Comparative evaluation of inversion approaches of the radiative transfer model for estimation of crop biophysical parameters

The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

Comparative proteomic analysis of primordial follicles from ovaries of immature and aged rats

Age related decline in reproductive performance in women is well documented and apoptosis has been considered as one of the reasons for the decline of primordial follicle reserve. Recently we observed a decline in the efficiency of DNA repair ability in aged rat primordial follicles as demonstrated by decreased mRNA levels of DNA repair genes BRCA1 and H2AX. In the present study, a two-dimensional electrophoresis (2DE) proteomic approach was employed to identify differentially expressed proteins in primordial follicles isolated from ovaries of immature (approximate to 20 days) and aged (approximate to 400-450 days) rats. Using MALDI-TOF/TOF MS, we identified 13 differentially expressed proteins (p<0.05) which included seven up-regulated and six down-regulated proteins in aged primordial follicles. These proteins are involved in a wide range of biological functions including apoptosis, DNA repair, and the immune system. Interestingly, the differentially expressed proteins such as FIGNL1 (DNA repair) and BOK (apoptotic protein) have not been previously reported in the rat primordial follicles and these proteins can be related to some common features of ovarian aging such as loss of follicle reserve and genome integrity. The quantitative differences of two important proteins BOK and FIGNL1 observed by the proteomic analysis were correlated with the transcript levels, as determined by semi-quantitative RT-PCR. Our results improve the current knowledge about protein factors associated with molecular changes in rat primordial follicles as a function of aging and our understanding of the proteomic processes involved in degenerative changes observed in aging primordial follicles.

Disaggregation of LST over India: comparative analysis of different vegetation indices

The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.