Reflectance studies of healthy, maize dwarf mosaic virus-infected, and Helminthosporium maydis-infected corn leaves

Ausmus, B.S.; Hilty, J. W.

doi:10.1016/0034-4257(71)90080-0

Cited by 55 publications

(9 citation statements)

References 3 publications

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“…Lorenzen and Jensen [ 35 ] studied the reflectance changes caused by fungal infection on cereal leaves, and found it increased in the visible region. On the other hand, a similar study by Ausmus and Hilty [ 36 ] showed considerably lower NIR reflection on infected plants. The present research detected that an analogous reduction in the reflectance in the VNIR spectrum was in the spectra of the diseased thistles ( Figure 8 ).…”

Section: Discussionmentioning

confidence: 78%

Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination

Tamouridou

Pantazi

Alexandridis

et al. 2018

Sensors

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Microbotryum silybum, a smut fungus, is studied as an agent for the biological control of Silybum marianum (milk thistle) weed. Confirmation of the systemic infection is essential in order to assess the effectiveness of the biological control application and assist decision-making. Nonetheless, in situ diagnosis is challenging. The presently demonstrated research illustrates the identification process of systemically infected S. marianum plants by means of field spectroscopy and the multilayer perceptron/automatic relevance determination (MLP-ARD) network. Leaf spectral signatures were obtained from both healthy and infected S. marianum plants using a portable visible and near-infrared spectrometer (310–1100 nm). The MLP-ARD algorithm was applied for the recognition of the infected S. marianum plants. Pre-processed spectral signatures served as input features. The spectra pre-processing consisted of normalization, and second derivative and principal component extraction. MLP-ARD reached a high overall accuracy (90.32%) in the identification process. The research results establish the capacity of MLP-ARD to precisely identify systemically infected S. marianum weeds during their vegetative growth stage.

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Section: Discussionmentioning

confidence: 78%

Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination

Tamouridou

Pantazi

Alexandridis

et al. 2018

Sensors

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“…One of the earliest studies examining the spectral responses of a diseased crop is credited to Colwell (1956), and since then other research has been conducted by adopting ground-based radiometry, for example, with Maize dwarf mosaic virus-infected and Helminthosporium maydis-infected corn leaves (Ausmus & Hilty, 1972); barley infected by cereal powdery mildew (Lorenzen & Jensen, 1989); leaf spectral reflectance for powdery mildew disease in golden euonymus (Carter, 1993); bean infected by Botrytis fabae (Malthus & Madeira, 1993); and powdery mildew and take-all disease in wheat (Graeff et al, 2006). Studies relating the spectral responses of diseased crop canopies with ground-based radiometry are essential as a scientific base to the use of satellite multispectral scanner data to detect and monitor plant disease.…”

Section: Experimental Approachesmentioning

confidence: 99%

Diseases in tropical and plantation crops as affected by climate changes: current knowledge and perspectives

Ghini¹,

2011

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Tropical and plantation crops include important crops for food security and alternative energy resources. Even so, there are few studies on the impact of climate change on diseases of these crops. Findings from previous studies concerning some climate-change effects on diseases of coffee, sugarcane, eucalyptus, cassava, citrus, banana, pineapple, cashew, coconut and papaya have been summarized to provide a context. By reviewing available methods to evaluate the impact of climate change on diseases of tropical and plantation crops, we present trends for some diseases and their management strategies, identify critical gaps in knowledge, and suggest experimental and analytical approaches to advance knowledge. As the projected climate conditions will probably vary greatly in the future from continent to continent and from developed to developing countries, studies must be conducted under tropical regions considering their specific environmental conditions. Multifactor studies under realistic field situations, such as free air CO 2 enrichment with increasing CO 2 and O 3 concentrations incorporating spectral reflectance measures in situ for realistic assessment of plant growth, are a way forward. Effects of a changing climate on chemical and biological controls are discussed in the context of changing global outlook on environmental demands for the future.

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“…A pioneering study was done by Ausmus and Hilty, [81] where spectral reflectance (400-2700 nm) was used to evaluate the presence of fungi Helminthosporium maydis and of the maize dwarf mosaic virus (MDMV), by taking into account the injuries and colour changes in the maize leaves. Their results revealed that healthy, MDMV infected, and H. maydis-infected leaves could be spectrally differentiated in the NIR range (800-2600 nm), especially at early infection stages when symptoms are not yet visible by direct observation (reflectivity: healthy leaves > MDMV-infected leaves > H. maydis-infected leaves).…”

Section: Microbial Contamination In Agricultural Cropsmentioning

confidence: 99%

Evaluation of biological contaminants in foods by hyperspectral imaging: A review

Mantilla

Jara

Yimer

2017

International Journal of Food Properties

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Responding to the ever-growing concern about safe foods and security, the food industries are forced to seek an emerging technology capable of detecting and quantifying contaminations, especially those of biological origin. Among the different emerging technologies, hyperspectral imaging is considered a good alternative as it can be easily applied at all steps of the food production process and is a non-destructive technique. This paper reviews targeted analytical applications of hyperspectral imaging in monitoring biological contaminants in food. First, traditional techniques for detection of biological contaminants in foods are presented, where disadvantages for practical applications are highlighted and explained in detail. Second, prominent applications of hyperspectral imaging from the last decade to food safety and quality assessment are reviewed, specifically focusing on both deteriorative and pathogenic microorganisms, microbial toxins, and parasites; whether acting individually or collectively in spoiling food products and/or represent a health risk to the consumers. Finally, relevant current and future challenges, advantages and disadvantages of hyperspectral imaging applications are briefly examined.

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Reflectance studies of healthy, maize dwarf mosaic virus-infected, and Helminthosporium maydis-infected corn leaves

Cited by 55 publications

References 3 publications

Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination

Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination

Diseases in tropical and plantation crops as affected by climate changes: current knowledge and perspectives

Evaluation of biological contaminants in foods by hyperspectral imaging: A review

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