交互式连续模型序列无损估计番茄果实特性

M. Kılıç, M. K. Bozokalfa
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引用次数: 0

摘要

果实形状是一个重要的品质参数,果实直径、高度、重量、截面积、体积等变量是影响果实形状特征的组成部分。特别是,这些特性是工业应用中最重要的参数,用于水果分级,确定最佳包装条件,提供最合适的运输设施,以及优化作物生产策略。在这项调查中,设计了数学模型,可以在收获前通过非破坏性方法在田间估计水果的横截面积,重量和体积。采用数据分析方法和交互式连续计算系列对Bandita F1番茄品种进行建模。果实横截面积、重量和体积的实测值与估计值的相关系数分别为0.9672、0.9809和0.9684。此外,所提出的模型对截面积、重量和体积的估计准确率分别为97.12%、95.40%和95.37%。此外,根据NS、RSR和PBIAS的三种分析,模型的性能和效度都处于“非常好”的类别。这些结果表明,所提出的模型给出了高准确率的结果
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Non-destructive estimation of tomato fruit properties by interactive consecutive model series
Fruit shape is an important quality parameter, and such variables as fruit diameter, height, weight, cross-sectional area and volume are components affecting this feature. In particular, these properties are the most important parameters in industrial applications for fruit grading, in determining the conditions of optimum packing, in providing the most suitable transportation facilities, and in optimizing crop production strategies. In this investigation, mathematical models were devised which enable estimation of the cross-sectional area, weight and volume of the fruit by a non-destructive method in the field before harvest. The modelling process was carried out by means of data analysis approaches and interactive consecutive calculation series for the Bandita F1 tomato cultivar. The correlation between the measured and estimated cross-sectional area, weight and volume of the fruit were 0.9672, 0.9809 and 0.9684, respectively. Apart from this, the accuracy rates of the models proposed for the estimation of the cross-sectional area, weight and volume are 97.12%, 95.40% and 95.37% respectively. In addition, the performance and validity of the models are in the “very good” category according to the all three analyses of NS, RSR and PBIAS. These results indicated that the models proposed gave high rates of accurate results
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