A novel dataset for wireless soil monitoring of a strawberry harvest and respective evaluation of physicochemical qualities

Abstract

The paper presents a complete collection of data and its preliminary statistical analysis obtained from the first phase of a large soil study on how to improve strawberry production and achieve sustainable and high-quality harvests through sensor-assisted real-time field monitoring. Six real-time loggers were placed in an operational commercial strawberry farm in Central Florida for the entirety of a harvest season from soil preparation to planting to harvesting. Along with temporally high-resolution soil sensory measurements including water content, electrical conductivity, and temperature, strawberries were harvested from each of the six locations on three separate occasions for their objective physicochemical characteristics to be monitored and recorded in a food chemistry lab. The primary goal of this paper is to introduce the dataset to the food science and engineering research community and present the results of its preliminary statistical analysis in identifying which factors correlate with one another. Based on the findings of this paper, while there exists a weak correlation between the quality of the harvest and the water content of the soil immediately preceding it, there were several cases where statistically significant differences exist between the soil sensory measurements from different locations which did not replicate the same differences in their corresponding harvest qualities.

Keywords

• Soil monitoring
• Smart farming
• IoT
• Statistical analysis
• Physicochemical characteristic
• Strawberry