河南省商丘市民权县胡萝卜种植环境分析数据

采集胡萝卜种植的土壤湿温度、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胡萝卜生长的具体影响。如确定适宜的土壤温度和湿度范围，以保证胡萝卜种子顺利发芽和根系的良好发育。明确合适的光照强度和时长，促使胡萝卜进行充分的光合作用，积累丰富的营养物质。把握恰当的二氧化碳浓度，助力胡萝卜提高光合效率，增强生长活力。同时，监测适宜的空气温湿度，为胡萝卜生长创造适宜的大气环境。利用这些数据构建胡萝卜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胡萝卜具有更高的胡萝卜素含量、更优的口感和更好的形状等，为显著提升胡萝卜品质奠定基础。基于数据驱动的方式，为胡萝卜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，为胡萝卜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胡萝卜种植中，形成多维度细粒度的感知与控制模式，有力推动胡萝卜种植产业朝着科学、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、土壤温湿度传感器、光照传感器、二氧化碳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、土壤温湿度、光照、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（如空气温湿度、土壤温湿度、光照、二氧化碳等），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，以光照为例，其权重为3，理想值设定为3000，容差范围为±500，扣分计算如下：光照扣分=3×|8-3000|/500=3×5.984=17.952。根据这些评分生成具体的环境优化方案。

This dataset collects multi-dimensional environmental data including soil temperature and humidity, light intensity, carbon dioxide concentration, and air temperature and humidity during carrot cultivation, aiming to comprehensively evaluate the specific impacts of different environmental conditions on carrot growth. Specifically, it seeks to determine the optimal soil temperature and humidity ranges for smooth carrot seed germination and robust root development; define appropriate light intensity and duration to enable sufficient photosynthesis and accumulation of abundant nutrients; control appropriate carbon dioxide concentrations to improve photosynthetic efficiency and enhance growth vitality; and monitor suitable air temperature and humidity to create a favorable atmospheric environment for carrot growth. Based on these collected data, a deep neural network model correlating carrot quality and environmental parameters is constructed to deeply explore which environmental condition combinations can yield carrots with higher carotene content, better taste, and more desirable shape, laying a foundation for significantly improving carrot quality. This data-driven approach provides effective support for intelligent regulation of carrot cultivation environments: automatically adjusting irrigation volume, ventilation intensity, and shading degree based on real-time data to create optimal growth conditions, thereby improving cultivation efficiency and yield. The optimized environmental regulation experience is then promoted and applied to carrot cultivation in different regions, forming a multi-dimensional fine-grained perception and control mode, which effectively promotes the carrot cultivation industry to develop toward a scientific, efficient, and transplantable model, and comprehensively enhances the competitiveness of the entire industry.

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

2. Algorithm Rules:
The system adopts an environmental parameter scoring algorithm to score the collected environmental data. Based on the ideal conditions for crop growth (such as air temperature and humidity, soil temperature and humidity, light intensity, and carbon dioxide concentration), the scoring 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 over 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 cultivation 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 crop's tolerance to different environmental changes. The more the environmental parameters deviate from the ideal values, the greater the score deduction. Taking light as an example: its weight is set to 3, the ideal value is 3000, and the tolerance range is ±500. The score deduction for light is calculated as:
Light Score Deduction = 3 × |8 - 3000| / 500 = 3 × 5.984 = 17.952
Specific environmental optimization schemes are generated based on these scores.

搜集汇总

数据集介绍

特点

河南省商丘市民权县胡萝卜种植环境分析数据包含793条多维环境监测记录，每日更新，通过物联网采集和算法评分优化种植条件，用于提升胡萝卜产量和品质。