Relevant bibliographies by topics / Plant reflectance spectra

Academic literature on the topic 'Plant reflectance spectra'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Plant reflectance spectra"

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Steddom, K., G. Heidel, D. Jones, and C. M. Rush. "Remote Detection of Rhizomania in Sugar Beets." Phytopathology® 93, no. 6 (June 2003): 720–26. http://dx.doi.org/10.1094/phyto.2003.93.6.720.

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As a prelude to remote sensing of rhizomania, hyper-spectral leaf reflectance and multi-spectral canopy reflectance were used to study the physiological differences between healthy sugar beets and beets infested with Beet necrotic yellow vein virus. This study was conducted over time in the presence of declining nitrogen levels. Total leaf nitrogen was significantly lower in symptomatic beets than in healthy beets. Chlorophyll and carotenoid levels were reduced in symptomatic beets. Vegetative indices calculated from leaf spectra showed reductions in chlorophyll and carotenoids in symptomatic beets. Betacyanin levels estimated from leaf spectra were decreased at the end of the 2000 season and not in 2001. The ratio of betacyanins to chlorophyll, estimated from canopy spectra, was increased in symptomatic beets at four of seven sampling dates. Differences in betacyanin and carotenoid levels appeared to be related to disease and not nitrogen content. Vegetative indices calculated from multi-spectral canopy spectra supported results from leaf spectra. Logistic regression models that incorporate vegetative indices and reflectance correctly predicted 88.8% of the observations from leaf spectra and 87.9% of the observations for canopy reflectance into healthy or symptomatic classes. Classification was best in August with a gradual decrease in accuracy until harvest. These results indicate that remote sensing technologies can facilitate detection of rhizomania.
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Schweiger, Anna K., Jeannine Cavender-Bares, Shan Kothari, Philip A. Townsend, Michael D. Madritch, Jake J. Grossman, Hamed Gholizadeh, Ran Wang, and John A. Gamon. "Coupling spectral and resource-use complementarity in experimental grassland and forest communities." Proceedings of the Royal Society B: Biological Sciences 288, no. 1958 (September 2021): 20211290. http://dx.doi.org/10.1098/rspb.2021.1290.

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Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated n -dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.
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Kvíčala, Miroslav, Eva Lacková, and Michaela Štamborská. "Internal Reflectance Modelling ofHordeum vulgareLeaves During Drying." Journal of Chemistry 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/210679.

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Spectral reflectance, or indexes that characterize spectral reflectance at concrete wavelength, is commonly used as an indicator of plant stress, or its photosynthetic apparatus status. In this paper, new leaf optical model is presented. Within this paper, experimental determination of surface and internal reflectance of Spring barley leaves and mathematical-physical modelling of internal reflectance were performed. It was proven that a new proposed theoretical model and the experimental spectra of internal reflectance are strongly correlated. It can be concluded that the total reflectance is not a function of epidermis condition, but it testifies about overall functional condition of Spring barley leaves.
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Merrick, Trina, Ralf Bennartz, Maria Luisa S. P. Jorge, Stephanie Pau, and John Rausch. "Evaluation of Plant Stress Monitoring Capabilities Using a Portable Spectrometer and Blue-Red Grow Light." Sensors 22, no. 9 (April 29, 2022): 3411. http://dx.doi.org/10.3390/s22093411.

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Remote sensing offers a non-destructive method to detect plant physiological response to the environment by measuring chlorophyll fluorescence (CF). Most methods to estimate CF require relatively complex retrieval, spectral fitting, or modelling methods. An investigation was undertaken to evaluate measurements of CF using a relatively straightforward technique to detect and monitor plant stress with a spectroradiometer and blue-red light emitting diode (LED). CF spectral response of tomato plants treated with a photosystem inhibitor were assessed and compared to traditional reflectance-based indices: normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI). The blue-red LEDs provided input irradiance and a “window” in the CF emission range of plants (~650 to 850 nm) sufficient to capture distinctive “two-peak” spectra and to distinguish plant health from day to day of the experiment, while within day differences were noisy. CF-based metrics calculated from CF spectra clearly captured signs of vegetation stress earlier than reflectance-based indices and by visual inspection. This CF monitoring technique is a flexible and scalable option for collecting plant function data, especially for indicating early signs of stress. The technique can be applied to a single plant or larger canopies using LED in dark conditions by an individual, or a manned or unmanned vehicle for agricultural or military purposes.
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Zhu, Yan, Yingxue Li, Wei Feng, Yongchao Tian, Xia Yao, and Weixing Cao. "Monitoring leaf nitrogen in wheat using canopy reflectance spectra." Canadian Journal of Plant Science 86, no. 4 (October 10, 2006): 1037–46. http://dx.doi.org/10.4141/p05-157.

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Non-destructive monitoring of leaf nitrogen (N) status can assist in growth diagnosis, N management and productivity forecast in field crops. The objectives of this study were to determine the relationships of leaf nitrogen concentration on a leaf dry weight basis (LNC) and leaf nitrogen accumulation per unit soil area (LNA) to ground-based canopy reflectance spectra, and to derive regression equations for monitoring N nutrition status in wheat (Triticum aestivum L.). Four field experiments were conducted with different N application rates and wheat cultivars across four growing seasons, and time-course measurements were taken on canopy spectral reflectance, LNC and leaf dry weights under the various treatments. In these studies, LNC and LNA in wheat increased with increasing N fertilization rates. The canopy reflectance differed significantly under varied N rates, and the pattern of response was consistent across the different cultivars and years. Overall, an integrated regression equation of LNC to normalized difference index (NDI) of 1220 and 710 nm of canopy reflectance spectra described the dynamic pattern of change in LNC in wheat. The ratios of several near infrared (NIR) bands to visible light were linearly related to LNA, with the ratio index (RI) of the average reflectance over 760, 810, 870, 950 and 1100 nm to 660 nm having the best index for quantitative estimation of LNA in wheat. When independent data were fit to the derived equations, the average root mean square error (RMSE) values for the predicted LNC and LNA relative to the observed values were no more than 15.1 and 15.2%, respectively, indicating a good fit. Our relationships of leaf N status to spectral indices of canopy reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in wheat. Key words: Wheat, leaf nitrogen concentration, leaf nitrogen accumulation, canopy reflectance, spectral index, nitrogen monitoring
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Stone, Christine, Laurie A. Chisholm, and Simon McDonald. "Spectral reflectance characteristics of Pinus radiata needles affected by dothistroma needle blight." Canadian Journal of Botany 81, no. 6 (June 1, 2003): 560–69. http://dx.doi.org/10.1139/b03-053.

