Examinando por Autor "Paz Monge, Michel"

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Estimation of height and aerial biomass in Eucalyptus globulus plantations using UAV-LiDAR
(Elsevier B.V., 2024-12-22) Enriquez Pinedo, Lucía; Ortega Quispe, Kevin; Ccopi Trucios, Dennis; Urquizo Barrera, Julio; Rios Chavarría, Claudia; Pizarro Carcausto, Samuel; Matos Calderon, Diana; Patricio Rosales, Solanch; Rodríguez Cerrón, Mauro; Ore Aquino, Zoila; Paz Monge, Michel; Castañeda Tinco, Italo
The lack of precise methods for estimating forest biomass results in both economic losses and incorrect decisions in the management of forest plantations. In response to this issue, this study evaluated the effectiveness of using the DJI Zenmuse L1 LiDAR, mounted on a DJI Matrice 300 RTK UAV, to provide three-dimensional measurements of canopy structure and estimate the aboveground biomass of Eucalyptus globulus. Various LiDAR metrics were employed alongside field measurements to calibrate predictive models using multiple regression and machine learning algorithms. The results at the individual tree level show that RF is the most accurate model, with a coefficient of determination (R²) of 0.76 in the training set and 0.66 in the test set, outperforming Elastic Net (R² of 0.58 and 0.57, respectively). At the plot level, a multiple regression model achieved an R² of 0.647, highlighting LiDAR-derived metrics as key predictors. The findings revealed that the combination of LiDAR with advanced statistical techniques, such as multiple regression and Random Forest, significantly improves the accuracy of biomass estimation, surpassing traditional methods based on allometric equations. Therefore, the use of LiDAR in conjunction with machine learning represents an effective alternative for biomasss estimation, with great potential in such plantations and contribute to more sustainable exploitation of timber resources.
Growth dynamics, harvest performance, and biomass partitioning of lettuce cultivars under contrasting hydroponic configurations: Implications for sustainable protected horticulture
(Acadlore Publishing Services Limited, 2026-06-10) Capcha Inga, Paola Veronica; Oliva Rojas, Luis; Chumbimune Vivanco, Sheyla Yanett; Amézquita León, Carlos Alberto; Paz Monge, Michel; Ortega Quispe, Kevin Abner
White Boston, Waldmann's Green, and Black Rose—grown in pyramidal nutrient film technique (NFT), floating raft (FR), and semihydroponic (SH) configurations. The experiment included 36 units and 192 plants. Nondestructive measurements were performed at 30 and 60 days after sowing, followed by destructive harvest measurements at 60 days. Temporal changes and cultivar responses were evaluated separately within each configuration because hydraulically independent units differed among configurations; between-configuration patterns were interpreted descriptively. Most temporal changes were similar among cultivars. At harvest, cultivar-dependent responses were configuration-specific and involved morphology, leaf fresh weight, total dry matter content, and biomass allocation. Total fresh and dry weight did not differ significantly among cultivars within any configuration. Nevertheless, FR–White Boston showed the highest numerical total fresh weight (189.96 ± 48.90 g plant⁻¹), whereas FR–Black Rose showed the greatest leaf fresh-weight proportion (81.0%). Waldmann's Green showed comparatively high total dry matter content, including 5.18% in FR, where cultivar differences were statistically supported. The first two principal components explained 56.9% of the total variance and revealed overlapping multivariate patterns among configuration × cultivar combinations. Overall, cultivar performance depended on the trait and cultivation configuration: White Boston was associated with higher numerical fresh biomass, Black Rose with greater leaf biomass allocation, and Waldmann's Green with comparatively higher dry matter content. These findings provide an agronomic basis for cultivar selection in protected hydroponic production.