The objective of this research was to know the behavior of ten coffee cultivars against Hemileia vastatrix in San Ramón (Chanchamayo, Peru). The test was carried out from April 2017 to March 2018 at the Coffee Germplasm Bank, at the Regional Development Institute “La Génova” (San Ramón, Chanchamayo) of La Molina National Agrarian University. 10 cultivars were selected (Catimor, Pache, Mundo Novo, Pacamara, Caturra, Catuaí, Bourbon, Typica, Maragogype and Geisha), each one with 5 plants (2 × 1 m) of seven years of age, installed under the shade of trees of Inga sp. (12 × 12 m). For the statistical analysis, it was worked as a Completely Random Design, considering each cultivar as a treatment and each plant as a repetition. The severity was evaluated throughout a year, in the lower, middle and upper third of each plant, using a graphic scale. For the months with high severity, a comparison of means obtained in each third of the plant and for each variety was made. Then, the severity means obtained in each cultivar were compared. The results showed that the severity was different in each of the ten cultivars evaluated. Throughout the year, the highest severity values corresponded to the months of April, May and June 2017. The severity was greater in the lower third and was decreasing until the upper third of the plant, presenting statistically significant differences. Maragogype, presented the highest severity (15.9%) and Pacamara the lowest (1.3%), values that were also statistically different.

En el cultivo de piña en el Perú existe carencia de estudios sobre la fertilización, con fuentes orgánicas e inorgánicas. Por tal motivo, se llevó a cabo este experimento cuyos objetivos fueron determinar la influencia del abono orgánico Alopes Forte, con y sin una fertilización mineral, sobre el crecimiento vegetativo, la productividad, la calidad del fruto y aspectos económicos en la producción de este cultivo. El material vegetal usado fue la piña cultivar ‘Golden’, la cual fue sometida a los siguientes tratamientos: T1: Testigo; T2: Alopes Forte (25 ‰); T3: Alopes Forte (50 ‰); T4: Alopes Forte (20 ‰) + N150-P75-K200-Mg25-Ca25; T5: Alopes Forte (20 ‰) + N250-P125-K300-Mg50-Ca50; T6: N300-P150-K400-Mg50-Ca50 y T7: N500-P250-K600-Mg100- Ca100. Los resultados muestran que no hubo diferencias entre los tratamientos para el número de hojas, sin embargo en la longitud, peso fresco y seco de la hoja D, se destaca el tratamiento T7, mientras que en tenor nitrógeno (hoja D) fueron los tratamientos T4, T5, T6 y T7 los que mostraron mejor resultado. Tanto en las variables de calidad del fruto (diámetro inferior, medio, superior, diámetro del eje central del fruto, número de frutillos por fruto, longitud del fruto, peso fresco del fruto con corona y sin corona, y tenor de sólidos solubles) como en el ingreso y rentabilidad en la producción de piña se destacó el tratamiento T7. Estos resultados demuestran que el abono orgánico usado no tuvo influencia sobre las variables evaluadas, además, que el uso de fertilizantes sintéticos afectó positivamente a las variables en estudio.

Parchment coffee results from washing the coffee cherry, and its production has achieved a significant increase in the coffee-growing regions of Peru. Knowing the production pattern of this grain is essential to help coffee producers make decisions in the economic and social sector. As growth curves generally have sigmoidal behavior, which is well fit by non-linear models, this study aimed to model the cumulative production pattern of parchment coffee as a function of time (in months) in the year 2022, comparing the fit of the non-linear Logistic, Gompertz and von Bertalanffy models. The cumulative national production, and production of the departments of Huánuco and San Martín, in Peru, were analyzed. Data used to fit the models were obtained from the Ministry of Development and Irrigation (MIDAGRI) of Peru. To check the assumptions of normality, homoscedasticity, and independence of residuals, the Shapiro-Wilk, Breusch-Pagan, and Durbin-Watson tests were used, respectively. The model parameters were estimated using the least squares method using the Gauss-Newton algorithm in the R software. The goodness-of-fit of the models was tested using goodness-of-fit measures such as Coefficient of Determination (R2), Residual Standard Deviation (RSD), Akaike Information Criterion (AIC), and nonlinearity measures. Based on the models’ goodness-of-fit measures, the Gompertz model with a first-order autoregressive error term (AR1) fit best to national production data, and the Logistic model was the most suitable for describing the production of the departments of Huánuco, and San Martín.

The formulation of coffee blends is of paramount importance for the coffee industry, as it provides the product with an expressive ability to compete in the market and adds sensory attributes that complement the consumption experience. Through redundancy analysis and canonical correspondence analysis, it is possible to study the relationships between a set of sensory notes and a set of blends with different proportions of coffee variety through multivariate linear regression models. However, it is unrealistic to assume that such sensory responses are given linearly in relation to the formulation of the blends, since some coffee species have greater weight in the sensory evaluation (quadratic terms) and the effect of the mixtures (term of interaction). With this motivation, this work aims to propose the use of redundancy analysis and nonlinear correspondence analysis through multivariate polynomial regression to evaluate the acceptance of different varieties of coffee blends according to the scores given by the evaluators. Finally, it is concluded that there were gains in the percentage of total explained variance in the polynomial models in relation to the classic models.

The study of the indexes of water to Olea europea L. is important because it allows understanding of the water capacity of this species. This trial was carried out in the Valley Cañete with olive varieties ‘Frantoio’ and ‘Sevillana’ (both 10 years old), with the aim of determine its moisture content. In both varieties relative water content (CHR), the Content of water saturation (CAS), the water deficit for saturation (DAS), dry weight (PS) and fresh weight (FW) was measured. ‘Sevillana’ shown a CHR (73.7%), PS (0.180 g) and PF (0.330 g) were higher than in the cultivar 'Frantoio' (with values of 68.2%, 0.140 g and 0.258 g respectively). In conclusion, these results indicate that the variety ‘Sevillana’ has greater capacity than water ‘Frantoio’ to withstand arid environments.

Excessive changes in factor levels can lead to a high cost in practice and hinder the conduction of experiments, in addition to adding a higher computational cost and loss of the orthogonality property, resulting in numerical problems in estimating the parameters of a model. The sequential specification of experimental points, seen as treatments in a 2k factorial design, results in a high-order bias in some factors, which is caused by the accumulation of −1 or +1 signals. This study aimed to propose new designs generated by the simulated annealing technique, respecting the main A-optimal and D-optimal optimality criteria as random execution orders that minimize the order bias. This approach allowed the generation of 24 and 25 factorials, which were compared to the designs in standard order. The simulated annealing technique is a viable method to generate optimal designs with the same efficiency as the usual designs to obtain A-optimal and D-optimal designs with new execution orders, which minimize the effect of order bias relative to standard order designs. Regarding efficiency, the generated designs were precise in the variance of model parameter estimates, similar to the original designs.