Multivariate Analysis and Optimization of the Relationship between Soil Nutrients and Berry Quality of <i>Vitis vinifera</i> cv. Cabernet Franc Vineyards in the Eastern Foothills of the Helan Mountains, China

Abstract

The aim of this study is to explore the relationship between soil nutrients and berry quality for the wine grape Vitis vinifera cv. Cabernet Franc in the eastern foothills of the Helan Mountains, and subsequently to optimize soil nutrient conditions for optimal berry quality, thus providing guidance for vineyard soil management. Based on the basic data on soil nutrients and berry quality indicators, a partial least squares regression method was used to screen for major soil nutrient factors affecting the grape quality index. Then, the selected soil nutrient factors were taken as independent variables and the corresponding grape quality indicators were taken as dependent variables and a multilinear regression equation was formulated by the method of multivariate linear regression. Finally, the optimal solution for fruit quality and soil nutrients was solved using linear programming equations. The results showed that there was a lack of total nitrogen, organic matter, nitrate nitrogen, ammonium nitrogen, and available phosphorus in the soil nutrients, and an alkaline soil. There is a significant positive correlation between some soil nutrient indices, and there is also a multivariate linearity problem. Among all berry quality indices, titratable acid, tannin, and anthocyanin were negatively correlated with eleven and ten soil indices, respectively, while other berry quality indices were positively correlated with most soil nutrient indices. The optimal parameters for grape quality were determined using the method of linear programming equations, and the corresponding soil nutrient indicators content were defined.

Keywords

• <i>Vitis vinifera</i> cv. Cabernet Franc
• soil nutrients
• berry quality
• multivariate statistical analysis
• optimum proposal