Examinando por Materia "Regression"

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Ecological zone-based volume estimation of Calycophyllum spruceanum and Cedrelinga cateniformis in the Northeastern Peruvian Amazon
(Elsevier B.V., 2025-11-08) Koch Duarte, Christian; del Aguila Piña, Carlos Francisco; Fernández Sandoval, Andrés; Cárdenas Rengifo, Gloria Patricia; Santillán Gonzáles, Manuel Dante; Salazar Hinostroza, Evelin Judith; Castedo Dorado, Fernando; Álvarez Álvarez, Pedro; Goycochea Casas, Gianmarco; Baselly Villanueva, Juan Rodrigo
Forest volume modeling plays a fundamental role in forest inventory, biomass estimation, and the sustainable management of timber resources. In the Amazon region of Peru, native species such as Calycophyllum spruceanum and Cedrelinga cateniformis hold high ecological and commercial value, yet remain understudied in terms of volumetric estimation. This study aimed to develop and evaluate volumetric models for both species across three ecological zones—humid forest, very humid forest, and dry forest—representing the environmental diversity of the northeastern Peruvian Amazon. A total of 18 volumetric models were fitted for each species and site condition using linear regression techniques. Model performance was assessed through adjusted coefficient of determination (R²adj), root mean square error (RMSE), mean absolute error (MAE), Akaike Information Criterion (AIC), and diagnostic analyses including residual plots and relative error histograms. The results revealed that model performance varied by ecological zone, with the dry forest models showing the highest precision and lowest residual dispersion. Models M3 (Spurr), M4 (Schumacher & Hall), and M9 (Meyer) consistently achieved strong predictive accuracy. Prediction errors were higher in small-volume classes, suggesting the need for caution when applying models to young or small-diameter trees. The developed models are statistically reliable, requiring minimal input variables for the accurate estimation of the timber volume of the two species across various Amazonian environments. It is recommended to adopt zone-specific models for operational use and to continue expanding regional forest databases to improve future model calibration and validation.
Morphological and productive correlations of cutting Pennisetum varieties under conditions of peruvian humid tropics
(Bogor Agricultural University, 2024-08-26) Pinchi Carbajal, Segundo Fidencio; Quispe Ccasa, Hurley Abel; Ampuero Trigoso, Gustavo; Nolasco Lozano, Emily; Saucedo Uriarte, Jose Américo
Livestock farming in the Peruvian tropics is based on the use of grazing forage, but cutting grasses offers greater productivity and seasonality advantages. In this study, the morphological and productive characteristics of King Grass Morado (KGM), Cuba OM-22 (CU), and Maralfalfa (MA) were evaluated and correlated with chlorophyll content under Peruvian humid tropic conditions. Five plots of 1 ha each were installed for the three Pennisetum varieties (2-1-2), with three samples per plot. No significant differences were found in plant height, leaf length, number of nodes, number of leaves/stem, number of stems, stem circumference, length of nodes, leaf, stems, and total weight, chlorophyll index (atLEAF CLOR), performance index (API), and dry matter. KGM stood out in tillering (12.86) (p<0.01), but CU and MA showed greater leaf width (4.16 and 4.42 cm, respectively) (p<0.05). The calculated biomass production was 40.3 t/ha for KGM, 24.5 t/ha for MA, and 76.5 t/ha for CU. MA had higher nitrogen (0.70%) and protein (4.33%) contents (p<0.01). The correlations were significant between stem height with the number of nodes and leaf width, stem circumference with stem, leaf, and total weight (p<0.05), and nitrogen and protein content were estimated with the atLEAF CLOR and API values of the basal leaves with R2 = 0.548 and R2 = 0.563, respectively (p<0.05). In conclusion, KGM, CU, and MA differed in some morphological and productive variables and were correlated with others; furthermore, the protein content could be estimated with the atLEAF CLOR and API values in these Pennisetum varieties.
Using acoustic tomography to model wood deterioration in Cedrelinga cateniformis Ducke in the Peruvian Amazon
(MDPI, 2024-04-29) Cardenas Rengifo, Gloria Patricia; Baselly Villanueva, Juan Rodrigo; Chumbimune Vivanco, Sheyla Y.; Macedo Ramírez, Arturo T.; Salazar, Evelin; Minaya, Benjamín; Quintana, Saron; Cabudivo, Abrahan; Palma, Stella S. A.; Álvarez Álvarez, Pedro; Ocaña Reyes, Jimmy Alcides
Forest plantations can be established in order to restore degraded areas. Acoustic tomography, which is of increasing importance in forest management, was used in the present study to obtain information for managing plantations of Cedrelinga cateniformis Ducke in the Peruvian Amazon. The species is valuable in the timber sector of Peru, but the core wood tends to deteriorate and develop cavities. The main objective of the study was to model wood deterioration in Cedrelinga cateniformis Ducke using the data obtained through acoustic tomography. Eight plantations of varying ages were analyzed using acoustic tomography in order to obtain indicators of wood deterioration. Biometric, climatic, and edaphic data (explanatory variables) were also measured in each plantation. The indicator variables and explanatory variables were compared and evaluated using correlation and principal component analysis. Wood deterioration was modelled using stepwise regression. The indicator variables differed significantly between plantations and were mainly correlated with the biometric variables (age and diameter at breast height). The models explained 81% of the variability of pith rot. The percentage rotten area was minimal in young plantations (1%), and the opposite was observed in mature trees (21.5 to 25.6%). The study findings provide valuable information, enabling foresters to determine the optimal age and diameter for felling Cedrelinga cateniformis in plantations in the Peruvian Amazon.