Pertanika Journal of Tropical Agricultural Science
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Pertanika · Universiti Putra Malaysia Press

Pertanika Journal of Tropical Agricultural Science

Official journal of Universiti Putra Malaysia for peer-reviewed research across tropical agriculture and allied agricultural sciences.

e-ISSN 2231-8542 ISSN 1511-3701
Research article

Site-specific Morphological and Nutritional Variability of Caulerpa lentillifera in Malaysia: A Chemometric Approach for Tropical Aquaculture

Nor Atikah Husna Ahmad Nasir, Mohd Hafis Yuswan, Nor Nadiah Abd Karim Shah, Aswir Abd Rashed, Kazunori Kadota, Muhamad Shirwan Abdullah Sani, Mohd Fakhrulddin Ismail, Alhussein M. Al-Awaadh, Mian Nadeem Riaz, and Yus Aniza Yusof

https://doi.org/10.47836/pjtas.49.1.19
KeywordsCaulerpa lentillifera, chemometric analysis, morphological plasticity, proximate composition, sea grape, site-specific
Article content

Abstract

Caulerpa lentillifera is an important tropical green macroalgae cultivated and harvested across Southeast Asia. Nevertheless, its morphological and biochemical responses towards varying environmental conditions remain insufficiently discussed. This study aimed to characterise the site-specific morphological, nutritional, and mineral variability of C. lentillifera collected from three Malaysian populations. Samples were harvested from wild populations in Port Dickson (PD) and Semporna (SS), and from a cultured pond population from Pulau Langkawi (PL). This study also applied chemometric methods to identify unique compositional patterns relevant to tropical aquaculture. Morphological and proximate analyses found that the PL sample has an assimilator length of up to 94 mm and a moisture content of 96% (wet weight basis), whereas PD samples had higher total nitrogen content (1.36 mg/L), crude fiber (3.45 g/100 g), and rhizoid length (13.8 mm), indicating site-related variability. Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and hierarchical heatmaps were used to integrate water-quality, morphometric, nutritional, mineral, and heavy-metal datasets and to visualise site-specific clustering patterns. The PCA explained 62.5% of the total variance, and the PLS-DA model showed clear, yet descriptive, group separation (R² and Q² > 0.9; p = 0.001). The fibre, calcium, and carbohydrates were identified as the main discriminant factors. Overall, the analyses revealed distinct site-associated compositional trends rather than definitive classifications. These findings provide baseline insights to guide future site selection and cultivation strategies for sustainable tropical aquaculture.