During the latest decades, the Amazon has experienced a great loss of vegetation cover, in many cases as a direct consequence of wildfires, which became a problem at local, national, and global scales, leading to economic, social, and environmental impacts. Hence, this study is committed to developing a routine for monitoring fires in the vegetation cover relying on recent multitemporal data (2017–2019) of Landsat-8 and Sentinel-2 imagery using the cloud-based Google Earth Engine (GEE) platform. In order to assess the burnt areas (BA), spectral indices were employed, such as the Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2), and Mid-Infrared Burn Index (MIRBI). All these indices were applied for BA assessment according to appropriate thresholds. Additionally, to reduce confusion between burnt areas and other land cover classes, further indices were used, like those considering the temporal differences between pre and post-fire conditions: differential Mid-Infrared Burn Index (dMIRBI), differential Normalized Burn Ratio (dNBR), differential Normalized Burn Ratio 2 (dNBR2), and differential Near-Infrared (dNIR). The calculated BA by Sentinel-2 was larger during the three-year investigation span (16.55, 78.50, and 67.19 km²) and of greater detail (detected small areas) than the BA extracted by Landsat-8 (16.39, 6.24, and 32.93 km²). The routine for monitoring wildfires presented in this work is based on a sequence of decision rules. This enables the detection and monitoring of burnt vegetation cover and has been originally applied to an experiment in the northeastern Peruvian Amazon. The results obtained by the two satellites imagery are compared in terms of accuracy metrics and level of detail (size of BA patches). The accuracy for Landsat-8 and Sentinel-2 in 2017, 2018, and 2019 varied from 82.7–91.4% to 94.5–98.5%, respectively.

The genusBeauveriais considered a cosmopolitan anamorphic and teleomorphic genus of soilborne necrotrophic arthropod-pathogenic fungi that includes ecologically and economically important species. Species identification inBeauveriais difficult because of its structural simplicity and the lack of distinctive phenotypic variation. Therefore, the use of multi-locus sequence data is essential to establish robust species boundaries in addition to DNA-based species delimitation methods using genetic distance, coalescent, and genealogical concordance approaches (polyphasic approaches). In this regard, our study used multilocus phylogeny and five DNA-based methods to delimit species inBeauveriausing three molecular makers. These polyphasic analyses allowed for the delimitation of 20–28 species inBeauveria, confirming cryptic diversity in five species (i.e.B. amorpha,B. bassiana,B. diapheromeriphila, andB. pseudobassiana) and supporting the description ofB. peruviensisas a new taxon from northeastern Peru. The other five species were not evaluated as they did not have enough data (i.e.B. araneola,B. gryllotalpidicola,B. loeiensis,B. medogensis, andB. rudraprayagi). Our results demonstrate that the congruence among different methods in a polyphasic approach (e.g. genetic distance and coalescence methods) is more likely to show reliably supported species boundaries. Among the methods applied in this study, genetic distance, coalescent approaches, and multilocus phylogeny are crucial when establishing species boundaries inBeauveria.

Peru is one of the world’s main coffee exporters, whose production is driven mainly by five regions and, among these, the Amazonas region. However, a combined negative factor, including, among others, climate crisis, the incidence of diseases and pests, and poor land-use planning, have led to a decline in coffee yields, impacting on the family economy. Therefore, this research assesses land suitability for coffee production (Coffea arabica) in Amazonas region, in order to support the development of sustainable agriculture. For this purpose, a hierarchical structure was developed based on six climatological sub-criteria, five edaphological sub-criteria, three physiographical sub-criteria, four socio-economic sub-criteria, and three restrictions (coffee diseases and pests). These were integrated using the Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS) and Remote Sensing (RS). Of the Amazonas region, 11.4% (4803.17 km²), 87.9% (36,952.27 km²) and 0.7% (295.47 km²) are “optimal”, “suboptimal” and “unsuitable” for the coffee growing, respectively. It is recommended to orient coffee growing in 912.48 km² of territory in Amazonas, which presents “optimal” suitability for coffee and is “unsuitable” for diseases and pests. This research aims to support coffee farmers and local governments in the region of Amazonas to implement new strategies for land management in coffee growing. Furthermore, the methodology used can be applied to assess land suitability for other crops of economic interest in Andean Amazonian areas.

