In guava plants, production pruning can be performed twice a year, and the return of growth is dependent on the physiological responses that are altered by the different cultivation environments and adopted management. From this perspective, this study aimed to characterize the photosynthetic dynamics of guava plants influenced by different pruning and fruit thinning intensities during two growing seasons in the region of Currais, Piauí, Brazil. The plants were distributed in a randomized block design with a factorial arrangement (3 × 3 × 2) consisting of three pruning intensities (short, medium, and long) and three fruit thinning intensities (0, 10, and 20%) during two growing seasons. The data were subjected to a cluster analysis and canonical discriminant analysis to discriminate treatment groups based on the variables. Through a cluster analysis for the evaluated treatments, it was possible to split the two pruning seasons into five different groups clustered for the first pruning season and the second pruning season. The highest assimilation values were observed in the first pruning season and especially in plants that received short pruning with 0% fruit thinning, medium pruning with 10% and 20% fruit thinning, and long pruning with 10% fruit thinning. Through the graphic representation of the canonical discriminant analysis, the first two variables explained 93.40% of the total variance contained in the nine original variables. The highest means of ambient PAR, transpiration, leaf temperature, internal carbon, and ambient temperature were observed in the second pruning season and in plants that received short pruning with 10% and 20% fruit thinning, medium pruning with 0% and 20% fruit thinning, and long pruning with 0%, 10%, and 20% fruit thinning favors a higher photosynthetic accumulation in guava plants. We observed a multiplicity of responses; however, short pruning with 10% thinning should be considered for both seasons.

El objetivo fue encontrar los factores climáticos que determinan el rendimiento y la producción de papa en el distrito de Julia, entre los periodos 2000-2018, para lo cual se utilizó la información estadística de la Dirección Regional Agraria Puno y del Servicio Nacional de Meteorología e Hidrología de Puno. Se utilizó la metodología descriptiva y correlacional, considerando el modelo econométrico de tipo log-log. Se determinó que las variables climáticas como la temperatura mínima, la temperatura máxima determinan de manera positiva en el rendimiento de la producción y en la producción de papa y las precipitaciones de la lluvia determinan de manera negativa en el rendimiento de la producción y en la producción de papa. Finalmente, la temperatura mínima, la temperatura máxima y las precipitaciones explican al rendimiento de la producción y en la producción de papa en 97.96% y 97.95% respectivamente.

Phytoparasitic nematodes are a common problem in coffee production worldwide. In Peru, the proliferation of phytoparasitic nematodes in Coffea arabica L. var. Typica has negative impacts on coffee production and huge economic losses. The objective of this study was to determine the ecological interactions that influence the proliferation of phytoparasitic nematodes in C. arabica var. Typica in Quillabamba, Cusco, Peru. The density of phytoparasitic nematodes in the soil and root was evaluated using the modified Baermann channel method. Identification of genera and species of phytoparasitic nematodes was carried out in the different samples, based on descriptions and taxonomic keys. Physical and chemical parameters of the soil were evaluated. Principal component analysis (PCA) and a correlation network were employed to distribute the different species of nematodes. The variables soil texture, organic matter, pH, altitude, temperature and humidity were used. During the sampling, several genera of plant-parasitic nematodes were identified in addition to various categories of nematodes. Meloidogyne exigua, Pratylenchus coffeae, Allotrichodorus longispiculis and Helicotylenchus longicaudatus are among the specific species of nematodes identified. The genus with the highest incidence was Meloidogyne spp. with 77.3% in soil and 96% in roots, reaching an average density of 340 nematodes in 100 g of soil and 368 nematodes in 1 g of roots. The PCA results show that 63.7% of the variability of the data is retained in the first two components. PCA shows that the sampled areas were differentiated and grouped with the evaluated characteristics, while the nematodes overlap in the representation of the analysis, thus making it difficult to select them. Pearson’s correlation showed a negative correlation between altitude and soil nematode density (−0.22), suggesting that conditions at higher altitudes may be more unfavorable for nematode growth. In addition, a positive correlation was found between soil pH and organic matter (0.93, p < 0.001) and may influence nematode density. The factors that influence the density of nematodes in the soil and plant roots are multiple and complex, and their understanding is essential for the success of coffee production. The finding of the current study may be useful in the development of sustainable strategies for managing nematodes in coffee network production.

In the present research work inspired by Strogatz [3], we qualitatively analyze the mathematical model of love in which two people can find themselves: Romeo and Juliet, this analysis is based on four possible states of love: he does not pay attention to his heart, fire and ice, soul mate and Romeo the robot, with the aim of anticipating the evolution over time of love bond, by means of an autonomous system of ordinary differential equations. Finally, simulations were carried out using Matlab software to represent the phase portraits and thus observe the stability of the critical points.