Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071 València, Spain.
Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E-46001 València, Spain.
Molecules. 2014 Jun 5;19(6):7388-414. doi: 10.3390/molecules19067388.
Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.
葡萄酒中的农药残留通过液相色谱-串联质谱法进行分析。保留时间通过结构-性质关系进行建模。生物塑料的进化是一种进化视角，结合了获得的特征和进化的不确定性-形态决定-自然选择原则的影响；其在设计协调指数中的应用几乎没有提高相关性。分形维数和分配系数可区分农药。分类算法基于信息熵及其产物。农药允许通过非平面性、O、S、N 和 Cl 原子以及环的数量来进行结构分类；不同的行为取决于环的数量。该方法的新颖之处在于，结构参数与保留时间有关。分类算法基于信息熵。当将程序应用于中等大小的集合时，过多的结果似乎与数据遭受组合爆炸兼容。然而，等分布猜想选择了来自分类的层次树之间的分类标准。信息熵允许对与主成分分析一致的化合物进行分类。周期性分类表明，同一组中的农药具有相似的性质；在同一周期的农药，相似性最大。分类的优势在于可以预测未包含在分类中的分子的保留时间。分类扩展到苯磺酰脲类，应用将是预测它们的保留时间。
