巨峰葡萄果实生长模型数据

在果实生长发育进程中, 气候对果实的生长发育影响较大。通过监测：空气温度、空气湿度、土壤温度、土壤湿度、光照各指标，建立气象因子对巨峰葡萄果实生长的MLR模型。可以更科学地预测和掌握果实在不同时期的发育水平，研究结果可精确模拟和预测果实直径，对适时进行果树灾害防御、灌溉施肥、生长环境调控等提供重要参考和数据支持。1、在果实进入生长期，采用线性位移传感器、空气远程检测仪和土壤水分传感器连续自动监测空气温度、空气湿度、土壤温度、土壤湿度、光照。传感器与物联网监测系统连接，每5分钟自动记录果实直径(mm)。果园内物联网监测系统每5分钟可以采集以下环境气象要素:空气温度（℃）、空气湿度（%）、土壤温度1A（℃）、土壤湿度1A（%）、外置1 光照（Lux）。
2、对采集到的数据进行去除无效值、降噪、标准化处理。
建立MLR模型预测果实直径，通过最小二乘法在模型拟合过程中计算得出：果实直径预测值（mm)=0.0000025*空气温度（℃）+0.000002*空气湿度（%）+0.000003*土壤温度1A（℃）+0.000002*土壤湿度1A（%）+0.00000002*外置1 光照（Lux）+5分钟前的果实直径实际值（mm）

Climate exerts a substantial influence on fruit growth and development throughout their ontogenetic process. By monitoring key indicators including air temperature, air humidity, soil temperature, soil moisture, and illuminance, a Multiple Linear Regression (MLR) model was developed to predict the growth of Kyoho grape fruits using meteorological factors. This approach enables more scientific prediction and mastery of fruit developmental levels at different stages. The research results can accurately simulate and predict fruit diameter, providing important reference and data support for timely orchard disaster prevention, irrigation and fertilization, and growth environment regulation.
1. During the fruit growth period, linear displacement sensors, air remote detectors, and soil moisture sensors are used for continuous automatic monitoring of air temperature, air humidity, soil temperature, soil moisture, and illuminance. The sensors are connected to an Internet of Things (IoT) monitoring system, which automatically records fruit diameter (mm) every 5 minutes. The IoT monitoring system in the orchard collects the following environmental meteorological elements every 5 minutes: air temperature (℃), air humidity (%), soil temperature 1A (℃), soil moisture 1A (%), and external 1 illuminance (Lux).
2. Preprocessing operations including invalid value removal, noise reduction, and standardization are performed on the collected data.
An MLR model was established to predict fruit diameter. During the model fitting process, the predicted fruit diameter (mm) was calculated via the least squares method as follows:
Predicted fruit diameter (mm) = 0.0000025 × air temperature (℃) + 0.000002 × air humidity (%) + 0.000003 × soil temperature 1A (℃) + 0.000002 × soil moisture 1A (%) + 0.00000002 × external 1 illuminance (Lux) + actual fruit diameter value (mm) 5 minutes prior

搜集汇总

背景与挑战

背景概述

该数据集记录了巨峰葡萄果实生长过程中的环境监测数据，包括空气温度、湿度、土壤温度、湿度、光照等指标，以及果实直径的实际值和预测值，数据每5分钟更新一次，总规模为5736条。它通过多元线性回归模型分析气象因子对果实生长的影响，旨在科学预测果实发育水平，为果树灾害防御、灌溉施肥和生长环境调控提供数据支持，适用于精准农业和智能果园管理场景。