Abstract
Ratio of carbon to nitrogen concentration (C/N) that can illuminate metabolic status of C and N in crop leaves is one valuable indicator for crop nutrient diagnosis. This study explored the feasibility of using spectral slope features from hyperspectral measurements with Branch-and-Bound (BB) algorithm to monitor leaf C/N in wheat and barley. Experimental data from barley in 2010 and wheat in 2012 were collected and used. The analyses prove that leaf C/N is closely related to leaf N concentration (LNC), which implies that it is feasible to apply spectral technology to monitor leaf C/N in that LNC may have been effectivly estimated by hyperspectral measurements. The results also show that many spectral slope features proposed in this study exhibit the significant correlations with leaf C/N. The best slope feature could evaluate changes of leaf C/N well, with R2 of 0.63 for wheat, 0.68 for barley and 0.65 for both species combined, respectively. using BB algorithm with input of optiaml four slope features can improve the accuracy of leaf C/N estimations with R2 over 0.81. It is concluded that using the spectral slope new features with BB method appears very promising and potential for remotely monitoring leaf C/N in crops.
Highlights
The metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production[1,2,3,4]
The variation tends between C/N, leaf N concentration (LNC) and LCC were analyzed with barley and wheat data from field measurements (Fig. 4)
C/N that can mirror the metabolic status of carbon and nitrogen is a comprehensive indicator for evaluating the metabolic balance of carbon-nitrogen and diagnosing growth vigor in crop plants
Summary
The metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production[1,2,3,4]. Leaf is the major organ of plant photosynthesis and physiological activity, and in leaf tissues the ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), can help people to understand and quantify the carbon and nitrogen metabolism in crop plants, and is a good indicator for synthetically diagnosing the balance of carbon and nitrogen, nutrient status, growth vigor and disease resistance in crops[5] It is very significant for dynamic regulation in crop fields to monitor changes of leaf C/N quickly and accurately and in real time. It should be more rational to apply multiple wavebands to assess the ratio of carbon to nitrogen since the ratio of C/N is related with two elements of C and N for crop development, but not one This present study intended to explore the spectral slope features to monitor leaf C/N for guiding field management and fertilizer strategy. A new method, Branch-and-Bound (BB) algorithm that may find the best subset of variables without examining all possible subsets when selecting numbers of variables in a multiple regression analysis was coupled with the slope features for accuracy improvement of estimating leaf C/N
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