• Title/Summary/Keyword: crop characteristics

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Automatic Estimation of Tillers and Leaf Numbers in Rice Using Deep Learning for Object Detection

  • Hyeokjin Bak;Ho-young Ban;Sungryul Chang;Dongwon Kwon;Jae-Kyeong Baek;Jung-Il Cho ;Wan-Gyu Sang
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.81-81
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    • 2022

  • Recently, many studies on big data based smart farming have been conducted. Research to quantify morphological characteristics using image data from various crops in smart farming is underway. Rice is one of the most important food crops in the world. Much research has been done to predict and model rice crop yield production. The number of productive tillers per plant is one of the important agronomic traits associated with the grain yield of rice crop. However, modeling the basic growth characteristics of rice requires accurate data measurements. The existing method of measurement by humans is not only labor intensive but also prone to human error. Therefore, conversion to digital data is necessary to obtain accurate and phenotyping quickly. In this study, we present an image-based method to predict leaf number and evaluate tiller number of individual rice crop using YOLOv5 deep learning network. We performed using various network of the YOLOv5 model and compared them to determine higher prediction accuracy. We ako performed data augmentation, a method we use to complement small datasets. Based on the number of leaves and tiller actually measured in rice crop, the number of leaves predicted by the model from the image data and the existing regression equation were used to evaluate the number of tillers using the image data.

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Effect of Cooking Methods on Cooked and Antioxidant Characteristics of Cooked Mixed Grain Rice with Added Proso Millet (기장 첨가 잡곡밥의 취반 및 항산화 특성에 미치는 취반방법의 영향)

  • Kim, Mi-Jung;Lee, Kyung Ha;Ko, Jee Yeon;Kim, Hyun-Joo;Lee, Seuk Ki;Park, Hye Young;Sim, Eun-Yeong;Cho, Dong-Hwa;Oh, Sea Kwan;Woo, Koan Sik
    • The Korean Journal of Food And Nutrition
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    • v.30 no.2
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    • pp.218-225
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    • 2017

  • This study was carried out to compare the cooked and antioxidant characteristics with of cooked mixed grain rice with an addition rate (0, 5, 10, 15 and 20%) of proso millet and various cooking methods. Mixed grain rice with added proso millet was cooked by general and high pressure cooking methods with and without fermented alcohol. All pasting characteristics, except for breakdown viscosity, decreased with increasing the amounts of proso millet. Water binding capacity and swelling power significantly decreased when increasing the amounts of proso millet, however the water solubility index significantly increased. The palatability characteristics of rice with added proso millet showed similar results to rice without proso millet. Total polyphenol contents of rice with 20% proso millet and fermented alcohol added, cooked by general and high pressure cooking methods, were $184.33{\pm}2.69$ and $179.80{\pm}5.22{\mu}g\;GAE/g$, respectively. Total flavonoid contents increased as amounts of proso millet increased. DPPH radical scavenging activities with and without proso millet added were 4.20~7.50 and 2.97~5.19 mg TE/100 g, respectively. ABTS radical scavenging activities with and without proso millet added were 14.36~27.92 and 14.07~15.83 mg TE/100 g, respectively. In this study, cooked and antioxidant characteristics of cooked mixed grain rice with added proso millet were expected to be used as basic data for manufactured processed products.

  • https://doi.org/10.9799/ksfan.2017.30.2.218 인용 PDF KSCI