Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat

Ali, Yasir; Raza, Ahmed; Iqbal, Sidra; Khan, Azhar Abbas; Aatif, Hafiz Muhammad; Hassan, Zeshan; Hanif, Ch. Muhammad Shahid; Ali, Hayssam M.; Mosa, Walid F. A.; Mubeen, Iqra; Sas-Paszt, Lidia

doi:10.3390/su142113893

Open AccessArticle

Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat

by

Yasir Ali

¹

,

Ahmed Raza

^2,3,*

,

Sidra Iqbal

⁴,

Azhar Abbas Khan

¹

,

Hafiz Muhammad Aatif

¹,

Zeshan Hassan

¹

,

Ch. Muhammad Shahid Hanif

¹,

Hayssam M. Ali

⁵

,

Walid F. A. Mosa

⁶,

Iqra Mubeen

⁷ and

Lidia Sas-Paszt

⁸

¹

College of Agriculture, Bahauddin Zakariya University Multan, Bahadur Sub-Campus, Layyah 31200, Pakistan

²

Department of Biology, Institute of Pure and Applied Zoology, University of Okara, Okara 56300, Pakistan

³

Department of Plant Pathology, University of Agriculture, Faisalabad, Depalpur Campus, Okara 56300, Pakistan

⁴

Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Depalpur Campus, Okara 56300, Pakistan

⁵

Botany and Microbiology Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

⁶

Plant Production Department (Horticulture-Pomology), Faculty of Agriculture, Saba Basha, Alexandria University, Alexandria 21531, Egypt

⁷

Key Lab of Integrated Crop Disease and Pest Management, College of Plant Health and Medicine, Qingdao Agricultural University, Qingdao 266109, China

⁸

The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland

^*

Author to whom correspondence should be addressed.

Sustainability 2022, 14(21), 13893; https://doi.org/10.3390/su142113893

Submission received: 28 July 2022 / Revised: 5 October 2022 / Accepted: 15 October 2022 / Published: 26 October 2022

Download

Browse Figures

Review Reports Versions Notes

Abstract

Leaf rust is a devastating disease in wheat crop. The disease forecasting models can facilitate the economic and effective use of fungicides and assist in limiting crop yield losses. In this study, six wheat cultivars were screened against leaf rust at two locations, during three consecutive growing seasons. Subsequently, the stepwise regression analysis was employed to analyze the correlation of six epidemiological variables (minimum temperature, maximum temperature, minimum relative humidity, maximum relative humidity, rainfall and wind speed) with disease severity and yield loss (%). Disease predictive models were developed for each cultivar for final leaf rust severity and yield loss prediction. Principally, all epidemiological variables indicated a positive association with leaf rust severity and yield loss (%) except minimum relative humidity. The effectiveness of disease predictive models was estimated using coefficient of determination (R²) values for all models. Then, these predictive models were validated to forecast disease severity and yield loss at another location in Faisalabad. The R² values of all disease predictive models for each of the tested cultivars were high, evincing that our regression models could be effectively employed to predict leaf rust disease severity and anticipated yield loss. The validation results explained 99% variability, suggesting a highly accurate prediction of the two variables (leaf rust severity and yield loss). The models developed in this research can be used by wheat farmers to forecast disease epidemics and to make disease management decisions accordingly.

Keywords: leaf rust; regression model; Triticum astivum L.; yield loss; disease forecast

Share and Cite

MDPI and ACS Style

Ali, Y.; Raza, A.; Iqbal, S.; Khan, A.A.; Aatif, H.M.; Hassan, Z.; Hanif, C.M.S.; Ali, H.M.; Mosa, W.F.A.; Mubeen, I.; et al. Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat. Sustainability 2022, 14, 13893. https://doi.org/10.3390/su142113893

AMA Style

Ali Y, Raza A, Iqbal S, Khan AA, Aatif HM, Hassan Z, Hanif CMS, Ali HM, Mosa WFA, Mubeen I, et al. Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat. Sustainability. 2022; 14(21):13893. https://doi.org/10.3390/su142113893

Chicago/Turabian Style

Ali, Yasir, Ahmed Raza, Sidra Iqbal, Azhar Abbas Khan, Hafiz Muhammad Aatif, Zeshan Hassan, Ch. Muhammad Shahid Hanif, Hayssam M. Ali, Walid F. A. Mosa, Iqra Mubeen, and et al. 2022. "Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat" Sustainability 14, no. 21: 13893. https://doi.org/10.3390/su142113893

APA Style

Ali, Y., Raza, A., Iqbal, S., Khan, A. A., Aatif, H. M., Hassan, Z., Hanif, C. M. S., Ali, H. M., Mosa, W. F. A., Mubeen, I., & Sas-Paszt, L. (2022). Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat. Sustainability, 14(21), 13893. https://doi.org/10.3390/su142113893

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu

Stepwise Regression Models-Based Prediction for Leaf Rust Severity and Yield Loss in Wheat

Abstract

Share and Cite

Article Metrics

Article Access Statistics

Further Information

Guidelines

MDPI Initiatives

Follow MDPI