PROSPECTS FOR THE DEVELOPMENT OF DIGITAL MODELS OF GRAPE VARIETIES FOR PREDICTING THE EFFECTIVENESS OF TECHNOLOGICAL PROCESSES

Margarita Igorevna Ivanova, V. Ivanchenko, Dmitry Valerievich Potanin
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Abstract

At the present stage, with an increase in the volume of consumption of grape-growing products, it is necessary to carry out a monitoring forecast of the possibility of its production for each individual variety or scion-rootstock combination, depending on edaphoclimatic conditions and cultivation technology. This is possible only if predictive models of the behavior of the grape variety or its scion-rootstock combination are developed in the grafted culture in various ecoagrobiocenoses. The purpose of the study was to consider methodological approaches to the creation of mathematical models for predicting the behavior of an individual variety or groups of grape varieties, depending on the abiotic and agrotechnological characteristics of cultivation. To achieve this goal, a previously created database was used, obtained during an experiment conducted on the basis of uterine plantations and an open grape school of the Institute "Agrotechnological Academy" of the V.I. Vernadsky Crimean Federal University, collected in the period from 2018 to 2021 and subjected to multidimensional regression analysis using the developed program. The total number of items included in the database is 1,860. (31 parameters). The research proved the possibility of developing regression models for predicting productivity using nonparametric digital introduction of varieties, as well as environmental factors. It is established that regression models characterizing the quality of the vine, taking into account varietal characteristics and weather conditions, can vary depending on a particular variety. Thus, a similar model for the Cabernet Sauvignon variety is fundamental with a multiple correlation coefficient of R = 0.9866, and for the Syrah variety it is logarithmic at R= 1.0000. Promising possibilities and ways of developing digital (mathematical) models characterizing individual varieties or groups of varieties by origin according to their productivity, depending on edaphoclimatic conditions, production technology, as well as quality parameters of manufactured products are considered
开发用于预测技术工艺有效性的葡萄品种数字模型的前景
现阶段,随着葡萄种植产品消费量的增加,有必要根据气候条件和栽培技术,对每个品种或接穗-砧木组合的生产可能性进行监测预测。只有开发出葡萄品种或接穗-砧木组合在不同生态环境下嫁接栽培的行为预测模型,才能做到这一点。本研究的目的是根据栽培的非生物和农业技术特点,考虑创建数学模型的方法,以预测单个品种或葡萄品种群的行为。为了实现这一目标,我们使用了之前创建的数据库,该数据库是在В.И. 维纳德斯基克里米亚联邦大学 "农业技术学院 "研究所的子宫种植园和开放式葡萄学校的基础上进行试验期间获得的,收集时间为2018年至2021年,并使用开发的程序进行了多维回归分析。数据库中共包含 1 860 个项目(31 个参数)。研究证明了利用非参数数字引入品种以及环境因素建立预测生产力回归模型的可能性。已确定的是,考虑到品种特性和天气条件,表征葡萄质量的回归模型会因特定品种而异。因此,赤霞珠品种的类似模型是基本的,多重相关系数为 R= 0.9866,而西拉品种的类似模型是对数的,R= 1.0000。根据不同的气候条件、生产技术以及制成品的质量参数,考虑开发数字(数学)模型的可能性和方法,按原产地描述单个品种或品种群的生产力特征。
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