Abstract
Chlorophyll content in plant leaves is an essential indicator of the growth condition and the fertilization management effect of naked barley crops. The soil plant analysis development (SPAD) values strongly correlate with leaf chlorophyll contents. Unmanned Aerial Vehicles (UAV) can provide an efficient way to retrieve SPAD values on a relatively large scale with a high temporal resolution. But the UAV mounted with high-cost multispectral or hyperspectral sensors may be a tremendous economic burden for smallholder farmers. To overcome this shortcoming, we investigated the potential of UAV mounted with a commercial digital camera for estimating the SPAD values of naked barley leaves. We related 21 color-based vegetation indices (VIs) calculated from UAV images acquired from two flight heights (6.0 m and 50.0 m above ground level) in four different growth stages with SPAD values. Our results indicated that vegetation extraction and naked barley ears mask could improve the correlation between image-calculated vegetation indices and SPAD values. The VIs of ‘L*,’ ‘b*,’ ‘G − B’ and ‘2G − R − B’ showed significant correlations with SPAD values of naked barley leaves at both flight heights. The validation of the regression model showed that the index of ‘G-B’ could be regarded as the most robust vegetation index for predicting the SPAD values of naked barley leaves for different images and different flight heights. Our study demonstrated that the UAV mounted with a commercial camera has great potentiality in retrieving SPAD values of naked barley leaves under unstable photography conditions. It is significant for farmers to take advantage of the cheap measurement system to monitor crops.
Highlights
We consider that the vegetation extraction and naked barley ears mask as an optimal image processing method for correlating color-based vegetation indices calculated from Unmanned Aerial Vehicles (UAV) images with soil plant analysis development (SPAD) values of naked barley leaves
The present study suggested that the application of vegetation extraction and naked barley ears mask can improve the correlation between color-based vegetation indices calculated from UAV-mounted commercial digital camera and SPAD values of the naked barley leaves
Values of naked barley leaf from UAV-derived RGB images in our study because of the excellent performance in the validation. This vegetation index could be used for different photography conditions
Summary
Barley production around the world is 159.0 million tons in 2019 [1]. It is a major food source for the people in the cool and semi-arid areas of the world, where wheat and other cereals are less adapted [2]. Due to the relatively harsh growing conditions, some suitable managements, especially nitrogen fertilizer, are necessary to sustain healthy growth and maximum yield production [3]. Leaf chlorophyll content has been proved to be related to nitrogen content in the crops and can be used as a fertilizer indicator during crop management [4,5,6,7,8]. The traditional chemical analysis of chlorophyll content has limitations of labor intensity, destruction and small
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