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Dothistroma needle blight, caused by Dothistroma septosporum (Dorog) Morelet, is an economically significant disease of several Pinus species in New Zealand, Australia, Chile, South Africa, and parts of Asia, North America, and Europe. The spectral reflectance properties of Pinus radiata D. Don needles infected by D. septosporum were examined over the visible and near-infrared wavelength region (400–1000 nm). The largest reflectance difference occurred on the shoulder of the near-infrared region at 763 nm. Wavelengths of greatest sensitivity to D. septosporum infection were located in the ranges of 675–691 nm, followed by wavelengths near 760 and 550 nm. Sensitivity minima occurred at 434, 493, 506, 709, and 1373 nm. The reflectance ratio best correlated to needle damage was 709/691 nm (r = –0.739, P < 0.001). Among the other reflectance indices tested, an index based on wavelengths of the upper red edge (710–740 nm) was also well correlated (r = –0.730, P < 0.001). There was not a strong linear relationship between the point of maximum slope in the red edge region (red edge position) and needle damage category. This may be because D. septosporum is a necrotrophic fungal pathogen producing a complex series of damage symptoms: initial chlorosis, production of red and brown metabolites, rapid loss of cellular integrity, cell necrosis, and eventual desiccation. Diagnostic features identified in the infected needle spectra may contribute to the formulation of remotely sensed spectral indices for detecting and monitoring dothistroma needle blight in plantations.Key words: Dothistroma, Pinus radiata, needle damage, reflectance spectra, remote sensing.
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Basinger, Nicholas T., Katherine M. Jennings, Erin L. Hestir, David W. Monks, David L. Jordan, and Wesley J. Everman. "Phenology affects differentiation of crop and weed species using hyperspectral remote sensing." Weed Technology 34, no. 6 (August 18, 2020): 897–908. http://dx.doi.org/10.1017/wet.2020.92.

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AbstractThe effect of plant phenology and canopy structure of four crops and four weed species on reflectance spectra were evaluated in 2016 and 2017 using in situ spectroscopy. Leaf-level and canopy-level reflectance were collected at multiple phenologic time points in each growing season. Reflectance values at 2 wk after planting (WAP) in both years indicated strong spectral differences between species across the visible (VIS; 350–700 nm), near-infrared (NIR; 701–1,300 nm), shortwave-infrared I (SWIR1; 1,301–1,900 nm), and shortwave-infrared II (SWIR2; 1,901–2,500 nm) regions. Results from this study indicate that plant spectral reflectance changes with plant phenology and is influenced by plant biophysical characteristics. Canopy-level differences were detected in both years across all dates except for 1 WAP in 2017. Species with similar canopy types (e.g., broadleaf prostrate, broadleaf erect, or grass/sedge) were more readily discriminated from species with different canopy types. Asynchronous phenology between species also resulted in spectral differences between species. SWIR1 and SWIR2 wavelengths are often not included in multispectral sensors but should be considered for species differentiation. Results from this research indicate that wavelengths in SWIR1 and SWIR2 in conjunction with VIS and NIR reflectance can provide differentiation across plant phenologies and, therefore should be considered for use in future sensor technologies for species differentiation.
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Solovchenko, Alexei, Alexei Dorokhov, Boris Shurygin, Alexandr Nikolenko, Vitaly Velichko, Igor Smirnov, Dmitriy Khort, Aleksandr Aksenov, and Andrey Kuzin. "Linking Tissue Damage to Hyperspectral Reflectance for Non-Invasive Monitoring of Apple Fruit in Orchards." Plants 10, no. 2 (February 5, 2021): 310. http://dx.doi.org/10.3390/plants10020310.

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Reflected light carries ample information about the biochemical composition, tissue architecture, and physiological condition of plants. Recent technical progress has paved the way for affordable imaging hyperspectrometers (IH) providing spatially resolved spectral information on plants on different levels, from individual plant organs to communities. The extraction of sensible information from hyperspectral images is difficult due to inherent complexity of plant tissue and canopy optics, especially when recorded under ambient sunlight. We report on the changes in hyperspectral reflectance accompanying the accumulation of anthocyanins in healthy apple (cultivars Ligol, Gala, Golden Delicious) fruits as well as in fruits affected by pigment breakdown during sunscald development and phytopathogen attacks. The measurements made outdoors with a snapshot IH were compared with traditional “point-type” reflectance measured with a spectrophotometer under controlled illumination conditions. The spectra captured by the IH were suitable for processing using the approaches previously developed for “point-type” apple fruit and leaf reflectance spectra. The validity of this approach was tested by constructing a novel index mBRI (modified browning reflectance index) for detection of tissue damages on the background of the anthocyanin absorption. The index was suggested in the form of mBRI = (R640−1 + R800−1) − R678−1. Difficulties of the interpretation of fruit hyperspectral reflectance images recorded in situ are discussed with possible implications for plant physiology and precision horticulture practices.
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Li, Ying, Brian K. Via, Yaoxiang Li, and Guozhong Wang. "Determination of Geographical Origin and Tree Species Using Vis-NIR and Chemometric Methods." Forest Products Journal 72, no. 3 (May 1, 2022): 147–54. http://dx.doi.org/10.13073/fpj-d-22-00011.

