RESUMO
At field scale, surface soil had special characteristics of volumetric moisture content (VMC) with a relatively little difference and spatial heterogeneity induced by physical and chemical properties, roughness, straw residues, etc. It has been a great challenge for near infrared diffuse reflectance spectroscopy (NIR-DRS) measurement of surface soil moisture in situ. In this study, exonential decay models based on seven water-related wavelengths (1200, 1400, 1450, 1820, 1940, 2000 and 2250 nm), linear models of normalized difference soil moisture index (NSMI) and relative absorption depth (RAD) based on wave-length combinations, linear or quadratic model of width of the inflection (σ), center amplitude of the function (Rd) and area under the Gaussian curve (A) from soil moisture Gaussian model (SMGM), and partial least square (PLS) regression models based on bands were used to quantify VMC. The results indicated that (1) of all the single wavelengths, 2 000 nm showed the best validation result, indicated by the lowest RMSEp (2.463) and the highest RPD value (1.060). (2) Comparing with RAD, the validation of NSMI was satisfactory with higher R² (0.312), lower RMSEp (2.133) and higher RPD value (1.224). (3) In the validation results of SMGM parameters and PLS fitting, Rd was found to produce the best fitting quality identified by the highest R² (0.253), the lowest RMSEp (2.222), and the highest RPD value (1.175). (4) Comprehensively, a linear model based on NSMI showed the highest validation accuracy of all the methods. What is more, its calculation process is simple and easy to operate, and therefore become the preferred method to quantify surface soil moisture content in situ.
RESUMO
In the present study, late frost experiments were implemented under a range of subfreezing temperatures (-1 - -9 degrees C) by using a field movable climate chamber (FMCC) and a cold climate chamber, respectively. Based on the spectra of winter wheat canopy measured at noon on the first day after the frost experiments, red edge parameters REP, Dr, SDr, Dr(min), Dr/Dr(min) and Dr/SDr were extracted using maximum first derivative spectrum method (FD), linear four-point interpolation method (FPI), polynomial fitting method (POLY), inverted Gaussian fitting method (IG) and linear extrapolation technique (LE), respectively. The capacity of the red edge parameters to detect late frost stress was explicated from the aspects of the early, sensitivity and stability through correlation analysis, linear regression modeling and fluctuation analysis. The result indicates that except for REP calculated from FPI and IG method in Experiment 1, REP from the other methods was correlated with frost temperatures (P < 0.05). Thereinto, significant levels (P) of POLY and LE methods all reached 0.01. Except for POLY method in Experiment 2, Dr/SDr from the other methods were all significantly correlated with frost temperatures (P < 0.01). REP showed a trend to shift to short-wave band with decreasing temperatures. The lower the temperature, the more obvious the trend is. Of all the REP, REP calculated by LE method had the highest correlation with frost temperatures which indicated that LE method is the best for REP extraction. In Experiment 1 and 2, only Dr(min) and Dr/Dr(min), calculated by FD method simultaneously achieved the requirements for the early (their correlations with frost temperatures showed a significant level P < 0.01), sensitivity (abso- lute value of the slope of fluctuation coefficient is greater than 2.0) and stability (their correlations with frost temperatures al- ways keep a consistent direction). Dr/SDr calculated from FD and IG methods always had a low sensitivity in Experiment 2. In Experiment 1, the sensitivity of Dr/SDr from FD was moderate and IG was high. REP calculated from LE method had a lowest sensitivity in the two experiments. Totally, Dr(min) and Dr/Dr(min) calculated by FD method have the strongest detection capacity for frost temperature, which will be helpful to conducting the research on early diagnosis of late frost injury to winter wheat.
