Imran Muhammad, Ali Jabbar, Ali Yasir, Kiran Quanita, Malik Mehar Ali, Aqib Muhammad
Department of Electrical Engineering, Prince Mohammad Bin Fahd University, P.O. Box 1664, Al Khobar 31952, Kingdom of Saudi Arabia.
Department of Basic Sciences and Humanities, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, P.O. Box 45200, Main Peshawar Rd, Rawalpindi 45200, Pakistan.
ACS Omega. 2025 Jul 3;10(27):29180-29193. doi: 10.1021/acsomega.5c01839. eCollection 2025 Jul 15.
Fusarium wilt is a soil-borne disease that leads to wilting, yellowing, and sometimes death of various plant species. This article examines the correlations between physicochemical properties and molecular invariants of the chemical structures of molecular biocontrol agents used to mitigate Fusarium wilt, a plant disease. The study considers effective agents like fungicides (thiophanate-methyl, azoxystrobin, trifloxystrobin, fludioxonil, and metalaxyl), soil fumigants (chloropicrin, metam sodium, and 1,3-dichloropropene), and molecular biocontrol agents (methionine and adenosine). This is the first review of QSPR studies on plant diseases in the literature. For the chemical structures of these molecular biocontrol agents, we have calculated M-polynomials of various molecular invariants, including the Zagreb-type indices, atom-bond connectivity index, harmonic index, Sombor index, forgotten index, and symmetric division degree index. The relationships identified through regression analysis provide insights into their effectiveness and optimization. Our findings highlight the best regression coefficients, which have the lowest RMSE and the maximum -statistics values for significant correlations. Using these regression coefficients, we can predict the behavior of bioagents.
枯萎病是一种土传病害,会导致多种植物物种枯萎、发黄,有时甚至死亡。本文研究了用于减轻植物病害枯萎病的分子生物防治剂的化学结构的物理化学性质与分子不变量之间的相关性。该研究考虑了杀菌剂(甲基托布津、嘧菌酯、肟菌酯、咯菌腈和甲霜灵)、土壤熏蒸剂(氯化苦、威百亩和1,3 - 二氯丙烯)以及分子生物防治剂(蛋氨酸和腺苷)等有效药剂。这是文献中关于植物病害定量构效关系(QSPR)研究的首次综述。对于这些分子生物防治剂的化学结构,我们计算了各种分子不变量的M - 多项式,包括 Zagreb 型指数、原子键连接性指数、调和指数、Sombor 指数、遗忘指数和对称分裂度指数。通过回归分析确定的关系为它们的有效性和优化提供了见解。我们的研究结果突出了最佳回归系数,这些系数具有最低的均方根误差(RMSE)和显著相关性的最大统计值。利用这些回归系数,我们可以预测生物制剂的行为。