Conference Agenda

This research aimed to evaluate the effect of ultrasound application on the convective drying kinetics of golden berry (Physalis peruviana) at different durations: 30, 60, and 90 minutes at 50°C. Golden berries were used to determine their initial moisture content using a moisture analyzer at a temperature of 105°C, which yielded a value of 82.55%. The samples were then divided into three groups of five units each and subjected to ultrasound treatment at a frequency of 40 kHz and a power of 100 watts for three different time intervals (30, 60, and 90 minutes). After ultrasound treatment, the samples were placed in an oven and their weights were measured every 10 minutes up to 210 minutes. The drying data obtained were fitted to the Page equation using a generalized reduced gradient algorithm in Excel. An analysis of variance (ANOVA) was performed with a significance level of 95%, testing two hypotheses: the null hypothesis, where all samples are the same, and the alternative hypothesis, where all samples are different. The results demonstrated that the 90-minute ultrasound treatment produced the best drying results and the lowest moisture content compared to the other treatments. This indicates that longer ultrasound exposure results in better drying efficiency.

The research was developed based on the problems of neglected ecotourism in the city of Cajamarca, difficulties that affect tourism, nature itself and the integral development of the city. Taking into account the aforementioned, this research will focus on taking advantage of ecotourism activities through the use of infrastructure designed with bamboo, a local material, whose typology has been taking place through ecoarchitecture or ecological architecture; in such a way that the objective of determining the sustainable properties of bamboo in the architecture for a bamboo ecotourism center in the city of Cajamarca 2024 is addressed. The methodology used is non-experimental through documentary review; From this, an architectural study can be carried out in the selected environment, using various instruments. At the conclusion of the research, different theoretical and technical guidelines were obtained, being applicable in different types of scales, in varied architectural forms, flexible functional spaces with virtual and mobile walls, as well as strategies to take advantage of the natural geometry of bamboo, use of terraces, free areas, and techniques for adequate siting and implementation, integrating the architecture and generating a connection with the environment.

This study evaluated the impact of osmotic dehydration (OD) and cutting pretreatments on the viscoelastic properties of discarded blueberries using three mathematical models: Maxwell, Peleg, and Guo-Campanella. The OD process was conducted in a 50 °Brix sucrose solution with a partial longitudinal cut. Viscoelastic properties were assessed through stress-relaxation curves obtained from compression tests. The findings indicated that both cutting and OD significantly reduced the initial compression force. All three models accurately described the experimental data (R² > 0.95), with the Maxwell model providing the best fit, followed by Guo-Campanella, and then Peleg. The Maxwell model effectively described the viscoelastic behavior by associating elastic elements with the solid part and viscous elements with the fluid part. It showed that the blueberry skin, being more resistant, exhibited purely elastic behavior, while internal structures combined both elastic and viscous elements. The Peleg model indicated that OD and cutting reduced the fruit's firmness. The Guo-Campanella model demonstrated a decrease in elastic modulus primarily due to OD. When blueberries were cut, the endocarp structure was most affected due to its empty spaces. OD drastically decreased the elastic and viscous properties by causing water loss and reduced turgor in the cells, impacting their mechanical properties. These findings should be considered to determine the potential positive or negative effects on subsequent processes, such as drying or overall product quality.

Abstract– Objective: To determine if the influence between the international reference price of avocado and the creation of economic value added in a Peruvian agribusiness is significant, complying with the fundamental principles of financial theory. Methods: To achieve this, economic time series analysis techniques are used in order to know the econometric influence between the international reference price of avocado on the generation of economic value added in the Peruvian agroindustry Results: Referring to the price of avocado and economic value added, a negative effect was found between these variables, indicating that the price of avocado is statistically significant with a high level of significance, i.e. this variable does have an effect on the EVA of the agroindustry at 90% confidence, with a coefficient of -292377. 9. Conclusions: The international reference price of avocado is a component of value in exports, this provides a deeper understanding of how external factors and internal factors, such as productive efficiency, influence the financial performance of Peruvian agribusiness and other companies in the sector.

Rice cultivation demands a significant amount of
water for irrigation, particularly in the Piura region of Peru,
where water supplies are limited. Currently, the region lacks
effective systems to conserve water resources, which could
increase the risk of water scarcity in the future. To address
this challenge, an integrated technological solution is proposed,
focusing on the development of a web and mobile application that
leverages the capabilities of the Internet of Things (IoT) for device
control and monitoring. This solution employs LoRa connectivity
for data transmission to the receiver, which utilizes the MQTT
protocol to send information to the Arduino IoT Cloud via 4G
LTE. Additionally, machine learning (ML), specifically the Long
Short-Term Memory (LSTM) algorithm, is integrated to predict
water consumption for irrigation. These predictions are based on
data from IoT devices and meteorological information obtained
through the OpenWeatherMap API. The research results indicate
a 56.8% reduction in water consumption when using this IoT
solution compared to the traditional flood irrigation method,
optimizing resource usage without impacting crop health. The
water consumption prediction model, evaluated with a root mean
square error (RMSE) of 1.31544, confirms the tool’s effectiveness
in accurately forecasting water needs. This technological solution
provides an efficient and sustainable tool to improve water
management in rice cultivation in Piura and mitigate the effects
of future water scarcity.

Most meat products come from small, medium-sized, or family-group farms that do not necessarily comply with safety practices, control, and monitoring. This study proposes strategies to mitigate various types of occupational risk and improve biosafety. Method: The study used PICOC guidelines to design the search equation and the application of PRISMA criteria to select documents. Then, the researcher in charge analyzed the research found in the Scopus database. Results: The study found factors that negatively impact workers' health, including prevention methods and risk reduction. Conclusions: This study proposed effective and innovative strategies related to disinfection and repel action and microbial reduction.