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Abstract The variation of wood properties between different geographical origin and tree species has an important influence on end use applications. This study aimed to investigate the feasibility of wood origin and species classification based on visible and near infrared spectroscopy and chemometric methods. The influence of geographical origin on tree species identification also was analyzed. A total of 530 samples with 2 origins and 5 tree species were collected for analysis. The raw reflectance spectra were preprocessed by spectral transformation technique, and nonlinear discrimination models were built by support vector machine (SVM) using various spectral forms. Three algorithms—grid search (GS), genetic algorithm (GA), and particle swarm optimization (PSO)—were applied to optimize the parameters of SVM models, respectively. Regardless of spectral forms and optimization techniques, the prediction accuracy was lower than that of the calibration set for wood origin and tree species identification. Except for reflectance spectra, prediction accuracy of 100 percent was obtained based on SVM in combination with three algorithms for origin discrimination. However, SVM in combination with reflectance spectra and GS technique achieved the best prediction accuracy (93.18%) for tree species identification. These results demonstrated that visible and near infrared spectroscopy combined with chemometric techniques can be used for geographical origin and tree species determination.
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Pandey, Jitendra Kumar, and R. Gopal. "Laser-induced chlorophyll fluorescence and reflectance spectroscopy of cadmium treatedTriticum aestivumL. plants." Spectroscopy 26, no. 2 (2011): 129–39. http://dx.doi.org/10.1155/2011/640232.

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The present study deals with laser-induced chlorophyll fluorescence (LICF) spectra, reflectance spectra and fluorescence induction kinetics (FIK) curves ofTriticum aestivumL. plants treated with different concentrations of cadmium (0.01, 0.1 and 1.0 mM). LICF spectra were recorded in the region of 650–780 nm using violet diode laser (405 nm) and FIK curves were recorded at 685 and 730 nm using red diode laser (635 nm) for excitation. Reflectance spectra were recorded in the region of 400–800 nm using spectrophotometer with an integrating sphere. The fluorescence intensity ratios (FIR) were determined from LICF spectra, vitality index (Rfd) from FIK curves and narrow band vegetation index (NBVI) from reflectance spectra. These parameters along with plant growth parameters and photosynthetic pigment contents were used to analyze the effect of cadmium on wheat plants. The results clearly show that lower concentration of Cd (0.01 mM) shows stimulatory response; whereas higher concentrations (0.1 and 1.0 Mm) are hazardous for plant growth, photosynthetic pigments and photosynthetic activity of wheat plants.
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Dissertations / Theses on the topic "Plant reflectance spectra"

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Johansson, Peter. "Plant Condition Measurement from Spectral Reflectance Data." Thesis, Linköping University, Computer Vision, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59286.

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The thesis presents an investigation of the potential of measuring plant condition from hyperspectral reflectance data. To do this, some linear methods for embedding the high dimensional hyperspectral data and to perform regression to a plant condition space have been compared. A preprocessing step that aims at normalized illumination intensity in the hyperspectral images has been conducted and some different methods for this purpose have also been compared.A large scale experiment has been conducted where tobacco plants have been grown and treated differently with respect to watering and nutrition. The treatment of the plants has served as ground truth for the plant condition. Four sets of plants have been grown one week apart and the plants have been measured at different ages up to the age of about five weeks. The thesis concludes that there is a relationship between plant treatment and their leaves' spectral reflectance, but the treatment has to be somewhat extreme for enabling a useful treatment approximation from the spectrum. CCA has been the proposed method for calculation of the hyperspectral basis that is used to embed the hyperspectral data to the plant condition (treatment) space. A preprocessing method that uses a weighted normalization of the spectrums for illumination intensity normalization is concluded to be the most powerful of the compared methods.

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Bidston, Caroline. "The effects of metal pollution on the spectral reflectance of plants." Thesis, University of Reading, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314319.

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Hollberg, Jens Lothar [Verfasser]. "Detecting Plant Functional Traits of Grassland Vegetation Using Spectral Reflectance Measurements / Jens Lothar Hollberg." Bonn : Universitäts- und Landesbibliothek Bonn, 2018. http://d-nb.info/1160594171/34.

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Sugianto, Biological Earth &amp Environmental Science UNSW. "Multi-angular hyperspectral data and its influences on soil and plant property measurements: spectral mapping and functional data analysis approach." Awarded by:University of New South Wales. Biological, Earth and Environmental Science, 2006. http://handle.unsw.edu.au/1959.4/25531.

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This research investigates the spectral reflectance characteristics of soil and vegetation using multi-angular and single view hyperspectral data. The question of the thesis is ???How much information can be obtained from multi-angular hyperspectral remote sensing in comparison with single view angle hyperspectral remote sensing of soil and vegetation???? This question is addressed by analysing multi-angular and single view angle hyperspectral remote sensing using data from the field, airborne and space borne hyperspectral sensors. Spectral mapping, spectral indices and Functional Data Analysis (FDA) are used to analyse the data. Spectral mapping has been successfully used to distinguish features of soil and cotton with hyperspectral data. Traditionally, spectral mapping is based on collecting endmembers of pure pixels and using these as training areas for supervised classification. There are, however, limitations in the use of these algorithms when applied to multi-angular images, as the reflectance of a single ground unit will differ at each angle. Classifications using six-class endmembers identified using single angle imagery were assessed using multi-angular Compact High Resolution Imaging Spectrometer (CHRIS) imagery, as well as a set of vegetation indices. The results showed no significant difference between the angles. Low nutrient content in the soil produced lower vegetation index values, and more nutrients increased the index values. This research introduces FDA as an image processing tool for multi-angular hyperspectral imagery of soil and cotton, using basis functions for functional principal component analysis (fPCA) and functional linear modelling. FDA has advantages over conventional statistical analysis because it does not assume the errors in the data are independent and uncorrelated. Investigations showed that B-splines with 20-basis functions was the best fit for multi-angular soil spectra collected using the spectroradiometer and the satellite mounted CHRIS. Cotton spectra collected from greenhouse plants using a spectrodiometer needed 30-basis functions to fit the model, while 20-basis functions were sufficient for cotton spectra extracted from CHRIS. Functional principal component analysis (fPCA) of multi-angular soil spectra show the first fPCA explained a minimum of 92.5% of the variance of field soil spectra for different azimuth and zenith angles and 93.2% from CHRIS for the same target. For cotton, more than 93.6% of greenhouse trial and 70.6% from the CHRIS data were explained by the first fPCA. Conventional analysis of multi-angular hyperspectral data showed significant differences exist between soil spectra acquired at different azimuth and zenith angles. Forward scan direction of zenith angle provides higher spectral reflectance than backward direction. However, most multi-angular hyperspectral data analysed as functional data show no significant difference from nadir, except for small parts of the wavelength of cotton spectra using CHRIS. There is also no significant difference for soil spectra analysed as functional data collected from the field, although there was some difference for soil spectra extracted from CHRIS. Overall, the results indicate that multi-angular hyperspectral data provides only a very small amount of additional information when used for conventional analyses.
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Yang, Yang. "Non-contacting techniques for detecting plant drought stress in a closed environment." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1068499233.

