Abstract
Climate change brings many changes in a physical environment like plants and leaves. The flowers and plants get affected by natural climate and local weather extremes. However, the projected increase in the frost event causes sensitivity in plant reproduction and plant structure vegetation. The timing of growing and reproduction might be an essential tactic by which plant life can avoid frost. Flowers are more sensitive to hoarfrost than leaves but more sensitive to frost in most cases. In most cases, frost affects the size of the plant, its growth, and the production of seeds. In this article, we examined that how frost affects plants and flowers? How it affects the roots and prevents the growth of plants, vegetables, and fruits? Furthermore, we predicted how the frost will grow and how we should take early precautions to protect our crops? We presented the convolutional neural network model framework and used the conv1d algorithm to evaluate one-dimensional data for frost event prediction. Then, as part of our model contribution, we preprocessed the data set. The results were comparable to four weather stations in the United States. The results showed that our convolutional neural network model configuration is reliable.
Highlights
Plant disease forecasting is critical in the farming sector
Bachofen et al.[8] presented differences in the hardening cycles between species highlight the importance of analyzing cold hardiness repeatedly during potentially vulnerable times to predict species range changes in the context of climate change, between February and July, on seven occasions
Style and Worster[12] presented the study on pure ice sublimating and solid form into an unsaturated atmosphere. Their findings may be used to predict the appearance of frost flowers (FFs) in climate models
Summary
Plant disease forecasting is critical in the farming sector. Agricultural production’s economic growth is dependent on the product quality they produce, which is dependent on crop growth and yield. Arco Molina et al.[6] examined the occurrence by changing age and bark thickness of frost ring in trees, with the hypothesis that certain variables can play a role in physiologic processes that improve the temperature resistance to freezing, impacting the constantly changing tissue. Hanninen[7] volume describes the annual period with different properties, including the timescale of bud explosion and other phonologic activities, seasonal photosynthesis, or frost resistance of the plants. Bachofen et al.[8] presented differences in the hardening cycles between species highlight the importance of analyzing cold hardiness repeatedly during potentially vulnerable times to predict species range changes in the context of climate change, between February and July, on seven occasions.
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More From: International Journal of Distributed Sensor Networks
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