Speaker
Description
As for the certification of agricultural products, the quality of agricultural products is guaranteed through various certifications according to the situation of each country around the world. However, it is not well known about the growth environment (e.g., weather, soil condition, fertilizer use etc.) and the expected quality for the entire cycle of the cultivation environment. In this study, we are developing a monitoring system for the entire process of evaluation of agricultural products (fruits and vegetables), cultivation (growth) environment, and environmental impact through analysis of air quality, soil environment, weather information, and various big data provided by the country in the relevant farmland. It can be evaluated and optimized for quality improvement and cost-benefit by providing producers with objective analysis and monitoring product results. In addition, by providing a grade for the cultivation environment and quality of agricultural products to consumers, they can intuitively consume. The main contents of this study are as follows.
1) Development of an environmental evaluation model through the development of evaluation items and indicators for agricultural cultivation environment and quality
2) Data collection and analysis algorithm development through integrated IoT environment sensor and monitoring system development
- Soil moisture content (humidity), cultivation temperature, soil pH (acidity), soil nutrient content (N, P, K content: fertility), carbon dioxide concentration (photosynthesis), the concentration of harmful substances in the air (fine dust, VOCs), etc.
3) Analysis of quality changes according to changes in environmental conditions
- Correlation analysis according to changes in multi-factor variables (experiment-based big data construction and analysis)
- Evaluation Indicator (Scoring): Normalization reflecting the weight of each indicator
In the future, through this evaluation model and monitoring system, it is possible to build an regional/local environmental impact whole process using LCA and the life cycle cost evaluation model. In addition, it can be applied practically to farmland to guarantee the quality of agricultural products and realize consumers' right to know.
References
[1] Deng, S.P., Luo, Y.M., Song, J., Teng, Y., Chen, Y.S. (2010) [Prediction of PCBs uptake by vegetable in a representative area and evaluation of the human health risk by Trapp model]. Huan Jing Ke Xue 31, 3018-3027.
[2] Singh, P.K., Shikha, D., Saw, S. (2022) Evaluation of potential toxic heavy metal contamination in soil, fly ash, vegetables and grain crops along with associated ecological and health risk assessment of nearby inhabitants of a thermal power station in Jharkhand (India). Environ Sci Pollut Res Int.
[3] Solazzo, E., Riccio, A., Van Dingenen, R., Valentini, L., Galmarini, S. (2018) Evaluation and uncertainty estimation of the impact of air quality modelling on crop yields and premature deaths using a multi-model ensemble. Sci Total Environ 633, 1437-1452.
[4] Zheng, S.A., Wu, Z., Chen, C., Liang, J., Huang, H., Zheng, X. (2018) Evaluation of leafy vegetables as bioindicators of gaseous mercury pollution in sewage-irrigated areas. Environ Sci Pollut Res Int 25, 413-421.
| Keywords | Agricultural products and systems, Cultivation environment Big data, IoT sensor, |
|---|