The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to identify potential habitat distribution of the genus, its availability in areas protected by national service of protected areas, and highlighted some areas because of their conservation relevance and the potential need for restoration. We modeled the distribution of the genus Cedrela in Peru using 947 occurrence records that included 10 species (C. odorata, C. montana, C. fissilis, C. longipetiolulata, C. angustifolia, C. nebulosa, C. kuelapensis, C. saltensis, C. weberbaueri, and C. molinensis). We aim to identify areas environmentally suitable for the occurrence of Cedrela that are legally protected by the National Service of Protected Areas (PAs) and those that are ideal for research and restoration projects. We used various environmental variables (19 bioclimatic variables, 3 topographic factors, 9 edaphic factors, solar radiation, and relative humidity) and the maximum entropy model (MaxEnt) to predict the probability of occurrence. We observed that 6.7% (86,916.2 km²) of Peru presents a high distribution probability of occurrence of Cedrela, distributed in 17 departments, with 4.4% (10,171.03 km²) of the area protected by PAs mainly under the category of protection forests. Another 11.65% (21,345.16 km²) of distribution covers areas highly prone to degradation, distributed mainly in the departments Ucayali, Loreto, and Madre de Dios, and needs immediate attention for its protection and restoration. We believe that the study will contribute significantly to conserve Cedrela and other endangered species, as well as to promote the sustainable use and management of timber species as a whole.

Cocoa (Theobroma cacao) is the main raw material for the production of chocolate; it is considered the food of the gods, as it possesses a diversity of bioactive compounds beneficial to human health. The abundance of bioactive compounds, among others, is conditioned by the post-harvest processing of cocoa beans, and fermentation is a major step in this regard. Consequently, this research evaluated the changes in phenolic compounds and methylxanthines occurred in the fermentation of Criollo and CCN-51 cocoa beans, varieties of great commercial interest for the cocoa-growing areas of Peru. For this purpose, samples were taken every 12 h of cocoa beans under fermentation for 204 h in which phenols (gallic acid, caffeic acid, catechin, and epicatechin) and methylxanthines (theobromine, caffeine and theophylline) were quantified by ultra-high performance liquid chromatography (UHPLC); total polyphenols by Folin Ciocalteu; antioxidant capacity by DPPH free radical capture method; total anthocyanins; pH; titratable acidity; and fermentation rate of beans. We found that during fermentation, phenolic content, antioxidant activity, and methylxanthines of cocoa beans decreased; on the other hand, the anthocyanin content increased slightly. Indeed, at distinctly degree, fermentation influences bioactive compounds in cocoa beans, depending on the variety cultivated.

Los bosques de la Amazonia peruana han experimentado importantes transformaciones desde mediados del siglo pasado. Este trabajo evaluó los Cambios de Cobertura y Uso del Suelo (CCUS) en la provincia de Rodríguez de Mendoza, mediante los métodos de clasificación supervisada de máxima probabilidad e interpretación visual interdependiente de imágenes del satélite Landsat, entre los períodos 1987–2001 y 2001–2016. Se construyeron matrices de tabulación cruzada y se calcularon tasas e índices anuales de cambio. Los resultados muestran una pérdida acumulada de 918,59 km2 de cobertura boscosa. La intensidad de CCUS y la tasa de deforestación fueron mayores en el segundo período de análisis. Se evidenció que las altas concentraciones de pérdida de cobertura boscosa están próximas a la red vial e hídrica. Las principales causas de la pérdida de bosques fueron la actividad ganadera y la expansión agrícola migratoria a pequeña explotación, favorecidas por la accesibilidad de infraestructuras de transporte.