

M. E. Khan
Department of Chemistry Federal University Lokoja, Kogi State, Nigeria.

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