Statistics on multiple linear regression (MLR), stepwise regression (SR), principal component regression (PCR), ordinary least squares regression (OLSR), partial least squares regression, and multilayer perceptron-genetic algorithm (MLPNN-GA) for modeling leaf quality responding to blue mold severity, chlorophyll, nitrogen, sugar, nicotine, chloride, and potassium content in four tobacco cultivars “Bergerac, Bell, Burly, and Basma”.

<p>Statistics on multiple linear regression (MLR), stepwise regression (SR), principal component regression (PCR), ordinary least squares regression (OLSR), partial least squares regression, and multilayer perceptron-genetic algorithm (MLPNN-GA) for modeling leaf quality responding to blue mol...

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Bibliographic Details
Main Author:	Mohammad Reza Najafi (9288989) (author)
Other Authors:	Mohammad Ali Aghajani (22386118) (author), Naser Safaie (6908615) (author), Siamak Rahmanpour (22386121) (author)
Published:	2025
Subjects:	Biotechnology Ecology Developmental Biology Science Policy Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified two growing seasons practical mathematical tool nicotiana tabacum </ factors would open blue mold severity actual data validated principal component regression multiple linear regression improving farmer income highest leaf quality div >< p 2 </ sup nt ), chloride n ), sugar bms ), chlorophyll ga models showed basma leaf quality leaf quality regression models stepwise regression internal quality income countries dw ), ), nicotine ga models tobacco leaves tobacco (< superior efficiency smokeless tobacco l .) including cigars highly related green weight global industry genetic algorithm ga vs developed mlnnp close match cl ), cigarette products chewing tobacco chemical components 94 vs 00 vs
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