Optimal Cultivation Strategies and Prediction of Fresh Weight in Vegetable Farming

Crops grown in open fields are greatly affected by various environmental factors such as climate, temperature changes and precipitation which can significantly influence crop yields depending on cultivation methods and environmental conditions. Therefore, this study proposes cultivation strategies to maximize the yield of onions and garlic along with methods for predicting bulb weight. An experimental site was established at the Allium Crop Research Institute in Muan, where growth characteristics were manually measured, and vegetation indices were acquired using multispectral imaging, along with corresponding bulb weights for both onions and garlic at regular intervals. To predict bulb weight, three predictive models were applied: NFCRM, RFRM, and 1D-CNN+Attention BiLSTM. Comparative analysis of predictive performance showed that NFCRM outperformed the other models, RFRM and 1DCABL, in predicting of the bulb weight of both onions and garlic.

Authors

Publication Details

Journal
Korean Institute of Smart Media
Published
2024-12-31
DOI
https://doi.org/10.30693/smj.2024.13.12.45
Citations
1
Primary Topic
Greenhouse Technology and Climate Control
Type
article
Field-Weighted Citation Impact
0.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal Cultivation Strategies and Prediction of Fresh Weight in Vegetable Farming

Jin Ho Kang, Z.H. Liu, Myung-Hwan Na, Soo Ram Kang
1 citations
Korean Institute of Smart Media
Greenhouse Technology and Climate Control
0.60
article

Optimal Cultivation Strategies and Prediction of Fresh Weight in Vegetable Farming

Jin Ho Kang, Z.H. Liu, Myung-Hwan Na, Soo Ram Kang
article en
1 citations

Abstract

Crops grown in open fields are greatly affected by various environmental factors such as climate, temperature changes and precipitation which can significantly influence crop yields depending on cultivation methods and environmental conditions. Therefore, this study proposes cultivation strategies to maximize the yield of onions and garlic along with methods for predicting bulb weight. An experimental site was established at the Allium Crop Research Institute in Muan, where growth characteristics were manually measured, and vegetation indices were acquired using multispectral imaging, along with corresponding bulb weights for both onions and garlic at regular intervals. To predict bulb weight, three predictive models were applied: NFCRM, RFRM, and 1D-CNN+Attention BiLSTM. Comparative analysis of predictive performance showed that NFCRM outperformed the other models, RFRM and 1DCABL, in predicting of the bulb weight of both onions and garlic.

Korean Institute of Smart MediaVol. 13(12)
Openalex Percentile: Top 20%
Greenhouse Technology and Climate Control
0.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.