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.数据集说明 1. 植物胁迫声音数据集（CSV格式）：plant_stress_sound_dataset.csv 该文件存储了不同胁迫条件下植物发出声音的录音元数据。数据集中每一行对应一条独立的声音录音，包含植物物种、胁迫类型、环境条件以及用于实时监测的其他相关元数据信息，可用于为录音打上标签，并将录制声音与植物生理状态及环境背景建立关联。 字段说明： • Audio_File：植物声音录音的文件名（示例：plant_drought_01.wav）。 • Stress_Type：植物所受胁迫的类型（示例：干旱、营养缺乏、机械损伤）。 • Duration (s)：声音录音的时长，单位为秒。 • Plant_Species：被监测植物的物种（示例：番茄、玉米、小麦）。 • Temperature (°C)：录音期间的环境温度。 • Humidity (%)：环境相对湿度。 • Soil_Moisture (%)：土壤含水率，该指标对分析干旱胁迫至关重要。 • Timestamp：录音生成的确切时间与日期。 • Location：录音场景描述，包括受控环境（如温室）或开放农田。 该数据集可支持深度学习模型基于植物发出的声音及环境因素，学习并分类不同的植物胁迫类型。 2. 音频文件夹：plant_sounds/ plant_sounds文件夹存储了植物发出声音的原始录音文件，所有文件均为.wav或.mp3格式，与plant_stress_sound_dataset.csv中的条目一一对应。录音文件依据胁迫类型命名（示例：plant_drought_01.wav、plant_nutrient_02.wav），可捕获与干旱、营养缺乏、机械损伤等不同植物胁迫源相关的空气传播声音信号。 示例文件： • plant_drought_01.wav：遭受干旱胁迫的植物录音。 • plant_nutrient_02.wav：出现营养缺乏症状的植物录音。 • plant_damage_03.wav：存在机械损伤的植物录音。 这些音频文件可作为深度学习模型的输入，用于分析声音模式并检测植物的胁迫状态。