山东省菏泽市郓城县玉米种植环境分析数据

采集玉米种植的土壤湿温度、光照强度、二氧化碳浓度、空气温湿度等数据，全面评估不同环境条件对玉米生长的具体影响。如确定适宜的土壤温度和湿度范围以确保玉米种子顺利萌发和根系健壮生长，明确合适的光照强度和时长以促进玉米的光合作用，提高有机物积累。同时，把握恰当的二氧化碳浓度以增强玉米的光合效能，监测适宜的空气温湿度为玉米生长营造舒适的大气环境。利用这些数据构建玉米品质与环境参数关联的深度网络模型，深入探索何种环境条件组合可以使玉米具有更高的淀粉含量、更优的籽粒品质和更好的抗倒伏能力等，为显著提升玉米品质奠定基础。基于数据驱动的方式，为玉米种植环境的智能调控提供有效的支持，依据实时数据自动调整灌溉量、通风强度以及遮阳程度等，为玉米创造适宜的生长环境，提高种植效率和产量。将优化后的环境调控经验推广应用至不同地区的玉米种植中，形成多维度细粒度的感知与控制模式，有力推动玉米种植产业朝着科学、高效、模式可移植的方向发展，全面提升整个产业的竞争力。1.数据采集：本系统通过空气湿温度传感器、光照传感器、土壤温湿度传感器等物联网设备，结合4G/5G、Wi-Fi与有线网络，实时采集种植环境中的空气湿温度、光照、土壤湿温度、二氧化碳等多维数据。 2.算法规则：系统采用环境参数评分算法，对环境数据进行评分。基于作物生长理想条件（如温度、湿度、光照等），并通过以下公式计算：环境参数评分=100-Σ(w_i×|当前值_i-理想值_i|/容差_i)，其中，Σ表示对所有参数的累加，w_i是第i个参数的权重。当前值_i是第i个参数的实际测量值，理想值_i是第i个参数的理想值。容差_i是第i个参数的允许波动范围。权重、理想值和容差范围设定基于历史数据分析以及实际种植经验的确定。对作物生长影响较大的参数获得较高的权重。容差范围则考虑到环境因素的波动性，针对作物对不同环境变化的耐受性设定进行适当设定，环境参数偏离理想值越多，扣分越大，以土壤湿度为例，其权重为2.5，理想值设定为80%RH，容差范围为±5%RH，扣分计算如下：土壤湿度扣分=2.5×|45-80|/5=2.5×7=17.5。根据这些评分生成具体的环境优化方案。

This dataset collects multi-dimensional environmental data for corn planting, including soil temperature and humidity, light intensity, carbon dioxide concentration and air temperature and humidity, aiming to comprehensively evaluate the specific impacts of different environmental conditions on corn growth. Specifically, it aims to determine the suitable ranges of soil temperature and humidity to ensure smooth germination of corn seeds and robust root growth; clarify appropriate light intensity and duration to promote corn photosynthesis and enhance organic matter accumulation; grasp proper carbon dioxide concentration to strengthen the photosynthetic efficiency of corn; and monitor suitable air temperature and humidity to create a favorable atmospheric environment for corn growth. Using these collected data, a deep network model correlating corn quality with environmental parameters will be constructed to deeply explore which combination of environmental conditions can endow corn with higher starch content, better grain quality and stronger lodging resistance, laying a solid foundation for significantly improving corn quality. Adopting a data-driven approach, this work provides effective support for intelligent regulation of corn planting environments, automatically adjusting irrigation volume, ventilation intensity and shading degree based on real-time data to create optimal growth conditions for corn, thereby improving planting efficiency and yield. The optimized environmental regulation experience will be promoted to corn planting in different regions, forming a multi-dimensional and fine-grained perception and control mode, effectively promoting the corn planting industry towards a scientific, efficient and transplantable development direction, and comprehensively enhancing the competitiveness of the entire industry.

1. Data Collection: This system collects real-time multi-dimensional data from the planting environment, including air temperature and humidity, light, soil temperature and humidity and carbon dioxide, via IoT devices such as air temperature and humidity sensors, light sensors and soil temperature and humidity sensors, combined with 4G/5G, Wi-Fi and wired networks.

2. Algorithm Rules: The system applies an environmental parameter scoring algorithm to evaluate the collected environmental data. Based on the ideal growth conditions for crops (such as temperature, humidity, light, etc.), the score is calculated using the following formula:
Environmental Parameter Score = 100 - Σ(w_i × |Current Value_i - Ideal Value_i| / Tolerance_i)
Where Σ represents the summation of all parameters, w_i is the weight of the i-th parameter, Current Value_i is the actual measured value of the i-th parameter, Ideal Value_i is the ideal value of the i-th parameter, and Tolerance_i is the allowable fluctuation range of the i-th parameter. The weights, ideal values and tolerance ranges are determined based on historical data analysis and actual planting experience. Parameters with greater impacts on crop growth are assigned higher weights. The tolerance ranges are appropriately set considering the volatility of environmental factors and the tolerance of crops to different environmental changes: the more the environmental parameters deviate from the ideal values, the greater the score deduction. Taking soil moisture as an example, its weight is set to 2.5, the ideal value is 80% RH, and the tolerance range is ±5% RH. The score deduction for soil moisture is calculated as:
Soil Moisture Score Deduction = 2.5 × |45 - 80| / 5 = 2.5 × 7 = 17.5
Specific environmental optimization schemes are then generated based on the calculated scores.

搜集汇总

数据集介绍

特点

该数据集包含518条山东省菏泽市郓城县玉米种植环境数据，每日更新，涵盖空气温湿度、光照、土壤温湿度、二氧化碳浓度等多维环境参数，用于优化玉米种植环境，提高产量和品质。