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Thesis (Ph. D.)--Ohio State University, 2003.
Title from first page of PDF file. Document formatted into pages; contains xx, 245 p.; also includes graphics. Includes bibliographical references (p. 206-216).
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Chen, Yaw-Nan, and 陳耀南. "The chlorophyll fluorescence and leaf reflectance spectra characteristics among different ecophysiological behavior plants." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/53928819798218020759.

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碩士
國立中興大學
生命科學系
92
In order to understand the chlorophyll fluorescence and leaf reflectance spectral characteristics among species, 12 species with different elevation distribution and temperature adaptation were used. The experiments were made in the campus of National Chung Hsing University (78 m), Hui-Sun Forest Station (800 m), and Tatachia area (2600 m). The results indicated that the PSII efficiency estimated from chlorophyll fluorescence parameters of Pinus taiwanensis (conifer) was lesser influenced by the low temperature and high illumination than those of 2 Miscanthus (C4) species when they were measured in Tatachia. Among 2 Miscanthus species, low elevation origin M. floridulus was more influenced by low temperature than that of high elevation origin M. transomrrisonensis. In Tatachia, transplanted M. floridulus showed lower photochemical reflectance index (PRI) calculated from leaf reflectance spectra in the winter, indicating it required higher xanthophyll cycle to dissipate more excess absorbed energy due to PSII efficiency were more inhibited by low temperature. It also found that no difference of potential of PSII efficiency (Fv/Fm) between flatland and crest line grew P. taiwanensis in Hui-Sun Forest Station. However the PRI of crest line grew P. taiwanensis was lower than that of flatland grown in dry season, probably due to the difference of water condition between 2 habitats. It showed positive correlation between photosynthesis capacity (Pn) and electron transport rate (ETR) for C4 species. This regression coefficient was higher in the species with higher photosynthetic capacity, and no significant correlation could be found in Miscanthus, which showed the lowest Pn among 5 tested C4 species. When merged together of 5 C4 species to statistic analysis, the leaf with higher photosynthetic capacity showed higher portion of absorbed light energy for photochemical (P), and low portion for non-photochemical (D) dissipations. The slope between Pn and P, as well as Pn and D were decreasing with PAR increased. However, the portion of excess energy was not influenced by PAR. From November to December, which daily minimum temperature ranging from 11.6oC to 22.4oC, predawn Fv/Fm of mango (Mangifera indica, cv. Aiwen) and Podocarpus nagi decrease with low temperature, and mango was more influenced than P. nagi. On the contrary, predawn Fv/Fm of Taiwan alder (Alnus formosana) was lesser influenced by temperature. Nevertheless, predawn Fv/Fm showed a strong significant correlation with predawn PRI (PRIp) for statistical analysis when merged together of 3 species. Therefore PRIp could be used as an indicator to estimate the seasonal variation of the potential photochemical efficiency of PSII. Both Fv/Fm and Ф (actual PSII efficiency) showed significant curvilinear correlation with PRI (PRIn) when 3 species were merged together for statistical analysis which data measured at noon. However, more strong correlation between Fv/Fm and ΔPRI (PRIp - PRIn) as well as between Ф and ΔPRI were found. In addition, non photochemical quenching (NPQ) did not correlated with PRIn, but significant correlated with ΔPRI. Thus ΔPRI is suit to indicate the actual dissipation of the excess energy as well as PSII efficiency during illumination. As a conclusion, both chlorophyll fluorescence parameters and leaf reflectance spectra indexes are powerful tools for ecophysiological study.
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Pereira, Maria de Lamares da Piedade e. Teixeira. "Monitoring the impact of soil management on plant spectral reflectance and soil-borne disease resistance." Master's thesis, 2016. http://hdl.handle.net/10348/6801.

