Study of soil aggregate breakdown dynamics under low dispersive ultrasonic energies with sedimentation and X-ray attenuation

Schomakers, Jasmin; Zehetner, Franz; Mentler, Axel; Ottner, Franz; Mayer, H.

doi:10.1515/intag-2015-0057

Cited by 12 publications

(9 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, great performance of OLSR was reported for predicting rainfed soybean and maize yields [39]. PCR (R 2 = 0.30-0.49) was likewise applied to model grain yields based on soil properties [40]. Moreover, PLSR model was successfully used to predict important management goals in land application [41].…”

Section: Introductionmentioning

confidence: 99%

Modeling of paclitaxel biosynthesis elicitation in Corylus avellana cell culture using adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA) and multiple regression methods

et al. 2020

View full text Add to dashboard Cite

Paclitaxel as a microtubule-stabilizing agent is widely used for the treatment of a vast range of cancers. Corylus avellana cell suspension culture (CSC) is a promising strategy for paclitaxel production. Elicitation of paclitaxel biosynthesis pathway is a key approach for improving its production in cell culture. However, optimization of this process is time-consuming and costly. Modeling of paclitaxel elicitation process can be helpful to predict the optimal condition for its high production in cell culture. The objective of this study was modeling and forecasting paclitaxel biosynthesis in C. avellana cell culture responding cell extract (CE), culture filtrate (CF) and cell wall (CW) derived from endophytic fungus, either individually or combined treatment with methyl-β-cyclodextrin (MBCD), based on four input variables including concentration levels of fungal elicitors and MBCD, elicitor adding day and CSC harvesting time, using adaptive neuro-fuzzy inference system (ANFIS) and multiple regression methods. The results displayed a higher accuracy of ANFIS models (0.94-0.97) as compared to regression models (0.16-0.54). The great accordance between the predicted and observed values of paclitaxel biosynthesis for both training and testing subsets support excellent performance of developed ANFIS models. Optimization process of developed ANFIS models with genetic algorithm (GA) showed that optimal MBCD (47.65 mM) and CW (2.77% (v/v)) concentration levels, elicitor adding day (16) and CSC harvesting time (139 h and 41 min after elicitation) can lead to highest paclitaxel biosynthesis (427.92 μg l-1). The validation experiment showed that ANFIS-GA method can be a promising tool for selecting the optimal conditions for maximum paclitaxel biosynthesis, as a case study.

show abstract

Section: Introductionmentioning

confidence: 99%

Modeling of paclitaxel biosynthesis elicitation in Corylus avellana cell culture using adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA) and multiple regression methods

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Most methods of measuring soil aggregate stability are based on wet sieving, rainfall simulation, ultrasonic vibration, and clay dispersion (Almajmaie, Hardie, Acuna, et al, ; Amézketa, ; Cerda, ; Le Bissonnais, ; Rohoskova & Valla, ; Schomakers, Zehetner, Mentler, Ottner, & Mayer, ). The wet‐sieving method, based on the early work of Kemper and Koch () using slowly immersed aggregates, is most frequently used, especially for the simulation of the disaggregation process of soil aggregates that are exposed to furrow irrigation and floods (Almajmaie, Hardie, Acuna, et al, ).…”

Section: Introductionmentioning

confidence: 99%

An improved method for determination of aggregate stability using laser diffraction

et al. 2018

View full text Add to dashboard Cite

Soil aggregate water stability is very important from both scientific and practical points of view. This stability is a critical factor in a soil's susceptibility to water erosion and, in turn, land degradation. The most popular measure of soil aggregate stability is the water resistance index (WRI), which is commonly measured using the wet‐sieving method. Using the laser diffraction method in order to observe changes in the median of the particle size distribution and determine soil aggregate stability was first proposed in 2010. However, the method was not suitable for weak aggregates. The aim of this study was to present a measure of aggregate stability using laser diffractometry, aggregate stability index (ASILD). Determination of the ASILD is based on the calculation of the directional coefficient of the straight line interpolated from 2 points: (a) the value calculated as the mean of the lower and upper nominal sieve sizes used for soil aggregate separation and (b) the median of the first measurement after the adding of the dry aggregates into the measuring system of the laser diffractometer. This proposed method for the calculation of the ASILD can be applied to very weak aggregates (i.e., aggregates that, in practice, are not at all water resistant). For weak and moderately stable aggregates, the correlation between ASILD and WRI is higher than 0.9. This method also enables differentiation between the water resistance of aggregates which, by the wet‐sieving method, are indistinguishable (i.e., those which have the maximum WRI).

show abstract

“…An alkaline chernozem with a sandy loam texture was sampled from the Marchfeld in Lower Austria. More details concerning the study site of the chernozem were described in Schomakers et al (2015). The podzol, as a forest soil, was rich in organic matter of 21.4% (Table 1) while the agricultural chernozem had a low organic content of 1.17%.…”

Section: Methodsmentioning

confidence: 99%

Comparison of commonly used extraction methods for ergosterol in soil samples

Sae-Tun¹,

Maftukhah²,

Noller³

et al. 2020

Int. Agrophys.

Self Cite

View full text Add to dashboard Cite

A b s t r a c t. Concerning the contribution of fungi to soil carbon sequestration, various methods have been used to extract ergosterol from soil samples. This study aims to explore the extraction ability and applicability of commonly used methods to extract ergosterol from two contrasting soils. An agricultural soil (chernozem) and a forest soil (podzol) were extracted with different types of cell lysis such as alkaline, glass bead, and ultrasonication methods in association with simple shaking. The ergosterol concentration was measured by high pressure liquid chromatography. Regardless of the method applied, ergosterol yield was higher in podzol than in chernozem. Alkaline extraction resulted in the highest ergosterol concentrations for both soils and miniaturized glass bead extraction produced comparable results in the case of chernozem. In terms of applicability, the non-alkaline methods were simpler to conduct and less demanding of labour, chemical use and glassware and more flexible in terms of the equipment used for mechanical disruption. Despite the limit of the two soil types in the present study, only the simple shaking method was revealed to be dependent on soil type. Based on our results, we recommend the miniaturized glass bead method for agricultural soils, low in organic matter for high throughput. However, not all of the methods described allow for the proper separation of coextracted organic substances from organic-rich soil.

show abstract

Study of soil aggregate breakdown dynamics under low dispersive ultrasonic energies with sedimentation and X-ray attenuation

Cited by 12 publications

References 24 publications

Modeling of paclitaxel biosynthesis elicitation in Corylus avellana cell culture using adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA) and multiple regression methods

Modeling of paclitaxel biosynthesis elicitation in Corylus avellana cell culture using adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA) and multiple regression methods

An improved method for determination of aggregate stability using laser diffraction

Comparison of commonly used extraction methods for ergosterol in soil samples

Contact Info

Product

Resources

About