Review on Parthenium hysterphorus as a potential energy source

Swati, Ghosh; Haldar, S.; Ganguly, Anindita; Chatterjee, Pradip K.

doi:10.1016/j.rser.2012.12.011

Cited by 20 publications

(11 citation statements)

References 45 publications

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“…It is an annual plant noxious in nature which germinates well in temperature between 10 and 25 C (Mcconnachie et al, 2011;Singh et al, 2013). The weed erects up to two meter (Swati, Haldar, Ganguly, & Chatterjee, 2013), maximum growth observed in those regions where rainfall occurs higher than 500 mm annually (OEPP/EPPO, 2014). It causes dermatitis, respiratory and other types of allergies in humans and livestock (Mcconnachie et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Exploitation of Parthenium hysterophorous biomass as low-cost substrate for cellulase and xylanase production under solid-state fermentation using Talaromyces stipitatus MTCC 12687

Bharti

Kumar

et al. 2018

Journal of Radiation Research and Applied Sciences

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To make the enzyme production process appreciably inexpensive in respect of SSF, use of economical substrates is of great interest. Out of total eight employed solid substrate, Parthenium hysterophorous biomass exhibited its potential and displayed maximum endoglucanase (30 IU/gds), xylanase (582 IU/ gds) and FPase (2.86 FPU/gds) activities. During optimization of cultural parameters, Talaromyces stipitatus MTCC 12687 produced maximum endoglucanase (53.3 IU/gds), FPase (4.51 FPU/gds) and bglucosidase (62.6 IU/gds) at temperature (30 C), incubation time (5 th day), pH (6.0) and moisture content (80%) with the supplementation of peptone as the nitrogen source and Tween-80 as the surfactant under SSF conditions. During the process of optimization different enzyme activities viz. endoglucanase, xylanase, FPase and b-glucosidase were enhanced by approximately 2.0, 1.54, 2.0 and 2.7 fold respectively compared to their respective controls. Talaromyces stipitatus MTCC 12687 enzymes hydrolysed untreated and organosolve pretreated P. hysterophorous biomass to release 93 ± 3.87 and734 ± 17 mg/g of reducing sugars respectively after hydrolysis time of 48 h.

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Section: Introductionmentioning

confidence: 99%

Exploitation of Parthenium hysterophorous biomass as low-cost substrate for cellulase and xylanase production under solid-state fermentation using Talaromyces stipitatus MTCC 12687

Bharti

Kumar

et al. 2018

Journal of Radiation Research and Applied Sciences

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“…Its aerial parts do not effectively resist frost, hence the majority of plants perish under low temperatures in winter; although some plants may regrow from their old stem bases after mild winters [36]. Parthenium weed tolerates a wide range of soils from sandy loams to clay loams, however, it prefers black, alkaline, cracking clay soils of high fertility (see [39,40]. Parthenium weed is extremely prolific in seed production (about 20 000 seeds per plant).…”

Section: Ecology Of the Parthenium Weedmentioning

confidence: 99%

“…In some sites of South Africa, an estimate of 958 million seeds per ha has been recorded [42]. Parthenium weed seeds may be dispersed by vehicles, farm machinery, animals (domestic and wild) and river or flood water [39], [42]. The above ecological attributes make the control of Parthenium weed very challenging.…”

Section: Ecology Of the Parthenium Weedmentioning

confidence: 99%

A Hybrid Feature Method for Handling Redundant Features in a Sentinel-2 Multidate Image for Mapping Parthenium Weed

Kiala

Mutanga

Odindi

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Multidate images provide additional spectral information valuable for mapping plant species. However, correlated or redundant variables created from multiple image data and a large set of variables impede accurate and efficient landscape classification. Nevertheless, with the implementation of an appropriate feature selection method, the full potential of multidate images and subsequent increased classification accuracies may be achieved. Feature selection is a process of automatically selecting features in a dataset that contribute the most to the prediction of a target variable. It improves the classification process in terms of computation cost and predictive accuracy. Feature selection algorithms are typically classified into three groups: filters, wrappers, and embedded. Due to the inherent tradeoffs provided by different feature selection approaches, we hypothesize that a hybrid approach could optimize landscape delineation by leveraging on their complementary strengths. In this regard, we propose a new feature selection method that combines a filter ReliefF, a wrapper Support vector machines-backward (SVM-b), and the embedded random forest in mapping the noxious Parthenium weed using a Sentinel-2 multidate image. The new approach was compared to its three constituents based on the size of optimal feature subsets and classification accuracies. To make comparison and assessment of developed models from selected variables more valuable, the split between training and test datasets was implemented in three different ratios, namely, 3:1(Dataset 1), 1:1(Dataset 2); 1:3 (Dataset 3). The new approach was also evaluated against the multidate image without feature selection and a single-date image. Results showed that the new approach yielded the highest overall accuracies with the smallest optimal feature subsets. For instance, on Dataset 3, the OA was 86.6% with 22 optimal features, whereas it was 84.7% with 35 optimal features using SVM-b, which was the second most performing feature selection algorithm. The new approach yielded higher classification accuracies than the multidate image without feature selection and the single-date image. The findings of this study underscore the capability of hybrid methods to select fewer features from multidate images, with higher predictive accuracies than individual feature selection methods.

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“…The noxious weed, Parthenium sp. (congress grass), which have no particular use and their eradication is a major challenge, caused decline in yield up to 40% in agricultural crops (Swati et al, 2013). Attempts have been made to use this as substrate for compost preparation but very negligible reports are available for enzyme production.…”

Section: Introductionmentioning

confidence: 99%

Parthenium sp. as Substrate for Production of Cellulolytic Enzymes by Trichoderma spp.

2020

MAJ

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Review on Parthenium hysterphorus as a potential energy source

Cited by 20 publications

References 45 publications

Exploitation of Parthenium hysterophorous biomass as low-cost substrate for cellulase and xylanase production under solid-state fermentation using Talaromyces stipitatus MTCC 12687

Exploitation of Parthenium hysterophorous biomass as low-cost substrate for cellulase and xylanase production under solid-state fermentation using Talaromyces stipitatus MTCC 12687

A Hybrid Feature Method for Handling Redundant Features in a Sentinel-2 Multidate Image for Mapping Parthenium Weed

Parthenium sp. as Substrate for Production of Cellulolytic Enzymes by Trichoderma spp.

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