Sharon Gomes Ribeiro, Marcio Regys Rabelo de Oliveira, Letícia Machado Lopes, M. Costa, Raul Shiso Toma, I. Araújo, L. C. J. Moreira, Adunias dos Santos Teixeira
{"title":"Reflectance spectroscopy in the prediction of soil organic carbon associated with humic substances","authors":"Sharon Gomes Ribeiro, Marcio Regys Rabelo de Oliveira, Letícia Machado Lopes, M. Costa, Raul Shiso Toma, I. Araújo, L. C. J. Moreira, Adunias dos Santos Teixeira","doi":"10.36783/18069657rbcs20220143","DOIUrl":"https://doi.org/10.36783/18069657rbcs20220143","url":null,"abstract":": Understanding organic carbon and predominant humic fractions in the soil allows contributes to soil quality management. Conventional fractionation techniques require time, excessive sampling, and high maintenance costs. In this study, predictive models for organic carbon in humic substances (HS) were evaluated using hyperspectral data as an alternative to chemical fractionation and quantification by wet digestion. Twenty-nine samples of Neossolos Flúvicos (Fluvents) - A1, and 36 samples of Cambissolos (Inceptisols) - A2 were used. The samples were also analyzed jointly, creating a third sample group - A1&A2. Untransformed spectral reflectance factors were obtained using the FieldSpec Pro FR 3 hyperspectral sensor (350–2500 nm). Pre-processing techniques were employed, including Savitzky–Golay smoothing and first-and second-order derivative analysis. After selecting variables using the Backward method, which removes spectral variables that are not statistically significant for the regression. Estimation models were built by Principal Components Regression (PCR) and Partial Least Squares Regression (PLSR). The spectral data were evaluated individually for soil classes A1 and A2, and jointly for A1&A2. The PLSR was more efficient than PCR, especially for the estimation models that used the first derivative of reflectance employing the three sample groups. For samples of A1, the best estimate was seen for humic acid (RPD = 6.09) and humin (RPD = 2.38); for A2, the best models estimated the OC in fulvic acid (RPD = 2.35) and humin (RPD = 2.51); and for the joint spectral data (A1&A2), the prediction was robust for humin only (RPD = 2.01). The most representative wavelengths were observed using the first derivative with PLSR and PCR, centred on the region between 1600 and 1800 nm. The first-derivative of reflectance calculated more-robust predictive models using PLSR than PCR. The best predictions occurred for organic carbon associated with humic acid in","PeriodicalId":21219,"journal":{"name":"Revista Brasileira de Ciência do Solo","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139364209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Dudas, W. Demetrio, H. Nadolny, George Gardner Brown, M. Bartz
{"title":"Earthworms in the state of Paraná, Brazil: State of the art","authors":"R. Dudas, W. Demetrio, H. Nadolny, George Gardner Brown, M. Bartz","doi":"10.36783/18069657rbcs20220159","DOIUrl":"https://doi.org/10.36783/18069657rbcs20220159","url":null,"abstract":": Paraná State has approximately 74 % of its territory destined for agricultural activities. Several agricultural management practices modify soil quality and biodiversity, including earthworm populations that can contribute to soil health. This study aimed to review the studies carried out in the state of Paraná, Brazil, focusing on earthworm populations (abundance, biomass, richness, proportion of native and exotic species) in different land-use systems. In total, 51 publications were compiled, including peer-reviewed papers, book chapters, dissertations and theses. We used studies that analyzed chemical and physical soil properties (n = 14) to perform a principal component analysis to explore the relationships between these properties and earthworm populations. In total, 90 earthworm species are known from Paraná, of which more than half (n = 46) may be new species that still must be formally described. Of the total, 24 are exotic and 66 are native species, though only 62 (16 %) of the 399 counties have earthworm records. Of the land-use categories sampled, the lowest abundance and biomass were recorded in annual crops under conventional tillage, and the highest populations were found in agroforestry systems. Higher earthworm abundance and species richness were related to higher chemical fertility (soil P and base contents), while biomass was related to higher silt and sand contents.","PeriodicalId":21219,"journal":{"name":"Revista Brasileira de Ciência do Solo","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139363713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Castro, Rafael Lucas Coca Cuesta, V. G. O. Duarte, E. M. Mattiello, J. A. Ferreira, R. F. Novais, J. Tronto
{"title":"Cellulose acetate film containing layered double hydroxide: a new method for determination of soil phosphorus availability","authors":"G. Castro, Rafael Lucas Coca Cuesta, V. G. O. Duarte, E. M. Mattiello, J. A. Ferreira, R. F. Novais, J. Tronto","doi":"10.36783/18069657rbcs20220140","DOIUrl":"https://doi.org/10.36783/18069657rbcs20220140","url":null,"abstract":": Soil nutrient availability and interpretations of nutrient contents are based on the results obtained from specific extraction methods used in routine testing laboratories. The development of new extraction methods and new extractants with better accuracy is particularly important to determine the correct fertilizer rates to be applied. For this purpose, this study aims to synthesize, characterize and evaluate the predictive capacity of cellulose acetate film containing calcinated layered double hydroxide (CAF-LDH-c), as a new extractant and a new method of P extraction in soils. Different analyses techniques were used to characterize the CAF-LDH-c sample, including X-ray diffraction, attenuated total reflectance Fourier transform infrared spectroscopy, and scanning electronic microscopy. Soils were collected from twelve areas with different management and initial availability of P. The soils were subjected to six rates of P and were cultivated with plants. The predictive capacity of CAF-LDH-c, as a new extractant of P in different soils, was evaluated and compared to Mehlich-1 (M-1), Mehlich-3 (M-3), and Mixed Exchange Resin (MER) extractants. Chemical analyses performed on CAF-LDH-c showed that LDH in powder form was incorporated into the cellulose acetate film. There was a linear relation between P uptake by plants and extractable soil P in the soil by CAF-LDH-c, M-1, M-3, and MER extractants. The significant correlations between extracted P in the soil and P uptake by plants for CAF-LDH-c showed the efficacy of the new extractor and the newly proposed method for different types of soils. The results from the present study confirm the possibility of using CAF-LDH-c extractant as a new methodology to evaluate the availability of P in the soil for plant cultivation.","PeriodicalId":21219,"journal":{"name":"Revista Brasileira de Ciência do Solo","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139363785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}