In silicoassessment of environmental factors affecting the spectral signature ofC4plants in the visible domain

Baranoski, Gladimir V. G.; Kimmel, Bradley W.; Chen, Tenn F.; Yim, Daniel

doi:10.1080/01431161.2010.550949

Cited by 10 publications

(21 citation statements)

References 61 publications

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“…These values were derived from data available in the literature and also borne out by observations of cross sections of maize leaves. 7 The modeled radiometric quantities for the wilted specimens were obtained considering a 25% water reduction accompanied by minor changes in the pigment contents, as reported in the experiments by Maracci et al, 3 involving maize leaves under moderate water stress. Measurements performed by Wolley 38 on maize leaves indicate that such a water content reduction is followed by approximately a 20% reduction in thickness and a 2% reduction in area.…”

Section: Specimens' Characterization Datamentioning

confidence: 99%

“…Again, it is important to note that the modeled (using the ABM-U) reflectance and transmittance curves obtained for the baseline specimens considered in this investigation closely approximate their measured LOPEX counterparts as depicted in previous works. 7,26 The LOPEX biochemical data, namely the contents of the main leaf absorbers in the visible range, used to characterize the baseline (fresh) specimens are presented in Table 1. The remaining LOPEX data employed in the characterization of these specimens, namely thickness, fresh weight, and dry weight, are presented in Table 2.…”

Section: Specimens' Characterization Datamentioning

confidence: 99%

“…It is important to note that this model has been extensively evaluated through quantitative and qualitative comparisons of modeled results with actual measured data. 7,26,28 Within the ABM-U formulation, a ray interacting with a given leaf specimen can be associated with any selected wavelength within the spectral regions of interest. Hence, ABM-U can provide reflectance and transmittance quantities with different spectral resolutions.…”

Section: Simulation Framework Overviewmentioning

confidence: 99%

“…Among these limitations, one can highlight the difficulties of performing in situ measurements requiring the control of a large number of biophysical variables. In the case of plants, it has been demonstrated that computer simulations paired with measured data can be effectively employed in the investigation of open questions involving their physiological responses to changes in water soil levels, 7 as well as the effects of limited water availability on their growing process. 24 In this paper, which is an updated and extended version of a conference presentation, 25 we employ computer simulations to assess whether variations on the visible spectral signatures of maize leaves can be effectively employed in the detection and monitoring of RWC changes under both in vitro and in vivo conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Accordingly, it has been proposed that a similar sequence of events may occur in maize leaves under moderate in vivo water stress and neutral illumination conditions. 7 More specifically, an elevation of cytosolic Ca 2þ , induced by water deficit signals, might provide a signaling pathway to trigger the migration of chloroplasts away from the walls of the cells, which, in turn, might result in a more homogeneous distribution of these chlorophyllcontaining organelles. Such a distribution pattern increases the probability of light detour effects and, consequently, light absorption in the visible (photosynthetic) domain.…”

Section: Introductionmentioning

confidence: 99%

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Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain

Baranoski

Leeuwen

2017

J. Appl. Remote Sens

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, "Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain," J. Appl. Remote Sens. 11(3), 036025 (2017), doi: 10.1117/1.JRS.11.036025. Abstract. The reliable detection and monitoring of changes in the water status of crops composed of plants like maize, a highly adaptable C4 species in large demand for both food and biofuel production, are longstanding remote sensing goals. Existing procedures employed to achieve these goals rely predominantly on the spectral signatures of plant leaves in the infrared domain where the light absorption within the foliar tissues is dominated by water. It has been suggested that such procedures could be implemented using subsurface reflectance to transmittance ratios obtained in the visible (photosynthetic) domain with the assistance of polarization devices. However, the experiments leading to this proposition were performed on detached maize leaves, which were not influenced by the whole (living) plant's adaptation mechanisms to water stress. In this work, we employ predictive simulations of light-leaf interactions in the photosynthetic domain to demonstrate that the living specimens' physiological responses to dehydration stress should be taken into account in this context. Our findings also indicate that a reflectance to transmittance ratio obtained in the photosynthetic domain at a lower angle of incidence without the use of polarization devices may represent a cost-effective alternative for the assessment of water stress states in maize crops. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Specimens' Characterization Datamentioning

confidence: 99%

Section: Specimens' Characterization Datamentioning

confidence: 99%

Section: Simulation Framework Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain

Baranoski

Leeuwen

2017

J. Appl. Remote Sens

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Implications of climate change for the sugarcane industry

Linnenluecke

Nucifora

Thompson

2017

WIREs Climate Change

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This review was undertaken to draw together research on how climate change impacts sugarcane production, and to assess the implications of climate change for the sugarcane industry, as well as possible response options. Much of the extant research examines how changes in climate lead to changes in primary production; however, few studies consider how climate change translates into industry-wide impacts and economic consequences across the sugarcane value chain. Of the 90 studies we reviewed (published as journal articles, proceedings, and book chapters), 61 assess observed and/or projected impacts of climate change on sugarcane production. These studies reach largely different conclusions regarding how increases in air temperature or atmospheric carbon dioxide levels impact sugarcane production. These mixed results can be attributed to differences between the studies in terms of methods, time frames, and growing regions, which all limit cross-study comparability. A total of 17 studies focus on the adaptation to observed and/or projected impacts of climate change, such as changed management procedures or farming practices, but there is limited evidence regarding successful adaptation outcomes. In addition, a separate stream of papers discusses mitigating energy use and greenhouse gas emissions in the sugarcane production process, often with a view to reducing environmental impacts. Our review concludes by outlining the pathways for future research, highlighting that further insights are needed in particular regarding the economic consequences of climate change for the sugarcane industry. © 2017 Wiley Periodicals, Inc. How to cite this article:WIREs Clim Change 2018, 9:e498. doi: 10.1002/wcc.498 INTRODUCTION T he amount of sugarcane produced worldwide is over four times that produced in 1965 and has now reached over 2 billion tons globally.1 The industry contributes significantly to gross domestic product in major sugarcane producing economies such as Brazil, India, and China. From the late 1990s onward, driven by growing concern about climate change and its potential economic consequences for the agricultural sector, researchers began to study the impacts of climate change on sugarcane production to better understand how projected changes in variables such as air temperature, rainfall, and atmospheric carbon dioxide (CO 2 ) concentration influence sugarcane production. [2][3][4][5][6][7] This has created a body of knowledge of how changes in climate lead to changes in the primary production of sugarcane. However, there are few studies that focus on how climate change translates into industry-wide impacts across the sugarcane value chain.8-10 Industry stakeholders of 34and researchers have therefore started to call for a better understanding not only of how climate change impacts agricultural production, but also of the possible economic consequences resulting from climate change for specific agricultural industries. 11,12This review was undertaken to draw together research on how climate change impacts sugarcane...

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Assessing the Effects of Nutrient Stress on the Red to Far-Red Ratios of Light Transmitted by Unifacial Plant Leaves

Baranoski

2020

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

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In silicoassessment of environmental factors affecting the spectral signature ofC₄plants in the visible domain

Cited by 10 publications

References 61 publications

Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain

Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain

Implications of climate change for the sugarcane industry

Assessing the Effects of Nutrient Stress on the Red to Far-Red Ratios of Light Transmitted by Unifacial Plant Leaves

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