DECIPHERING BIOSTIMULANT ORIGINS: ANALYZING AMINO ACID COMPOSITION IN HYDROLYZED PROTEINS

Аннотация

INTRODUCTION amino acids can vary significantly depending on Biostimulants have emerged as key components in the source material and manufacturing process modern agricultural practices, offering solutions to used to produce biostimulants. Therefore, enhance crop productivity, resilience, and analyzing the amino acid profile of biostimulants sustainability. Derived from various organic holds promise as a means of deciphering their sources such as plants, animals, and microbes, origin and quality. biostimulants contain a diverse array of compounds that promote plant growth, nutrient This study proposes a novel approach for uptake, and stress tolerance. However, ensuring classifying biostimulant origin based on the amino the quality and efficacy of biostimulants requires a acid composition of hydrolyzed proteins. By comprehensive understanding of their origin and leveraging advanced analytical techniques and composition. statistical methods, we aim to identify distinctive patterns in amino acid profiles that can Amino acids, the building blocks of proteins, play a differentiate biostimulants derived from different crucial role in the biological activity of sources. By elucidating the relationship between biostimulants. The composition and abundance of https://www.theamericanjournals.com/index.php/tajhfr 7 THE USA JOURNALS THE AMERICAN JOURNAL OF HORTICULTURE AND FLORICULTURE RESEARCH (ISSN – 2689-0976) VOLUME 06 ISSUE04 amino acid composition and biostimulant origin, analytical techniques to generate comprehensive this approach offers a reliable and efficient method amino acid profiles for each biostimulant sample. for quality control and regulatory compliance in Following amino acid analysis, statistical methods the biostimulant industry. were employed to identify patterns and The classification of biostimulant origin has relationships within the data. Multivariate significant implications for agricultural statistical techniques, such as principal component sustainability and food security. By accurately analysis (PCA) and cluster analysis, were utilized to identifying the source of biostimulants, farmers explore similarities and differences in amino acid can make informed decisions regarding their use, composition between biostimulant samples optimizing crop performance while minimizing derived from different sources. These analyses environmental impact. Furthermore, facilitated the identification of distinctive features manufacturers can ensure product consistency and that could be used to classify biostimulant origin integrity, fostering consumer confidence and based on amino acid composition. market competitiveness. To further refine the classification of biostimulant In this paper, we present the methodology and origin, machine learning algorithms were applied findings of our study on deciphering biostimulant to the amino acid data. Supervised learning origins through the analysis of amino acid algorithms, including support vector machines composition in hydrolyzed proteins. By elucidating (SVM) and random forest classifiers, were trained the relationship between amino acid profiles and on a subset of the data to develop predictive biostimulant origin, we aim to advance our models for classifying biostimulant origin. These understanding of biostimulant quality and efficacy, models were validated using independent test ultimately supporting sustainable agriculture and datasets to assess their accuracy and robustness. food production. The first step in the methodology involved the METHOD collection of biostimulant samples from various sources, including plant-based, animal-derived, The process of deciphering biostimulant origins and microbial sources. These samples were through the analysis of amino acid composition in obtained from reputable manufacturers and hydrolyzed proteins began with the careful suppliers to ensure consistency and reliability. collection and preparation of biostimulant samples Upon collection, the biostimulant samples were sourced from various organic materials, including carefully processed and prepared for analysis. This plants, animals, and microbes. These samples were involved homogenization and extraction to obtain processed to extract hydrolyzed proteins suitable hydrolyzed proteins suitable for amino acid for amino acid analysis. Subsequently, amino acid analysis. analysis was conducted using high-performance liquid chromatography (HPLC) or similar https://www.theamericanjournals.com/index.php/tajhfr 8 THE USA JOURNALS THE AMERICAN JOURNAL OF HORTICULTURE AND FLORICULTURE RESEARCH (ISSN – 2689-0976) VOLUME 06 ISSUE04 performed to identify patterns and relationships The hydrolyzed protein samples were subjected to among the data. Multivariate statistical techniques, amino acid analysis using high-performance liquid such as principal component analysis (PCA) or chromatography (HPLC) or similar analytical cluster analysis, were employed to explore techniques. Amino acid profiles