Development of deep learning-based mobile application for predicting in-situ habitat suitability of Perilla frutescens L. in real-time-Reference-Cited by-同舟云学术

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Development of deep learning-based mobile application for predicting in-situ habitat suitability of Perilla frutescens L. in real-time

Published:2024-08 Issue: Volume:8 Page:100508
ISSN:2772-3755
Container-title:Smart Agricultural Technology
language:en
Short-container-title:Smart Agricultural Technology

Author:

Singh Naseeb^ORCID,Kaur Simardeep,Mahore Vijay^ORCID,Pohshna Chwadaka,Shekhar Shashank,Bhardwaj Rakesh^ORCID

Publisher

Elsevier BV

Reference78 articles.

1. Prospects of orphan crops in climate change;Mabhaudhi;Planta,2019

2. Orphan crops: a best fit for dietary enrichment and diversification in highly deteriorated marginal environments;Talabi;Front. Plant Sci.,2022

3. Nutritional and short term toxicological evaluation of Perilla seed oil;Longvah;Food Chem.,2000

4. Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models;Su;Sci. Rep.,2021

5. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills;Yang;Ecol. Eng.,2013

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