Propolis produced by selected bees Apis mellifera were collected from March to June of 2013 and in March of 2015 and analyzed in order to evaluate the influence of climate, colony of origin, and food supplementation of colonies on the content of total phenolic and flavonoid by chromatographic analysis and antioxidant activity by radical scavenging of 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) and ferric reducing antioxidant power (FRAP) methods. The Principal Component Analysis (PCA) was carried out with propolis collected in 2013 and two clusters were formed. Propolis produced in the months of March and April showed a higher content of total phenolic compounds (TPC) and antioxidant capacity than those produced in May and June. The results of PCA obtained from samples collected in March of 2013 and 2015 showed two clusters, and propolis collected in 2015 were more bioactive and presented a higher content of TPC. The chromatographic analysis of extracts allowed the identification of phenolic acids p-coumaric, ferulic and caffeic with similar chemical profiles that could be closely related to the botanical origin of propolis. It can be concluded that the season and food supplementation of colonies influenced the chemical composition and the biological activity of samples analysed.
A fast and non-destructive method is reported to nitrogen, phosphorus and potassium quantification in sorghum, oat, and maize residues. The reflectance spectra of 261 litter plant samples using near-infrared spectroscopy were obtained with integrating sphere and sampling rotator. Second derivative spectra and Partial Least Squares were used to develop calibration and validation models. The cross-validation (leave-one-out) technique was used to evaluate the performance of the calibration and validation models, based on analytical parameters, root-mean-square error of estimation, determination coefficient, number of latent variables, residual prediction deviation, root-mean-square error of cross-validation. It was concluded that near-infrared spectroscopy and chemometric tools are a fast and non-destructive alternative to determine nitrogen and phosphorus content in sorghum, oat, and maize residues using calibration and validation models developed according to values obtained from traditional chemical methods. For potassium content, the results indicate the low quality (imprecision) of the calibration and validation models.
Plant growing substrates obtained by composting agro-industrial waste can serve as organic soil amendments. However, it is crucial to determine the maturity and quality of organic amendments before their application to soil. This study aimed to evaluate the suitability of compost obtained from poultry wastes combined with five different vegetal residues (tree trimmings, sugarcane bagasse, sawdust, cotton residues, and Napier grass) as growth media for container-grown Giant of Italy parsley. Fourier-transform infrared and laser-induced fluorescence spectra were used to characterize the humification extent in composts before and after the addition of charcoal at five inclusion rates (0%, 15%, 30%, 45%, and 60%, weight basis). Spectroscopic measurements identified absorption bands between 1625 and 1448 cm−1 specific to each of the 25 organic amendments evaluated. The most suitable amendments (composts made from sawdust and sugarcane bagasse) were associated with O–H stretching of phenols and aromatic rings. Charcoal addition to composts changed some of their physical characteristics, leading to increased nutrient availability in some cases. Experimental and calculated dry matter yield were compared via multiple linear regression and simple non-linear regression as a function of the spectroscopic and physicochemical (N, P, K, pH, EC, C, HLIF, C:N, CEC, HA:HA) properties of the organic amendments. Regression models accurately assigned high yields to the sawdust- and bagasse-based composts and low yields to the Napier grass- and cotton-based composts. Electrical conductivity (EC) was the main factor limiting potted-parsley productivity, an indication that efficient management of charcoal rate and compost EC levels can aid in predicting parsley yield.
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