One of the main factors affecting the productivity of plant cultivation is water scarcity. Likewise, "hierba buena" (Mentha spicata) is considered a plant with beneficial characteristics for health due to its antidiabetic, anti-inflammatory, antioxidant, and digestionimproving properties. In the present work we examined the use of hydrogel in the cultivation of Mentha spicata, evaluating its effect on growth in the cauline and root systems. A control sample "A" without the application of the hydrogel, a sample "B" in the presence of hydrogel with soil, and a sample "C" containing hydrogel and a guano substrate were analyzed. Greater growth was observed in the cauline system in sample "B" with a size of 21.400 ± 0.337 cm and 4.300 ± 0.0816 cm in stem and leaves, respectively; growth in this system could be associated with the thermoregulatory role of the hydrogel in the presence of soil which favored the growth of this zone. These results are favorable since the main sources of its nutrients and the plant zone that is most used are found in the caulinar system.

Nowadays, nutritional foods have a great impact on healthy diets. In particular, maca, oatmeal, broad bean, soybean, and algarrobo are widely used in different ways in the daily diets of many people due to their nutritional components. However, many of these foods share certain physical similarities with others of lower quality, making it difficult to identify them with certainty. Few studies have been conducted to find any differences using practical techniques with minimal preparation and in short durations. In this work, Principal Component Analysis (PCA) and Near Infrared Spectroscopy (NIR) were used to classify and distinguish samples based on their chemical properties. The spectral data were pretreated to further highlight the differences among the samples determined via PCA. The results indicate that the raw spectral data of all the samples had similar patterns, and their respective PCA analysis results could not be used to differentiate them. However, pretreated data differentiated the foods in separate clusters according to score plots. The main difference was a C-O band that corresponded to a vibration mode at 4644 cm⁻¹ associated with protein content. PCA combined with spectral analysis can be used to differentiate and classify foods using small samples through the chemical properties on their surfaces. This study contributes new knowledge toward the more precise identification of foods, even if they are combined.