Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy

Author:

Kaur Simardeep,Singh NaseebORCID,Dagar Preety,Kumar Amit,Jaiswal Sandeep,Singh Binay K.,Bhardwaj Rakesh,Chand Rana Jai,Riar AmritbirORCID

Funder

Swiss Agency for Development and Cooperation

Publisher

Elsevier BV

Reference70 articles.

1. Identification and quantification of essential oil content and composition, total polyphenols and antioxidant capacity of Perilla frutescens (L.) Britt;Ahmed;Food Chemistry,2018

2. Perilla frutescens L.: A dynamic food crop worthy of future challenges;Aochen;Frontiers in Nutrition,2023

3. In vitro screening antiviral activity of Thai medicinal plants against porcine reproductive and respiratory syndrome virus;Arjin;BMC Veterinary Research,2020

4. Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran;Bagchi;Food Chemistry,2016

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