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ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Agroecosystems Management Research » Research » Publications at this Location » Publication #350329
Research Project: Agroecosystem Benefits from the Development and Application of New Management Technologies in Agricultural Watersheds

Location: Agroecosystems Management Research

Title: An approach for indirect determination of leaf area index

Author
item Logsdon, Sally
item Cambardella, Cynthia

Submitted to: American Society of Agricultural and Biological Engineers
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/1/2019
Publication Date: 6/1/2019
Citation: Logsdon, S.D., Cambardella, C.A. 2019. An approach for indirect determination of leaf area index. American Society of Agricultural and Biological Engineers. 62(3):655-659. https://doi.org/10.13031/trans.13187.
DOI: https://doi.org/10.13031/trans.13187

Interpretive Summary: Leaf area index is an important measurement of crop growth, but can be timely or expensive to measure. This study determined leaf area index from photos taken looking down on the crop, combined with height of the crop. The results from the photos were less variable than from a commercial instrument used to measure leaf area index. This study is important for scientists who want an inexpensive way to determine crop growth.

Technical Abstract: Assessing leaf area index (LAI) for multiple crops and species growing together in a given area can be challenging. The purpose of this study was to indirectly determine LAI from ground cover and canopy height using defined relationships based on crop coefficients. Images of plant canopy were obtained to estimate green cover fraction. An equation was derived to determine LAI from ground cover and plant height, and tested on different crops. For three of the measurement dates, the data were compared to LAI measurements obtained with a LAI-2200. The trend was the same for the two LAI procedures but there was some scatter. Determining LAI from digital images was an inexpensive way to determine LAI for multiple crops that also allowed distinguishing crop from weed, and green from senescent plants.