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Dissertação de Mestrado em Gestão dos Recursos Naturais
O solo e a sua biodiversidade são o motor de todos os sistemas de produção terrestres e serviços de ecossistemas. A mudança na produção agrícola de extensiva para intensiva tem um efeito negativo profundo nos solos e na sua biodiversidade. A perda de biodiversidade resulta em comunidades do solo menos complexas. Com o aumento da procura dos serviços dos ecossistemas, como o solo, existe a necessidade da melhoria da gestão dos solos e das produções agrícolas. Esta melhoria pode trazer vantagens a nível do desenvolvimento de práticas mais sustentáveis que contribuem para um desenvolvimento económico sustentável. A gestão sustentável de qualquer ecossistema requer, entre outras informações, uma compreensão completa da interação solo-planta para tentar descrever padrões naturais. As plantas produzem substância orgânica através da fotossíntese. A fotosíntese depende da absorção de luz pelos pigmentos fotossintéticos presentes na folha. Portanto, as propriedades óticas da folha são influenciadas pela concentração dos pigmentos fotossintéticos e metabolitos, do seu teor em água e da estrutura e anatomia da folha. A reflectância hiperspectral tem ganho importância comercial e científica, contudo, permanece ainda subdesenvolvida apesar do seu potencial. A deteção remota da vegetação é uma boa ferramenta, pois pode extrapolar escalas de tempo, e é cada vez mais utilizada para perceber interações planta-solo. Sabe-se que o sinal de reflectância é sensível a mudanças abióticas e bióticas, mas ainda há um longo caminho a percorrer. Consequentemente, foi realizado durante nove semanas um bioensaio com duas culturas diferentes, a Beterraba (Beta vulgaris) e o Milho (Zea mays). Foram plantadas em três diferentes tipos de gestão do solo e aplicados seis tipos de tratamentos. Os tratamentos aplicados foram: o fungo Rhizoctonia solani, o nemátode Pratylenchus penetrans, a radiação gama, os nutrientes, e o fungo R. solani com nutrientes e um controlo. Os tipos de gestão que foram aplicados foram o solo Biológico, os fertilizantes artificiais e Fertelizantes orgânicos. No total foram consideradas 3650 plantas. Os dados da refletância espetral foram obtidos com um espectrómetro de campo ASD plant-probe e clip-foliar. Um objetivo deste estudo consistiu em monitorizar a refletância espetral das folhas das duas espécies durante o período experimental. Os dados espetrais foram analisados utilizando índices de vegetação. Os efeitos do biota do solo foram analizados numa análise multivariada ANOVA com os fatores, espécie de planta, tipos de solo e tratamentos. A biomassa total de patogénicos tende a aumentar quanto mais intensiva for a prática agricola. No solo Biológico observou-se uma intensificação da cor verde da planta nas duas espécies, com o aumento da disponibilidade de nutrientes. A adição de fertelizante pode ter influenciado a resistência das plantas às doenças do solo. A menor biomassa foi encontrada no tratamento com radiação gama (estéril), sugerindo que o biota do solo influenciou o desempenho da planta. O melhor tipo de gestão do solo teve um efeito positivo no crescimento das plantas. As melhores práticas agricolas permitem uma supressão das doenças inoculadas. Foi demonstrado que o espetro da planta difere quando é induzido stresse e também consoante o tipo de gestão do solo. A melhor gestão agrícola foi considerada a Biológica.
Soil and soil biodiversity are the driving force of all the terrestrial production systems and ecosystem services. The intensification of agriculture production and shifts from extensive crop rotation have, regularly, a profound negative effect on soils and their biodiversity. Biodiversity losses result in less complex soil communities. The increasing demand of soil ecosystem implies the improvement of soil and crop management, and it’s a key opportunity for supporting sustainable economic development. The sustainable management of any ecosystem requires, amongst other information, a thorough understanding of plant-soil feedback attempting to describe natural patterns and relations between the plants and their environment. Plants produce organic substances by photosynthesis. Photosynthesis depends upon the absorption of light by pigments, as chlorophyll-a among other accessory pigments, in the leaves of the plants. Therefore, leaf optical properties are influenced by the concentration of the photosynthetic pigments, metabolites, water content, leaf structure and leaf anatomy. Hyperspectral reflectance in remote sensing has gained scientific and commercial importance but still remains underdeveloped despite its potential. Vegetation remote sensing is a great tool, as it can extrapolate to synoptic scales and time sequences can be acquired. It is increasingly used for measurements of agricultural crop condition and also for plant-soil interactions. It is known that reflectance signal is sensitive to abiotic changes, but concerning biotic changes, there are still several limitations. Therefore, was conducted a 9 weeks greenhouse bioassay with two different crops, Sugar beet (Beta vulgaris) and Corn (Zea mays), three different types of soil management and six different treatments were applied. The treatments applied were: the fungus Rhizoctonia solani, the nematode Pratylenchus penetrans, the Gamma radiation, the nutrients, the R. solani with nutrients and a control treatment. The types of management were the Biologic, the Artificial Fertilizer and the Manure. In total were 3650 plants. Spectral reflectance data were collected with an ASD Fieldspec 3 spectrometer with an ASD plant-probe and leaf-clip device attached. One of the objectives of the measurement was to monitor the differences between leaf reflectance over time. The spectral data was analyzed using vegetation indices. The effects of soil biota were analyzed in a multivariate ANOVA analysis with plant species, soil regime and soil treatment. The total biomass of the pathogens increase with a more intensive agriculture and shoot biomass in both plant species increased with disposal of the nutrient supply in the Biologic soil. The application of manure compost that is rich in nitrogen may have reduced soil-borne diseases. The lowest biomass was found in the sterilized treatments suggesting that the soil biota has influenced the plant performance. The best soil management had positive effect in growth of the plants. Disease suppression can be influenced by management practices. It was demonstrated that plant spectral signatures changes due induced stress and soil type. The best soil regime overall in this study case was considered the Biologic type.
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Prasad, Bishwajit. "The potential for using canopy spectral reflectance as an indirect selection tool for yield improvement in winter wheat." 2006. http://digital.library.okstate.edu/etd/umi-okstate-1915.pdf.

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Hwang, Mon-Yuan, and 黃盟元. "Studies on reflectance spectra of plants leaves and the related physiological characters in different ecological habitats and seasons." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/80327596581588152296.

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Axness, Daniel S. "Estimating ground cover via spectral data." Thesis, 1991. http://hdl.handle.net/1957/36337.

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Potato ground cover and spectral data were measured in the Columbia Basin during the 1990 growing season. Three spectral were correlated with ground cover; normalized difference, near infrared-red ratio, and the first derivative of the spectral curve at 750 nm. All models were statistically significant at the 99% level. Normalized was most correlated followed by the near infrared-red ratio, and the first derivative of the spectral curve at 750 nm.
Graduation date: 1992
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Books on the topic "Plant reflectance spectra"

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Ripple, William J. Spectral reflectance relationships to leaf water stress. Corvallis, Or: Environmental Remote Sensing Applications Laboratory - ERSAL, Oregon State University, 1986.

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M, Ager C., Power M. S, and Geological Survey (U.S.), eds. Spectral reflectance changes in greenhouse-grown metal-doped plants. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1988.

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Axness, Daniel S. Estimating ground cover via spectral data. 1991.

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Chance, Kelly, and Randall V. Martin. Basic Solar and Planetary Properties. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199662104.003.0001.

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Basic properties of the Sun, the Earth and its atmosphere, other solar system atmospheres, and extrasolar planetary atmospheres are introduced here to provide background and context for the detailed study of the spectroscopy and radiative transfer of planetary atmospheres. Solar structure is described, including the solar cycle and variability, and a reference solar irradiance is presented. The Earth’s orbit, the seasons, and the ecliptic plane are introduced. The properties of hydrostatic equilibrium, albedo, and spectral reflectance are described. Earth’s atmospheric composition, including aerosols and gases, is summarized. Other atmospheres in the solar system are described and the growing field of extrasolar planets detection and characterization introduced.
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Book chapters on the topic "Plant reflectance spectra"

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Meireles, José Eduardo, Brian O’Meara, and Jeannine Cavender-Bares. "Linking Leaf Spectra to the Plant Tree of Life." In Remote Sensing of Plant Biodiversity, 155–72. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_7.

