Variability of physiochemical properties of livestock manure with added wood shavings during Windrow Composting

The objective of the present investigation was to evaluate the physical characteristics of the vermicompost and the quality of the purine of the red Californian (Eisenia foetida) using different substrates of feed for these worms. For this purpose, nine treatments were studied: 75% African palm rachis + 25% cattle manure, 50% African palm rachis + 50% cattle manure, 25% African palm rachis + 75% livestock manure, 50% manure of cattle, 50% of manure of cattle, 25% of manure of cattle, 50% of manure of cattle, 50% of manure of cattle, 50% of rach of coconut + 50% of manure of Livestock, 25% coccus rachis + 75% livestock manure. The substrate made up of 50% of rachis of coconut and 50% of livestock manure can be used in nurseries or nurseries for being the one that registered a value of pH 7.3 plus the closest to the neutral compared to the others, besides this (75% of oil palm rachis and 25% of cattle manure) showed a higher content of humic and fulvic acids (0.87 and 0.45 p / p, respectively), compounds that are important for agriculture by stimulating plant growth, in addition to this reflection 0.06% sulfur content, 4.0 ppm boron, 7.0 ppm copper, 47.5 ppm iron, 6.0 ppm manganese, with a presence of microorganisms of the species Trichoderma, Penicillium, Cladosporium sp. in amounts of 1.91x105 UFC / ml, however in this substrate was obtained between 13.3 and 43.5% less liquid slurry in Comparison with other treatments.

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Physiochemical properties of 3-mercaptopyruvatesulphurtransferase from Ginger (Zingiber Officinale

Asian journal of biochemical and pharmaceutical research ◽

10.24214/ajbpr/9/1/119130 ◽

2019 ◽

Vol 9 (1) ◽

Keyword(s):

Zingiber Officinale ◽

Physiochemical Properties

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SAMPL6 Challenge Results from pKa Predictions Based on a General Gaussian Process Model

10.26434/chemrxiv.6406505.v2 ◽

2018 ◽

Author(s):

Caitlin C. Bannan ◽

David Mobley ◽

A. Geoff Skillman

Keyword(s):

Gaussian Process ◽

Process Model ◽

Molecular Graph ◽

Gaussian Process Regression ◽

Ionization State ◽

Training Set ◽

Physiochemical Properties ◽

Quantile Plots ◽

Physical And Chemical ◽

Good Agreement

<div>A variety of fields would benefit from accurate pK<sub>a</sub> predictions, especially drug design due to the affect a change in ionization state can have on a molecules physiochemical properties.</div><div>Participants in the recent SAMPL6 blind challenge were asked to submit predictions for microscopic and macroscopic pK<sub>a</sub>s of 24 drug like small molecules.</div><div>We recently built a general model for predicting pK<sub>a</sub>s using a Gaussian process regression trained using physical and chemical features of each ionizable group.</div><div>Our pipeline takes a molecular graph and uses the OpenEye Toolkits to calculate features describing the removal of a proton.</div><div>These features are fed into a Scikit-learn Gaussian process to predict microscopic pK<sub>a</sub>s which are then used to analytically determine macroscopic pK<sub>a</sub>s.</div><div>Our Gaussian process is trained on a set of 2,700 macroscopic pK<sub>a</sub>s from monoprotic and select diprotic molecules.</div><div>Here, we share our results for microscopic and macroscopic predictions in the SAMPL6 challenge.</div><div>Overall, we ranked in the middle of the pack compared to other participants, but our fairly good agreement with experiment is still promising considering the challenge molecules are chemically diverse and often polyprotic while our training set is predominately monoprotic.</div><div>Of particular importance to us when building this model was to include an uncertainty estimate based on the chemistry of the molecule that would reflect the likely accuracy of our prediction. </div><div>Our model reports large uncertainties for the molecules that appear to have chemistry outside our domain of applicability, along with good agreement in quantile-quantile plots, indicating it can predict its own accuracy.</div><div>The challenge highlighted a variety of means to improve our model, including adding more polyprotic molecules to our training set and more carefully considering what functional groups we do or do not identify as ionizable. </div>

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A Study on Reduction Characteristics of Ammonia Gas Generated by Rotary-type Livestock Manure Composting Process

Journal of the Korean Society for Environmental Technology ◽

10.26511/jkset.20.6.5 ◽

2019 ◽

Vol 20 (6) ◽

pp. 418-424

Author(s):

Ji-Hun Jang ◽

Yong-Ho Ok ◽

Go-Su Yang

Keyword(s):

Livestock Manure ◽

Ammonia Gas ◽

Composting Process ◽

Reduction Characteristics ◽

Rotary Type

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Physiochemical properties and antioxidant potential of Persea Americana seed oil

10.31221/osf.io/jtf4s ◽

2019 ◽

Author(s):

Chem Int

Keyword(s):

Seed Oil ◽

Antioxidant Activities ◽

Radical Scavenging ◽

Reducing Power ◽

Acid Value ◽

Persea Americana ◽

Antioxidant Potential ◽

Physiochemical Properties ◽

Physiochemical Parameters ◽

Ic50 Value

Oil extracted from Persea Americana seed was assayed for its physiochemical properties and antioxidant potential using various standard methods. The oil content of the seed was found to be < 10%. Brownish-red color oil was liquid at room temperature, with specific gravity of 0.91±0.02 g/mL. Other physiochemical parameters determined were; acid value (4.51±0.08 mgKOH/g), %FFA (2.26±0.08), peroxide value (2.40±0.57 mgO2/Kg), ester value (31.26±0.03 mgKOH/g), saponification value (35.76±0.07 mgKOH/g) and iodine value (23.5±0.07). The results of the antioxidant activities of the seed oil showed that the flavonoid content (80.00±1.41 mgQE/g) was ~10 folds higher than the phenolic content (8.27±0.06 mgGAE/g). The DPPH radical scavenging value was found to be 51.54±0.25% with an IC50 value of 4.68±0.02 mg/mL and reducing power with an average absorbance of 0.85±0.01 and an IC50 value of 0.001±0.02 mg/mL. Gallic acid showed better antioxidant activities than the oil studied. The results obtained in this study showed that Persea Americana seed oil has nutritional, industrial as well as medicinal potentials.

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