Determination of Cassava Leaf Area for Breeding Programs

The evaluation of leaf area provides valuable information for decision-making for the cassava yield trail. The objectives of this study were (1) to determine the relationship between the leaf area and yield of the segregating populations and (2) to investigate the suitable mathematical model for cal...

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Published inAgronomy (Basel) Vol. 12; no. 12; p. 3013
Main Authors Phoncharoen, Phanupong, Banterng, Poramate, Vorasoot, Nimitr, Jogloy, Sanun, Theerakulpisut, Piyada
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.12.2022
Subjects
Agricultural production
Biomass
Cassava
Correlation
Decision making
estimation
Experiments
Genotype & phenotype
Genotypes
Harvest
Leaf area
Leaf area index
Leaves
linear regression
Lobes
Mathematical analysis
Mathematical models
Mean square errors
segregating progenies
Statistical analysis
yield
Thailand
Southeast Asia
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Summary:The evaluation of leaf area provides valuable information for decision-making for the cassava yield trail. The objectives of this study were (1) to determine the relationship between the leaf area and yield of the segregating populations and (2) to investigate the suitable mathematical model for calculating cassava leaf area. The single-row trial for 60 segregating progenies of Kasetsart 50 × CMR38–125–77 was conducted from 2021 to 2022. The trial for eighteen progenies and the Kasetsart 50 and CMR38–125–77 was carried out in 2022. The sampled leaves for each genotype were collected to measure the leaf area. The length (L) and width of the central lobe (W), number of lobes (N), the product of the length and width (L × W; K), and the product of the length and number of lobes (L × N; J) were recorded for developing the mathematical models. The result showed that there were statistically significant correlations between the maximum individual leaf area and the total crop fresh weight and storage root fresh weight. The mathematical model LA = −3.39L + 2.04K + 1.01J − 15.10 is appropriate to estimate the maximum individual leaf area and leaf area index (LAI). This mathematical model also provided the estimated individual maximum leaf area that had the highest correlation with actual biomass at the final harvest as compared to the other three functions. The results showed statistical significance for the estimated LAI and biomass correlation.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy12123013