Modified Vegetation Detection Index Using Different-Spectral Signature

The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near- IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near- IR and Shortwave infrared radiation (SWIR) divided by their sums. The radiances or reflectances are included in this index from the Near-IR channel and WSIR2 channel (2.1 μm). The NDVSI is less sensitivite to atmospheric effects as compared to NDVI. By comparing the one NDVSI index with the two indexes (NDVI, SAVI) of vegetation cover, good correlations were found between NDVI and NDVSI (R2=0.917) and between SAVI and NDVSI (R2=0.809. Accordingly, the proposed index can be taken into consideration as an independent vegetation index

Species-Level Classification and Mapping of a Mangrove Forest Using Random Forest—Utilisation of AVIRIS-NG and Sentinel Data

Although studies on species-level classification and mapping using multisource data and machine learning approaches are plenty, the use of data with ideal placement of central wavelength and bandwidth at appropriate spatial resolution, for the classification of mangrove species is underreported. The species composition of a mangrove forest has been estimated utilising the red-edge spectral bands and chlorophyll absorption information from AVIRIS-NG and Sentinel-2 data. In this study, three dominant species, Heritiera fomes, Excoecaria agallocha and Avicennia officinalis, have been classified using the random forest (RF) model for a mangrove forest in Bhitarkanika Wildlife Sanctuary, India. Various combinations of reflectance/backscatter bands and vegetation indices derived from Sentinel-2, AVIRIS-NG, and Sentinel-1 were used for species-level discrimination and mapping. The RF model showed maximum accuracy using Sentinel-2, followed by the AVIRIS-NG, in discriminating three dominant species and two mixed compositions. This study indicates the potential of Sentinel-2 data for discriminating various mangrove species owing to the appropriate placement of central wavelength and bandwidth in Sentinel-2 at ≥10 m spatial resolution. The variable importance plots proved that species-level classification could be attempted using red edge and chlorophyll absorption information. This study has wider applicability in other mangrove forests around the world.

Advanced Photonic Thin Films for Solar Irradiation Tuneability Oriented to Greenhouse Applications

The world population is growing by 1 billion people every 10 years. There will come a time when there will be more people to feed but less land to grow food. Greenhouses can be the solution to this problem because they provide the highest production yield per m2 and also use less water, provide food safety, and offer high quality. Photosynthetic active radiation (PAR) favors vegetable growth with a specific blue and red light ratio. Thus, increasing the amount of red light improves chlorophyll absorption and photosynthetic efficiency. In this article, we present a hybrid system that combines luminescent materials and photonic crystals for better management of the light reaching the greenhouse. The luminescent dyes considered herein are combined ensuring a Förster resonance energy transfer (FRET) nonradiative mechanism to enhance the absorption range. The designed photonic crystal maximizes reflections in the Near-Infrared (NIR) range, and therefore, thermal losses are minimized. Thus, by converting harmful or ineffective radiation for plant growth to the PAR region, we aim to demonstrate growth-condition enhancement for the different vegetables that have been used as a model.

Strain Sensor via Wood Anomalies in 2D Dielectric Array

Optical sensing is one of many promising applications for all-dielectric photonic materials. Herein, we present an analytical and numerical study on the strain-responsive spectral properties of a bioinspired sensor. The sensor structure contains a two-dimensional periodic array of dielectric nanodisks to mimic the optical behavior of grana lamellae inside chloroplasts. To accumulate a noticeable response, we exploit the collective optical mode in grana ensemble. In higher plants, such a mode appears as Wood’s anomaly near the chlorophyll absorption line to control the photosynthesis rate. The resonance is shown persistent against moderate biological disorder and deformation. Under the stretching or compression of a symmetric structure, the mode splits into a couple of polarized modes. The frequency difference is accurately detected. It depends on the stretch coefficient almost linearly providing easy calibration of the strain-sensing device. The sensitivity of the considered structure remains at 5 nm/% in a wide range of strain. The influence of the stretching coefficient on the length of the reciprocal lattice vectors, as well as on the angle between them, is taken into account. This adaptive phenomenon is suggested for sensing applications in biomimetic optical nanomaterials.

Pemanfaatan Tepung Biji Nangka (Artocarpus heterophyllus) dan Tepung Singkong (Manihot esculenta) Dengan Penambahan Pigmen Klorofil Pada Sayuran Sebagai Sumber Antioksidan Beras Analog

Jackfruit seeds have high carbohydrate and protein, which is around 56.21% and 12.19%. Substitution with cassava starch which has amylose and amylopectin can help analog rice characteristics. The addition of natural dyes such as chlorophyll is also needed in the diversification of analog rice food as a source of antioxidants. The purpose of this study was to find out the diversification of jackfruit seed processing through the use of jackfruit seed flour and cassava flour substitution into analog rice, determine the effect of adding extracts to different vegetables on the physicochemical and organoleptic properties of analog rice, knowing the presence of chlorophyll and antioxidant content in analog rice substitution jackfruit seed flour and cassava flour. This study uses Nested design / nested design. Nest/parent namely the proportion of flour with 3 levels (10% jackfruit seed flour and 90% cassava flour, 20% jackfruit seed flour and 80% cassava flour, 30% jackfruit seed flour and 70% cassava flour) and the nest is a pigment with 4 levels (without pigments, green spinach pigments, suji leaf pigments, moringa leaf pigments). The results showed a very significant effect on water content, ash content, fat, protein, carbohydrates, antioxidants, chlorophyll, absorption, brightness, color (a-), and color (b +), redeem and organoleptic such as taste, texture, shape, and liking. Organoleptic texture has no real effect. The best treatment for T3W2 treatment is the proportion of 30% jackfruit seed flour and 70% tapioca flour with the addition of pigment from green spinach.

