Assessment of Photochemical Reflectance Index as a Tool for Evaluation of Chlorophyll Fluorescence Parameters in Cotton and Peanut Cultivars Under Water Stress Condition

The relationships between photochemical reflectance index （PRI） and the chlorophyll fluorescence parameters were examined to assess suitability of PRI as a remote-sensing tool for the chlorophyll fluorescence parameters. A greenhouse experiment was conducted using cotton and peanut crops under water stress condition. Five cotton and six peanut cultivars were grown using Andosole soil in pots maintained at two water levels; the control and water stress treatment （WS） of 100 and 50% of the daily transpiration, respectively. Higher non-photochemical quenching （NPQ） was exhibited by peanut than that of cotton by the water stress. On the other hand, the decreases of the actual quantum yield of photosystem II （△F/F＇m） and PRI by the water stress in cotton were larger than those in peanut. There were positively significant correlation coefficients between PRI and △F/F＇m in cotton at noon and in the afternoon including the control and WS. The correlations of PRI with NPQ were negatively significant at noon and in the afternoon for cotton, and in the afternoon for peanut. No clear relationship was found among these parameters in the morning probably due to the diurnal increase in global solar radiation. It was concluded that there would be a possibility to detect the effects of water stress on △F/F＇m and NPQ by PRI with some exceptions, although PRI could not note varietals differences in △F/F＇m and NPQ for each treatment.

Simple method for extracting the seasonal signals of photochemical reflectance index and normalized difference vegetation index measured using a spectral reflectance sensor

A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.

Cultivar,Nitrogen and Irrigation Influence on Grain Quality and Its Forecasting Methods by In situ Reflected Spectrum of Winter Wheat

Field experiments were conducted to examine the influence factors of cultivar, nitrogen application and irrigation on grain protein content, gluten content and grain hardness in three winter wheat cultivars under four levels of nitrogen and irrigation treatments. Firstly, the influence of cultivars and environment factors on grain quality were studied, the effective factors were cultivars, irrigation, fertilization, etc. Secondly, total nitrogen content around winter wheat anthesis stage was proved to be significantly correlative with grain protein content, and spectral vegetation index significantly correlated to total nitrogen content around anthesis stage were the potential indicators for grain protein content. Accumulation of total nitrogen content and its transfer to grain is the physical link to produce the final grain protein, and total nitrogen content at anthesis stage was proved to be an indicator of final grain protein content. The selected normalized photochemical reflectance index (NPRI) was proved to be able to predict grain protein content on the close correlation between the ratio of total carotenoid to chlorophyll a and total nitrogen content. The method contributes towards developing optimal procedures for predicting wheat grain quality through analysis of their canopy reflected spectrum at anthesis stage. Regression equations were established to forecast grain protein and dry gluten content by total nitrogen content at anthesis stage, so it is feasible for forecasting grain quality by establishing correlation equations between biochemical constitutes and canopy reflected spectrum.

Remote Sensing Indices to Measure the Seasonal Dynamics of Photosynthesis in a Southern China Subtropical Evergreen Forest

The accurate measurement of the dynamics of photosynthesis in China’s subtropical evergreen forest ecosystems is an important contribution to carbon(C) sink estimates in global terrestrial ecosystems and their responses to climate change. Eddy covariance has historically been the only direct method to assess C flux of whole ecosystems with high temporal resolution, but it suffers from limited spatial resolution. During the last decade, continuous global monitoring of plant primary productivity from spectroradiometer sensors on flux towers and satellites has extended the temporal and spatial coverage of C flux observations. In this study, we evaluated the performance of two physiological remote sensing indices, fluorescence reflectance index(FRI) and photochemical reflectance index(PRI), to measure the seasonal variations of photosynthesis in a subtropical evergreen forest ecosystem using continuous canopy spectral and flux measurements in the Dinghushan Nature Reserve in southern China.The more commonly used NDVI has been shown to be saturated and mainly affected by illumination(R^2=0.88, p <0.001), but FRI and PRI could better track the seasonal dynamics of plant photosynthetic functioning by comparison and are less affected by illumination(R^2=0.13 and R^2=0.51, respectively) at the seasonal scale. FRI correlated better with daily gross primary production(GPP) in the morning hours than in the afternoon hours, in contrast to PRI which correlated better with light-use efficiency(LUE) in the afternoon hours. Both FRI and PRI could show greater correlations with GPP and LUE respectively in the senescence season than in the recovery-growth season. When incident PAR was taken into account, the relationship between GPP and FRI was improved and the correlation coefficient increased from 0.22 to 0.69(p < 0.001). The strength of the correlation increased significantly in the senescence season(R^2=0.79, p < 0.001). Our results demonstrate the application of FRI and PRI as physiological indices for the accurate measurement of the seasonal dynamics of plant community photosynthesis in a subtropical evergreen forest, and suggest these indices may be applied to carbon cycle models to improve the estimation of regional carbon budgets.