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AbstractEvolutionary trees recount the history of how biological diversity came to be and how evolution gave rise to the incredible variation in plant form and function that can be captured by spectral reflectance. Understanding plant spectra in light of evolution is thus important for assessing biodiversity and critical for explaining how spectral diversity is generated. Here, we focus on leaf spectra and how they are linked to the plant tree of life. We review what evolutionary trees (phylogenies) are and how to interpret them. We then describe how to model the evolution of quantitative traits, discuss which evolutionary processes are involved, and explain specific concepts and metrics, such as phylogenetic signal and evolutionary rates, and how they can be applied to reflectance spectra. Next, we describe a framework that links phylogenies and leaf spectra by coupling models of evolution and radiative transfer models. In doing so, we review some of the challenges of subjecting spectra to evolutionary analyses. We then discuss how spectra can help us to understand leaf evolution and to differentiate plant taxa at different phylogenetic scales from populations to lineages, advancing our potential to remotely detect biodiversity.
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Ustin, Susan L., and Stéphane Jacquemoud. "How the Optical Properties of Leaves Modify the Absorption and Scattering of Energy and Enhance Leaf Functionality." In Remote Sensing of Plant Biodiversity, 349–84. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_14.

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AbstractLeaves absorb, scatter, and transmit sunlight at all wavelengths across the visible, near-infrared, and shortwave-infrared spectrum. The optical properties of a leaf are determined by its biochemical and biophysical characteristics, including its 3-D cellular organization. The absorption and scattering properties of leaves together create the shape of their reflectance spectra. Terrestrial seed plant species share similar physiological and metabolic processes for fluxes of gases (CO2, O2, H2O), nutrients, and energy, while differences are primarily consequences of how these properties are distributed and their physical structures. Related species generally share biochemical and biophysical traits, and their optical properties are also similar, providing a mechanism for identification. However, it is often the minor differences in spectral properties throughout the wavelengths of the solar spectrum that define a species or groups of related species. This chapter provides a review and summary of the most common interactions between leaf properties and light and the physical processes that regulate the outcomes of these interactions.
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Klančnik, Katja, Igor Zelnik, Primož Gnezda, and Alenka Gaberščik. "Do Reflectance Spectra of Different Plant Stands in Wetland Indicate Species Properties?" In The Role of Natural and Constructed Wetlands in Nutrient Cycling and Retention on the Landscape, 73–86. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08177-9_6.

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Carter, Gregory A., and Lee Estep. "General Spectral Characteristics of Leaf Reflectance Responses to Plant Stress and Their Manifestation at the Landscape Scale." In From Laboratory Spectroscopy to Remotely Sensed Spectra of Terrestrial Ecosystems, 271–93. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-1620-8_12.

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Hummel, John W., and Jing Yu. "Spectral Reflectance Pattern Recognition for Segmenting Corn Plants and Weeds." In Proceedings of the Fourth International Conference on Precision Agriculture, 1523–36. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1999.precisionagproc4.c54b.

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Kong, Weiping, Yinli Bi, Wenjiang Huang, Lingli Tang, Chuanrong Li, and Lingling Ma. "Nondestructive Evaluation of Inoculation Effects of AMF and Bradyrhizobium japonicum on Soybean under Drought Stress From Reflectance Spectroscopy." In Soybean for Human Consumption and Animal Feed. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.88673.

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Precise estimation of leaf chlorophyll content (LCC) and leaf water content (LWC) of soybean, using remote sensing technology, provides a new avenue for the nondestructive evaluation of inoculation effects of arbuscular mycorrhizal fungi (AMF) and Bradyrhizobium japonicum (BJ) on soybean growth condition. In this study, a series of pot experiments were conducted in the greenhouse, soybean inoculated with Glomus intraradices (G.i, one of AMF species), G.i and BJ, and non-inoculation were planted under drought stress (DS) and normal irrigation (NI) conditions. Leaf spectra and LCC and LWC were measured on the 28th and 56th days after inoculation. Two new simple ratio (SR) indices, derived from the first derivative spectral reflectance at λ1 nm (Dλ1) and the raw spectral reflectance at λ2 nm (Rλ2), were developed to estimate LCC and LWC. The results indicate that under DS, plants inoculated with G.i had higher LCC and LWC than the non-inoculated plants, followed by the counterparts co-inoculated with G.i and BJ. Linear estimation models, established by the D650/Rred edge and D1680/R680, achieved great improved accuracy for quantifying LCC and LWC of soybean under inoculation and drought stress treatments, with determination of coefficient of 0.63 and 0.76, respectively.
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Eguchi, Hiromi. "DIGITAL PROCESSING OF PLANT IMAGES SELECTED BY SPECTRAL CHARACTERISTICS OF REFLECTANCE FOR EVALUATION OF GROWTH." In Measurement Techniques in Plant Science, 361–72. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-12-330585-5.50024-4.

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Kapp Jr., Claudio, Eduardo Fávero Caires, and Alaine Margarete Guimarães. "Discriminating Biomass and Nitrogen Status in Wheat Crop by Spectral Reflectance Using ANN Algorithms." In Innovations and Trends in Environmental and Agricultural Informatics, 156–72. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5978-8.ch007.

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Precision agriculture has the goal of reducing cost which is difficult when it is related to fertilizer application. Nitrogen (N) is the nutrient absorbed in greater amounts by crops and the N fertilizer application presents significant costs. The use of spectral reflectance sensors has been studied to identify the nutritional status of crops and prescribe varying N rates. This study aimed to contribute to the determination of a model to discriminating biomass and nitrogen status in wheat through two sensors, GreenSeeker and Crop Circle, using the resilient propagation and backpropagation artificial neural networks algorithms. As a result, a strong correlation to the sensor readings with the aboveground biomass production and N extraction by plants was detected. For both algorithms a satisfactory model for estimating wheat dry biomass production was established. The best backpropagation and resilient propagation models defined showed better performance for the GreenSeeker and Crop Circle sensors, respectively.
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Parra, Javier Lo, Jacinto Garrido Velarde, Jesus Barrena González, and Manuel Pulido Fernández. "Ecohydrological Behavior of Semiarid Ecosystems of Chile in Present and Future Climate Scenarios." In Practice, Progress, and Proficiency in Sustainability, 60–74. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7391-4.ch005.

