Audio signals from stressed plants

Dataset Description
1. Plant Stress Sound Dataset (CSV Format): plant_stress_sound_dataset.csv
The plant_stress_sound_dataset.csv contains metadata for audio recordings of plant-emitted sounds under various stress conditions. Each row in the dataset represents an individual sound recording and includes details about the plant species, type of stress, environmental conditions, and additional relevant metadata for real-time monitoring. The dataset helps in labeling and correlating the recorded sound with the plant’s physiological state and environmental context.
Columns:
• Audio_File: The filename of the recorded plant sound (e.g., plant_drought_01.wav).
• Stress_Type: The type of stress experienced by the plant (e.g., Drought, Nutrient Deficiency, Mechanical Damage).
• Duration (s): The duration of the sound recording in seconds.
• Plant_Species: The species of plant being monitored (e.g., Tomato, Corn, Wheat).
• Temperature (°C): The environmental temperature during the recording.
• Humidity (%): The relative humidity in the environment.
• Soil_Moisture (%): The percentage of soil moisture, which is critical for understanding drought stress.
• Timestamp: The exact time and date when the recording was made.
• Location: Describes whether the sound was recorded in a controlled environment (e.g., Greenhouse) or an open agricultural field.
This dataset allows deep learning models to learn and classify different stress conditions based on the plant’s emitted sound and environmental factors.
2. Audio Folder: plant_sounds/
The plant_sounds folder contains the actual audio recordings of plant-emitted sounds. Each file is a .wav or .mp3 format, corresponding to entries in the plant_stress_sound_dataset.csv file. The recordings are labeled based on the type of stress (e.g., plant_drought_01.wav, plant_nutrient_02.wav), and they capture airborne sound emissions linked to different plant stressors like drought, nutrient deficiency, or mechanical damage.
Example Files:
• plant_drought_01.wav: A recording of a plant experiencing drought stress.
• plant_nutrient_02.wav: A recording of a plant suffering from nutrient deficiency.
• plant_damage_03.wav: A recording of a plant with mechanical damage.
These audio files serve as the input to the deep learning model for analyzing sound patterns and detecting stress in plants.

数据集描述
1. 植物应激声音数据集（CSV格式）：plant_stress_sound_dataset.csv
该数据集包含植物在不同应激条件下所发出声音的元数据。数据集中每一行代表一个独立的声音记录，并包含有关植物种类、应激类型、环境条件及其他与实时监控相关的相关元数据。该数据集有助于对记录的声音进行标记，并关联植物生理状态和环境背景。
列名：
• 音频文件：记录的植物声音的文件名（例如，plant_drought_01.wav）。
• 应激类型：植物所经历的应激类型（例如，干旱、养分缺乏、机械损伤）。
• 持续时间（秒）：声音记录的持续时间，单位为秒。
• 植物种类：被监测的植物种类（例如，番茄、玉米、小麦）。
• 温度（°C）：记录期间的环境温度。
• 湿度（%）：环境中的相对湿度。
• 土壤湿度（%）：土壤湿度百分比，对于理解干旱应激至关重要。
• 时间戳：记录的确切时间和日期。
• 位置：描述声音是在控制环境（例如，温室）还是开放农业田地中记录的。
此数据集允许深度学习模型通过植物发出的声音和环境因素来学习和分类不同的应激条件。
2. 音频文件夹：plant_sounds/
plant_sounds 文件夹包含植物发出声音的实际音频记录。每个文件均为 .wav 或 .mp3 格式，与 plant_stress_sound_dataset.csv 文件中的条目相对应。这些记录根据应激类型进行标记（例如，plant_drought_01.wav、plant_nutrient_02.wav），并捕捉与干旱、养分缺乏或机械损伤等不同植物应激因子相关的空中声音排放。
示例文件：
• plant_drought_01.wav：记录植物经历干旱应激的声音。
• plant_nutrient_02.wav：记录植物遭受养分缺乏的声音。
• plant_damage_03.wav：记录植物机械损伤的声音。
这些音频文件作为深度学习模型的输入，用于分析声音模式并检测植物中的应激状况。