A decision-supporting system for vineyard management: a multi-temporal approach with remote and proximal sensing

IF 5.4 2区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Precision Agriculture Pub Date : 2024-08-20 DOI:10.1007/s11119-024-10177-2

A. Deidda, A. Sassu, L. Mercenaro, G. Nieddu, C. Fadda, P. F. Deiana, F. Gambella

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Abstract

Purpose

Site-specific field management operations represent one of the fundamental principles of precision viticulture. The purpose of the research is to observe and analyse the evolution of a vineyard over three consecutive years to understand which factors most significantly influence the quality of the vineyard’s production.

Methods

The research involved technologically advanced tools for crop monitoring, such as remote and proximal sensors for vegetation surveys. In association, grape quality analyses were performed through laboratory analysis, constructing geostatistical interpolation maps and matrix correlation tables.

Results

Both remote and proximal sensing instruments demonstrated their ability to effectively estimate the spatial distribution of vegetative and quality characteristics within the vineyard. Information obtained from GNDVI and CHM proved to be valuable and high-performance tools for assessing field variability. The differentiated plant management resulted in uniform production quality characteristics, a change evident through the monitoring techniques.

Conclusion

The research highlights the effectiveness of using advanced technological instruments for crop monitoring and their importance in achieving uniformity in production quality characteristics through differentiated plant management. From the results obtained, it was possible to observe how differentiated plant management led to a uniformity of production quality characteristics and how the monitoring techniques can observe their evolution. This result represents a positive accomplishment in field management during the three monitoring years, responding to the principles and objectives of precision agriculture.

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葡萄园管理决策支持系统：利用遥感和近距离传感的多时空方法

目的因地制宜的田间管理操作是精准葡萄栽培的基本原则之一。这项研究的目的是观察和分析葡萄园连续三年的变化情况，以了解哪些因素对葡萄园的产量质量影响最大。研究方法这项研究采用了技术先进的作物监测工具，如用于植被调查的远程和近距离传感器。结果两种遥感和近距离传感仪器都证明了它们能够有效估计葡萄园内植被和质量特征的空间分布。从 GNDVI 和 CHM 中获得的信息被证明是评估田间变异性的有价值的高性能工具。研究强调了使用先进技术手段进行作物监测的有效性，以及这些手段在通过差异化植物管理实现生产质量特征统一方面的重要性。从获得的结果中，我们可以观察到差异化植物管理是如何实现生产质量特征的统一性的，以及监测技术是如何观察到它们的变化的。这一结果表明，在三个监测年份中，田间管理取得了积极成果，符合精准农业的原则和目标。

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来源期刊

Precision Agriculture 农林科学-农业综合

CiteScore

12.30

自引率

8.10%

发文量

103

审稿时长

>24 weeks

期刊介绍： Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.