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Semiarid ecosystems of Chile with Mediterranean climate support high demographic rates and maintain important economies associated with the productivity of the natural environment; however, they strongly depend on the water availability and their future is compromised by climate variations. This study tries to define the role of hydrological variables on the growth of herbaceous biomass under the current climate and under future weather variations. For this, the authors used meteorological stations which let them estimate the water balance at plot scale and spectral reflectance sensors which let them follow the dynamics of the NDVI of herbaceous plants. In this context, the NDVI value was about 0.7, which means approximately 3700 kg DM ha1. However, under the worst-case climate change scenarios (RCP 8.5), annual precipitation showed a reduction of up to 31.6% regarding the present period. In this situation, the NDVI could be reduced up to 80% respect to the current situation. Thus, if climate changes to its worst scenario, it could threaten the maintenance and productivity of these ecosystems.
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Rango, Albert, and Jerry Ritchie. "Applications of Remotely Sensed Data from the Jornada Basin." In Structure and Function of a Chihuahuan Desert Ecosystem. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195117769.003.0019.

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Like other rangelands, little application of remote sensing data for measurement and monitoring has taken place within the Jornada Basin. Although remote sensing data in the form of aerial photographs were acquired as far back as 1935 over portions of the Jornada Basin, little reliance was placed on these data. With the launch of Earth resources satellites in 1972, a variety of sensors have been available to collect remote sensing data. These sensors are typically satellite-based but can be used from other platforms including ground-based towers and hand-held apparatus, low-altitude aircraft, and high-altitude aircraft with various resolutions (now as good as 0.61 m) and spectral capabilities. A multispectral, multispatial, and multitemporal remote sensing approach would be ideal for extrapolating ground-based point and plot knowledge to large areas or landscape units viewed from satellite-based platforms. This chapter details development and applications of long-term remotely sensed data sets that are used in concert with other long-term data to provide more comprehensive knowledge for management of rangeland across this basin and as a template for their use for rangeland management in other regions. In concert with the ongoing Jornada Basin research program of ground measurements, in 1995 we began to collect remotely sensed data from ground, airborne, and satellite platforms to provide spatial and temporal data on the physical and biological state of basin rangeland. Data on distribution and reflectance of vegetation were measured on the ground along preestablished transects with detailed vegetation surveys (cover, composition, and height); with hand-held and yoke-mounted spectral and thermal radiometers; from aircraft flown at different elevations with spectral and thermal radiometers, infrared thermal radiometers, multispectral video, digital imagers, and laser altimeters; and from space with Landsat Thematic Mapper (TM), IKONOS, QuickBird, Terra/Aqua, and other satellite-based sensors. These different platforms (ground, aircraft, and satellite) allow evaluation of landscape patterns and states at different scales. One general use of these measurements will be to quantify the hydrologic budget and plant response to changes in components in the water and energy balance at different scales and to evaluate techniques of scaling data.
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Conference papers on the topic "Plant reflectance spectra"

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Xu, Tingyan, Taotao Zhu, Ting Yang, Yanxin Guo, Jingqi Xu, Wandong Chang, Siyi Fang, and Kangkang Zhu. "Research advances in reflectance spectra of plant leafs." In Fourth Seminar on Novel Optoelectronic Detection Technology and Application, edited by Weiqi Jin and Ye Li. SPIE, 2018. http://dx.doi.org/10.1117/12.2314999.

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KARLOVSKA, Amanda, Inga GRĪNFELDE, Ina ALSIŅA, Gints PRIEDĪTIS, and Daina ROZE. "PLANT REFLECTED SPECTRA DEPENDING ON BIOLOGICAL CHARACTERISTICS AND GROWTH CONDITIONS." In Rural Development 2015. Aleksandras Stulginskis University, 2015. http://dx.doi.org/10.15544/rd.2015.045.

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Sustainable and economically based forestry needs modern inventory and monitoring techniques. One of the most common technologies for identification of forest tree species and monitoring of forest growth conditions is the hyperspectral remote sensing. This technology gives an opportunity to economize human resources and time for data collecting and processing. The spectral behaviour of plant leaves depends on number of factors, including environmental background. The aim of this study was to assess the tree reflectance spectra in relation to the growth conditions to take into account potential differences for increasing precision of species identification in Latvian forests and for estimating of forest growth conditions. Remote sensing data were obtained using a specialized aircraft (Pilatus PC-6), which is equipped with a high-performance airborne VNIR pushbroom hyperspectral system (AisaEAGLE). The study area was flown at 1000 m altitude. Data was recorded in the 400–970 nm spectral range, spectral resolution was 3.3 nm, ground resolution 0.5 m. Data processing consisted of manually selecting trees with a recognizable tree crowns in the airborne images. Tree centres were adjusted by putting them in the accurate position according to the situation in aerial photography. All trees with a diameter at breast height DBH of more than 5 cm were measured and for each tree coordinates, its species, height, DBH, crown width and length were recorded. Differentially corrected Global Positioning System measurements were used to determine the position of each plot centre. Data from different hyperspectral bands were compared using ANOVA at confidence level 95 %. Four species: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), silver birch (Betula pendula Roth), and European aspen (Populus tremula L.) – were examined in distinct forest site types. The spectral response of studied species was 1) different between species and 2) different between site types within each species, correlating with soil fertility gradient and soil moisture gradient. Differences between species occurred most in the intensity of reflected electromagnetic radiation rather than distinctive locations of maximums or minimums in spectrum curve, and near infrared (NIR) region of spectrum showed more differences between species than visible light zone. Most informative wavebands for distinguishing differences between site types were 805 nm and 644 nm.
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Shi, Runhe, Huifang Zhang, Juan Sun, Wei Gao, Dafang Zhuang, and Zheng Niu. "Responses of plant biochemical substances to reflectance spectra at leaf and canopy scales." In Optical Engineering + Applications, edited by Wei Gao and Hao Wang. SPIE, 2008. http://dx.doi.org/10.1117/12.794088.

