Conventional methods of plant nutrient estimation for nutrient management need a huge number of leaf or tissue samples and extensive chemical analysis, which is time-consuming and expensive. Remote sensing is a viable tool to estimate the plant’s nutritional status to determine the appropriate amounts of fertilizer inputs. The aim of the study was to use remote sensing to characterize the foliar nutrient status of mango through the development of spectral indices, multivariate analysis, chemometrics, and machine learning modeling of the spectral data. A spectral database within the 350–1050 nm wavelength range of the leaf samples and leaf nutrients were analyzed for the development of spectral indices and multivariate model development. The normalized difference and ratio spectral indices and multivariate models–partial least square regression (PLSR), principal component regression, and support vector regression (SVR) were ineffective in predicting any of the leaf nutrients. An approach of using PLSR-combined machine learning models was found to be the best to predict most of the nutrients. Based on the independent validation performance and summed ranks, the best performing models were cubist (R² ≥ 0.91, the ratio of performance to deviation (RPD) ≥ 3.3, and the ratio of performance to interquartile distance (RPIQ) ≥ 3.71) for nitrogen, phosphorus, potassium, and zinc, SVR (R² ≥ 0.88, RPD ≥ 2.73, RPIQ ≥ 3.31) for calcium, iron, copper, boron, and elastic net (R² ≥ 0.95, RPD ≥ 4.47, RPIQ ≥ 6.11) for magnesium and sulfur. The results of the study revealed the potential of using hyperspectral remote sensing data for non-destructive estimation of mango leaf macro- and micro-nutrients. The developed approach is suggested to be employed within operational retrieval workflows for precision management of mango orchard nutrients.

Salt stress is a major abiotic stress affecting the productivity of rice crop worldwide. This study screened a set of 71 rice genotypes collected from coastal parts of Goa and Karnataka states in India for seedling stage salinity tolerance to identify genotypes alternative to standard salt-tolerant donors Pokkali, FL478, etc. Phenotyping for seedling stage tolerance was carried out under micro plots at an induced salinity of 12 dS/m. For haplotyping, 14SaltolQTL linked simple sequence repeat (SSR) markers on chromosome 1 were utilized. On the basis of the response to salt stress, 10 genotypes were found tolerant, 16 moderately tolerant, 29 sensitive and 15 as highly sensitive. Among the SSR markers, marker RM10871 was the most polymorphic with a polymorphic information content of 0.90, exhibiting 14 different alleles followed by RM10793 (0.84) and RM3412 (0.80) with 8 and 7 alleles, respectively. These markers also exhibited high values for the effective number of alleles (Ne) and gene diversity (I). The haplotype analysis revealed that the allelic constitution of theSaltolregion of 10 tolerant genotypes from our study varied in comparison to the reference tolerant check FL478. Further, the haplotype of three tolerant genotypes, namely, Goa Dhan 2, Panvel 1 and Goa wild rice (GWR) 005 appears to be completely different from the FL478 haplotype indicating tolerance in these genotypes is controlled by genomic region other thanSaltol.These three genotypes with probable novel regions for seedling stage salt tolerance can be considered for enhancing salinity tolerance of rice cultivars.

The currents study evaluated the morphology (apperture, size, perine structures and surface ornamentation) of treated spores of 45 selected fern species from the Western Ghats of India, using Scanning Electron Microspcopy (SEM). Twenty-six species of fern spores were trilete type, while 19 of them had monolete aperture types. The size of the spore were found to be highly variable (20X20µm to 60X60µm) with an average mean spore size of 44 µmX38µm. Further more the spores were found to have a highly diverse perine ornementaion with 11 different types of perine structures. Gammate and psilatetype of perine ornamentation,and Globose and ellipsoidal spore shape were found to be the most common within the studies fern spore samples.The variability found in the spore ultra structure and perispore ornamentation of the selected pteridophytes species reflects the morphological differences observed in the sporophyte. The spores could be an important source of characteristics with systematic value in fern taxonomy.The spore morphology of the examined pteridophytes studied common, endemicor otherwise will find a significant role in future taxonomic surveys, and other morphology, Palynology, discrimination, and identification studies of pteridophytesin the Western Ghats.