Phenotyping system for precise monitoring of potato crops during growth-Reference-Cited by-同舟云学术

Phenotyping system for precise monitoring of potato crops during growth

Published:2023 Issue:1 Volume:16 Page:24-36
ISSN:1881-8366
Container-title:Engineering in Agriculture, Environment and Food
language:en
Short-container-title:Engineering in Agriculture, Environment and Food

Author:

NJANE Stephen Njehia¹,TSUDA Shogo¹,SUGIURA Ryo²,KATAYAMA Kenji¹,GOTO Kazuhisa³,TSUCHIYA Shinori¹,TSUJI Hiroyuki¹

Affiliation:

1. Hokkaido Agricultural Research Center, National Agriculture and Food Research Organization (NARO)

2. The Research Center for Agricultural Information Technology, National Agriculture and Food Research Organization (NARO)

3. NARO Development Strategy Center (NDSC), National Agriculture and Food Research Organization (NARO)

Publisher

Asian Agricultural and Biological Engineering Association

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,Food Science

Link

https://www.jstage.jst.go.jp/article/eaef/16/1/16_24/_pdf

Reference35 articles.

1. Barnes, E. M. et al. 2000. Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. Proceedings of the 5th International Conference on Precision Agriculture. Madison, WI, USA, 2000.

2. Beukema, H. P. and D. E. van der Zaag. 1990. Introduction to Potato Production. The Netherlands: Centre for Agriculture Publication and Documentation (Pudoc), Wageningen.

3. Bhadra, S. et al. 2020. Quantifying leaf chlorophyll concentration of sorghum from hyperspectral data using derivative calculus and machine learning. Remote Sensing. 12 (13): 2082. https://doi.org/10.3390/rs12132082 (Accessed 8 Aug. 2023).

4. Boiarskii, B. and H. Hasegawa. 2019. Comparison of NDVI and NDRE indices to detect differences in vegetation and chlorophyll content. Journal of Mechanics of Continua and Mathematical Sciences. Special Issue 4: 20–29. https://doi.org/10.26782/jmcms.spl.4/2019.11.00003 (Accessed 8 Aug. 2023).

5. Boyd, N. S. et al. 2002. Relationship between leaf area index and ground cover in potato under different management conditions. Potato Research. 45 (2): 117–129. https://doi.org/10.1007/BF02736107 (Accessed 8 Aug. 2023).

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