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Shahrimie, M. A. Mohd, Puneet Mishra, Stien Mertens, Stijn Dhondt, Nathalie Wuyts, and Paul Scheunders. "Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging." In 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2016. http://dx.doi.org/10.1109/whispers.2016.8071753.

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Sahba, Kaveh, Sreten Askraba, and Kamal E. Alameh. "Photonics-based Spectral Reflectance Sensor for Plant Discrimination." In 2007 the Joint International Conference on Optical Internet (COIN) and Australian Conference on Optical Fibre Technology (ACOFT). IEEE, 2007. http://dx.doi.org/10.1109/coinacoft.2007.4519146.

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Sahba, Kaveh, Sreten Askraba, and Kamal E. Alameh. "Photonics-based Spectral Reflectance Sensor for Plant Discrimination." In 2006 Australian Conference on Optical Fibre technology (ACOFT). IEEE, 2007. http://dx.doi.org/10.1109/acoft.2007.4516239.

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Makino, Toshiro, and Hidenobu Wakabayashi. "Experimental Verification of Kirchhoff’s Thermal Radiation Law on Surfaces With Emittance Spectra Characterized by Optical Interference Phenomena." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22718.

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This paper discusses Kirchhoff’s law on thermal radiation. The logic of derivation of the law is reconsidered, first. Then, spectra of normal emittance εN and normal incidence hemispherical reflectance RNH are measured on surfaces whose microstructure changes in a non-equilibrium experimental system to examine the validity of the complementary relation between εN and RNH, which is the suggestion of Kirchhoff’s law. As the results of the examination, it is illustrated experimentally on a variety of surfaces that the complementary relation is valid within an experimental uncertainty. Provided this conclusion is admitted, the followings are suggested. If a surface is designed so that it does not reflect a narrow spectral region of radiation to any direction and reflects the other spectral regions of radiation much over the hemisphere, then the surface can be a new spectrally-functional emitter of radiation. It is also suggested that thermal radiation emitted at a surface is considered as the emission of plane waves at the surface rather than as the emission of spherical waves by electric dipoles.
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Bao, Hua, and Xiulin Ruan. "Radiative Properties of GaAs From First Principles Calculations." In ASME 2008 Heat Transfer Summer Conference collocated with the Fluids Engineering, Energy Sustainability, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/ht2008-56341.

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Spectral reflectance of GaAs from infrared (IR) to ultra-violet (UV) bands is calculated from first principles. We first calculate the spectral dielectric function which is determined by the response of GaAs to external electromagnetic field. Two mechanisms exist for different wavelengths, namely, phonon absorption in the far-IR region and the electronic absorption in the near-IR to UV region. With plane-wave pseudopotential method, we determined the dielectric function of GaAs with the the initial structure as the only input. For the far-IR region, phonon calculations are carried out. By analyzing the phonon modes, low-frequency dielectric constant is calculated. For the near-IR to UV band, the electronic band structure of GaAs is calculated, and the imaginary part of the dielectric function is determined from the band structure using Fermi’s Golden rule. The real part of spectral dielectric function is then derived from Kramer-Kronig transformation. The reflectance is then calculated using Maxwell’s equations.
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Akbarzadeh, Saman, Selam Ahderom, and Kamal Alameh. "Application of spectral reflectance for increasing plant discrimination speed in precision agriculture." In 2019 IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT and AI (HONET-ICT). IEEE, 2019. http://dx.doi.org/10.1109/honet.2019.8907994.

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Velichkova, Kalinka, and Dora Krezhova. "SENSITIVITY OF REMOTELY-SENSED SPECTRAL REFLECTANCE TO BIOPHYSICAL VARIABLES OF PLANTS." In RAD Conference. RAD Association, 2017. http://dx.doi.org/10.21175/radproc.2017.56.

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Reports on the topic "Plant reflectance spectra"

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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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Agassi, Menahem, Michael J. Singer, Eyal Ben-Dor, Naftaly Goldshleger, Donald Rundquist, Dan Blumberg, and Yoram Benyamini. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7586479.bard.

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The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid, semi-arid regions, e.g. much of Israel and vast area in US, where water is a limiting factor for crop production. A major reason for runoff of rain and overhead irrigation water is the structural crust that is generated over a bare soils surface during rainfall or overhead irrigation events and reduces its infiltration rate (IR), considerably. IR data is essential for predicting the amount of percolating rainwater and runoff. Available information on in situ infiltration rate and crust strength is necessary for the farmers to consider: when it is necessary to cultivate for breaking the soil crust, crust strength and seedlings emergence, precision farming, etc. To date, soil IR is measured in the laboratory and in small-scale field plots, using rainfall simulators. This method is tedious and consumes considerable resources. Therefore, an available, non-destructive-in situ methods for soil IR and soil crusting levels evaluations, are essential for the verification of infiltration and runoff models and the evaluation of the amount of available water in the soil. In this research, soil samples from the US and Israel were subjected to simulated rainstorms of increasing levels of cumulative energies, during which IR (crusting levels) were measured. The soils from the US were studied simultaneously in the US and in Israel in order to compare the effect of the methodology on the results. The soil surface reflectance was remotely measured, using laboratory and portable spectrometers in the VIS-NIR and SWIR spectral region (0.4-2.5mm). A correlation coefficient spectra in which the wavelength, consisting of the higher correlation, was selected to hold the highest linear correlation between the spectroscopy and the infiltration rate. There does not appear to be a single wavelength that will be best for all soils. The results with the six soils in both countries indeed showed that there is a significant correlation between the infiltration rate of crusted soils and their reflectance values. Regarding the wavelength with the highest correlation for each soil, it is likely that either a combined analysis with more then one wavelength or several "best" wavelengths will be found that will provide useful data on soil surface condition and infiltration rate. The product of this work will serve as a model for predicting infiltration rate and crusting levels solely from the reflectance readings. Developing the aforementioned methodologies will allow increased utilization of rain and irrigation water, reduced runoff, floods and soil erosion hazards, reduced seedlings emergence problems and increased plants stand and yields.
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3

Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.
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