阳光十三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，建立气象因子对阳光十三葡萄果实生长的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，同一品种葡萄，随机选取一株，选择生长在外部中间位置的葡萄果实进行测量，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)=0.0000035*空气温度（℃）+0.0000035*空气湿度（%）+0.000003*土壤温度1A（℃）+0.000002*土壤湿度1A（%）+0.000000045*外置1 光照（Lux）+5分钟前的果实直径实际值（mm）

Climate plays a substantial role in fruit growth and development across their entire developmental cycle. By monitoring key environmental indicators including air temperature, air humidity, soil temperature, soil moisture, and light intensity, a multiple linear regression (MLR) model was developed to quantify the effects of meteorological factors on fruit growth of Sunshine No.13 grapes. This framework enables more scientific prediction and assessment of fruit development status at different growth stages. The study results can accurately simulate and predict fruit diameter, providing vital references and data support for timely orchard disaster prevention, irrigation and fertilization, and growth environment regulation.

1. During the fruit growth phase, linear displacement sensors, remote air monitors, and soil moisture sensors are deployed for continuous automated monitoring of air temperature, air humidity, soil temperature, soil moisture, and light intensity. These sensors are connected to an Internet of Things (IoT) monitoring system. For grapevines of the same variety, one vine is randomly selected, and grape fruits located at the external middle position of the vine are chosen for measurement. The fruit diameter (mm) is automatically recorded every 5 minutes. The IoT monitoring system in the orchard collects the following environmental meteorological parameters every 5 minutes: air temperature (℃), air humidity (%), soil temperature 1A (℃), soil moisture 1A (%), and external 1 light intensity (Lux).

2. The collected raw data undergo preprocessing including invalid value removal, noise reduction, and standardization. An MLR model is established to predict fruit diameter, with the model coefficients calculated via the least squares method during the fitting process:
Predicted fruit diameter (mm) = 0.0000035 × air temperature (℃) + 0.0000035 × air humidity (%) + 0.000003 × soil temperature 1A (℃) + 0.000002 × soil moisture 1A (%) + 0.000000045 × external 1 light intensity (Lux) + actual fruit diameter (mm) measured 5 minutes prior.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于阳光十三葡萄果实的生长过程，通过每5分钟自动采集空气温度、湿度、土壤温度、湿度、光照等环境指标，以及果实直径的实际值和预测值，共包含1639条结构化数据。它基于多元线性回归模型建立气象因子与果实生长之间的关联，旨在科学预测果实直径变化，为果园的灾害防御、灌溉施肥和环境调控提供精准的数据支持。