RESUMO
Vermicomposting is the bio-oxidation and stabilization of organic matter involving relationships between the action of earthworms and microorganisms and the activation and dynamics of several enzyme activities. Semi-arid farmers to make (extra) money and organic production, produce their vermicompost using plant residues and animal manure, but there is no information about the final product generated. Thus, this study aimed to analyze the potential of vermicomposting with mixtures of animal manure and vegetable leaves in the development of Eisenia foetida, microbial biomass, and enzymatic activity in the semi-arid region, Brazil. The experimental design applied was randomized block in a 6 × 4 factorial scheme with four replicates, with six treatments (mixtures of cattle manure, goat manure, cashew leaves, and catanduva leaves) and evaluated at four-time intervals (30, 60, 90, and 120 days of vermicomposting). The treatments were placed in polyethylene pots in the same site, environmental conditions, and residues proportions as used by farmers. The characteristics analyzed were the number of earthworms (NE), total earthworm biomass (TEB) and earthworm multiplication index (MI), microbial biomass carbon (MBC), and activities of enzymes ß-glucosidase, dehydrogenase, alkaline and acid phosphatases. The cattle manure vermicomposted shows the highest average values observed for NE, MI, TEB, MBC, and enzymatic activity, regardless of the plant leaves mix. In general, the enzymes activities were found in the descending order of ß-glucosidase > alkaline phosphatase > dehydrogenase > acid phosphatase. The maturation dynamics of vermicompost were characterized by a decline in the microbial population and number and biomass of earthworms in the substrate and consequently a decrease in new enzyme synthesis and degradation of the remaining enzyme pool. Microbial biomass and enzymatic activity were indicators for changes in the quality of vermicompost.
Assuntos
Celulases , Oligoquetos , Animais , Bovinos , Biomassa , Carbono/metabolismo , Celulases/metabolismo , Esterco , Oligoquetos/metabolismo , Oxirredutases/metabolismo , Solo , Verduras/metabolismoRESUMO
Near-infrared (NIR) spectroscopy and chemometric methods were used to predict the chemical properties of decomposing eucalyptus harvest residues to better understand the decomposition process of these materials. Leaves, twigs, branches, and bark from a decomposition experimental set up in commercial plantations were sampled for one year. The contents of carbon (C), nitrogen (N), extractives (EX), acid-soluble lignin (SL), Klason insoluble lignin (KL) and holocellulose (HC) were determined by the reference method in the collected samples. Principal component analysis (PCA) was employed to distinguish the types of harvest residues throughout the decomposition period. Multi-residue regression models were built from the NIR spectra using partial least squares regression (PLS). Two feature selection methods, i.e., ordered predictors selection (OPS) and genetic algorithm (GA), were applied and compared. The OPS and GA did not differ statistically; however, compared with the GA, OPS was more computationally efficient and selected fewer variables. Using the PLS-OPS models, the root mean square errors of prediction (RMSEP) for C, N, EX, SL, KL and HC were 19.70, 0.08, 0.74, 0.39, 28.13 and 33.99, respectively, and the prediction correlations (Rp) for these properties were 0.94, 0.99, 0.99, 0.99, 0.96 and 0.98, respectively. PLS-discriminant analysis (PLS-DA) was used to classify the samples over the decomposition time and provided a good separation. Some mismatches obtained in the modeled classes were explained by the differences in the decomposition rate and changes in the chemical composition of the different harvest residue components that were evaluated. The results showed the feasibility of NIR spectroscopy and chemometric methods to evaluate the chemistry of decomposing eucalyptus harvest residues, indicating that these methods can be used as rapid and inexpensive alternatives to conventional methods to help understand the decomposition process.