Detection of fungal infection in Lolium perenne by Fourier transform infrared spectroscopy

Brandl, Helmut

doi:10.1093/jpe/rts043

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…They can be used as biomarkers for G. boninense detection. This finding corroborates the study in [ 63 ], which reported a unique IR pattern due to the presence of fungi to discriminate between infected tissues and uninfected tissues. A similar study by Alexander et al [ 57 ] reported that FTIR spectroscopy is capable of detecting G. boninense infection contents as low as 5%.…”

Section: Spectroscopy Technique For Ganoderma Boninense Detectionsupporting

confidence: 93%

Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

Tan

Jamlos

Omar

et al. 2021

Sensors

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Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.

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Section: Spectroscopy Technique For Ganoderma Boninense Detectionsupporting

confidence: 93%

Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

Tan

Jamlos

Omar

et al. 2021

Sensors

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“…Accordingly, it is evident that oil palms infected with this organism exhibit a different spectrum; hence, the pathogen can be detected or identified directly from the leaf tissue. According to Brandl. (2013), the infected biomass will produce a different FTIR compared to the healthy counterpart, owing to fungal metabolism in the plant tissues.…”

Section: Resultsmentioning

confidence: 99%

The Fourier transform infrared spectroscopy from Diplazium esculentum and Rivina humilis analysis to reveals the existence of necessary components in oil palm plantations of Ganoderma boninense control

et al. 2021

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Abstract. Saragih WS, Purba E, Lisnawita, Basyuni M. 2021. The Fourier transform infrared spectroscopy from Diplazium esculentum and Rivina humilis analysis reveals necessary components in oil palm plantations of Ganoderma boninense control. Biodiversitas 22: 3645-3651. The Fourier transform infrared spectroscopy (FTIR) has been widely utilized for biological samples and biomolecular characterization. We aim to identify Ganoderma boninense through FTIR and obtain a functional group that can facilitate early basal stem rot detection. Here, positive control (KP) was not inoculated with G. boninense and negative control (KN) was inoculated with G. boninense. However, the treatment samples, Diplazium esculentum leaf extract, Rivina humilis leaf extract, and fungicide treatment, were not inoculated with G. boninense. The positive control oil-palm leaf samples exhibited spectral bands similar to those in the D. esculentum extract, R. humilis extract, and fungicide treatment. Strong bonds were observed at wavelengths 3379 cm-1, 2927 cm-1, 1639 cm-1, and 1056 cm-1. Others were moderate to weak, except the negative control samples with strong bonds at 2044 cm-1. This indicates amine N-H functional groups, alkane functional group C-H, functional group alkene C=C, C-O, functional group ester, and functional group isothiocyanate N=C=S (C4H5NS or CH2 = CHCH2N=C=S). The FTIR plot result denotes G. boninense through N=C=S Isothiocyanate functional group presence at 2140-1990 cm-1. This unique structure is only found in infected oil-palm leaf tissues of G. boninense. Our study suggests that FTIR spectroscopy is more beneficial than conventional methods in early detection of G. boninense infection in oil palm.

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“…Identification of ryegrass plants infected with E. festucae var. lolii using NIR spectroscopy was performed by Brandl with good identification of all samples. However, the samples consisted of a single commercial cultivar of perennial ryegrass, and a small sample set ( n = 20) was used.…”

Section: Discussionmentioning

confidence: 99%

Near‐infrared spectroscopy allows detection and species identification of Epichloë endophytes in Lolium perenne

et al. 2018

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Detection of fungal infection in Lolium perenne by Fourier transform infrared spectroscopy

Cited by 10 publications

References 26 publications

Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

The Fourier transform infrared spectroscopy from Diplazium esculentum and Rivina humilis analysis to reveals the existence of necessary components in oil palm plantations of Ganoderma boninense control

Near‐infrared spectroscopy allows detection and species identification of Epichloë endophytes in Lolium perenne

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