Development of sugarcane and trash identification system in sugar production using hyperspectral imaging

Classification and differentiation of clean sugarcane from trash (green sugarcane leaf, dry sugarcane leaf, stone, and soil) are important for the sugar payment system at a sugar mill. Currently, the methods used to do this are manual and subjective. Therefore, this study is aimed at accurately differentiating clean sugarcane from trash by using hyperspectral imaging with multivariate analyses. Samples containing sugarcane billets and trash mixed in a ratio of 18:38 were analyzed in this study. The reflectance data of the samples were analyzed in the wavelength range of 400–1000 nm via principal component analysis (PCA). The PCA model was capable of identifying all of the clean sugarcane and trash samples. The spectral loadings of the PCA model show that the sugarcane and trash samples are easily identifiable based on the color (visible light) of each class, water absorption (approximately 970 nm), and chlorophyll absorption (approximately 680 nm). Based on the characteristic wavelengths of the PCA loading peaks, over 90% of the sugarcane and trash samples were differentiated using a multiple linear regression model. Sugarcane and trash are classified by using partial least-squares discriminant analysis and support vector machine models. For all wavelengths, the classification rate is 92.9% and 98.2%, respectively. This shows that sugarcane and trash can be accurately classified and differentiated by using hyperspectral imaging and multivariate analyses.

Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards

Heatwaves are common in many viticultural regions of Australia. We evaluated the potential of satellite-based remote sensing to detect the effects of high temperatures on grapevines in a South Australian vineyard over the 2016–2017 and 2017–2018 seasons. The study involved: (i) comparing the normalized difference vegetation index (NDVI) from medium- and high-resolution satellite images; (ii) determining correlations between environmental conditions and vegetation indices (Vis); and (iii) identifying VIs that best indicate heatwave effects. Pearson’s correlation and Bland–Altman testing showed a significant agreement between the NDVI of high- and medium-resolution imagery (R = 0.74, estimated difference −0.093). The band and the VI most sensitive to changes in environmental conditions were 705 nm and enhanced vegetation index (EVI), both of which correlated with relative humidity (R = 0.65 and R = 0.62, respectively). Conversely, SWIR (short wave infrared, 1610 nm) exhibited a negative correlation with growing degree days (R = −0.64). The analysis of heat stress showed that green and red edge bands—the chlorophyll absorption ratio index (CARI) and transformed chlorophyll absorption ratio index (TCARI)—were negatively correlated with thermal environmental parameters such as air and soil temperature and growing degree days (GDDs). The red and red edge bands—the soil-adjusted vegetation index (SAVI) and CARI2—were correlated with relative humidity. To the best of our knowledge, this is the first study demonstrating the effectiveness of using medium-resolution imagery for the detection of heat stress on grapevines in irrigated vineyards.

DETECTION OF BACTERIAL WILT DISEASE (<i>PSEUDOMONAS SOLANCEARUM</i>) IN BRINJAL USING HYPERSPECTRAL REMOTE SENSING

<p><strong>Abstract.</strong> Bacterial wilt disease (pathogen: <i>Pseudomonas solancearum</i>) is a major problem affecting brinjal crop. Infected leaves show yellowing, loss in turgidity, drying and ultimately the entire plant collapses. The study aims to examine the potential of hyperspectral remote sensing for detection of biotic stress caused due to bacterial wilt disease and identify best spectral band widths and hyperspectral indices indicative of disease infestation. This study was conducted in a farmer’s plot at Alampur in Baruipur block, South 24 Pargana district, West Bengal. Canopy spectra (using ASD Fieldspec 2 Spectroradiometer), chlorophyll content (by Chlorophyll meter) and Leaf Area Index (LAI) (by plant canopy imager) were collected. The healthy plants had green and fully turgid leaves whereas diseased plants had lower chlorophyll content and LAI. The reduction in chlorophyll content lowered reflectance in green region and internal leaf damage in near-infrared region. A correlation analysis was carried out between reflectance at specific bandwidths and hyperspectral indices with chlorophyll content and LAI of healthy and stressed plants. Bandwidths of 528&amp;ndash;531&amp;thinsp;nm, 550&amp;ndash;570&amp;thinsp;nm, 710&amp;ndash;760&amp;thinsp;nm, and single bands such as 800&amp;thinsp;nm and 920&amp;thinsp;nm and indices viz. Greenness index, Modified Chlorophyll Absorption in Reflectance Index (MCARI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Triangular Vegetation Index (TVI), Simple Ratio Pigment Index (SRPI), Photochemical Reflectance Index (PRI 2), Lichtenthaler Indices (LIC1, LIC2), Structure Intensive Pigment Index (SIPI) etc. were found to have strong positive correlation (R²&amp;thinsp;&amp;gt;&amp;thinsp;0.9) with plant parameters. These specific bandwidths and indices can be helpful in biophysical parameter estimation and early detection of crop stress, crop growth and disease monitoring.</p>

The ways and means of Express-diagnostics of plants for protected ground

The article deals with the results of studies related to the testing of the proposed method of rapid diagnosis of plants conducted in the production conditions of Agrocomplex "Churilovo". It was found that the absorption spectrum of the leaf apparatus of cucumber plants in the control variant (substrate – mineral wool) and the experimental variant (substrate - agroperlite) differed insignificantly: the arithmetic mean values of chlorophyll absorption in the control and experiment were 3,668 and 3,772, respectively; carotenoid absorption - 3,560 and 3,403; cytochrome absorption - 2,681 and 2,645, respectively. There were minor differences in the content of micro - and macronutrients in plant leaves and yield. It is revealed that the proposed method of rapid diagnosis, based on the analysis of the absorption spectra of the sheet apparatus, allows to obtain results comparable to the results of chemical analysis and yield assessment, and can be used to diagnose the condition of plants.