Study of Diversity and Estimation of Leaf Area in Different Mint Ecotypes Using Artificial Intelligence and Regression Models under Salinity Stress Conditions-Reference-Cited by-同舟云学术

Study of Diversity and Estimation of Leaf Area in Different Mint Ecotypes Using Artificial Intelligence and Regression Models under Salinity Stress Conditions

Published:2019-12-01 Issue:32 Volume:11 Page:59-73
ISSN:2228-6128
Container-title:Journal of Crop Breeding
language:fa
Short-container-title:jcb

Author:

Hosseini seyed jaber,Tahmasebi-sarvestani Zeinolabedin,Pirdashti Hematolahe,Modarres sanavi Seyed ali mohammad,Mokhtassi-bidgoli Ali,Hazrati Saeid, , , , , ,

Publisher

CMV Verlag

Link

http://jcb.sanru.ac.ir/article-1-1046-en.pdf

Reference49 articles.

1. Artificial Neural Network Model for the Prediction of the Cotton Crop Leaf Area

2. Ahmadian-Moghadam, H. 2012. Prediction of pepper (Capsicum annuum L.) leaf area using group method of data handling-type neural networks. International Journal of Agriculture Science, 2(11): 993-999.

3. Application of an Adaptive Neural-Based Fuzzy Inference System Model for Predicting Leaf Area

4. Modeling Pb (II) adsorption from aqueous solution by ostrich bone ash using adaptive neural-based fuzzy inference system

5. Estimation of Leaf Area Index and Foliage Area Index of Rice using an Indirect Gravimetric Method

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