A new model of the stages of disintegration and hydrolysis, and co-digestion process following the classical Anaerobic Digestion Model No.1 (ADM1) structure is proposed. In the new method, substrate-microorganism relationships are represented using the Contois equation rather than the first order models previously used to represent substrates in the degradation process. This model was validated by assessing the biogas production from the co-digestion of vegetable (V) and manure (M) with variations in the V/M ratio in the feed. The highest biogas and yield levels were obtained when the feed ratio was 50/50 V/M. This finding was reproduced by running simulations of the original and modified ADM1. The original ADM1 explains the low digestibility and utilization of manure for biogas production as a consequence of a slow disintegration or hydrolysis stage, which depends exclusively on the disintegration and hydrolysis constants used. The new model offers a more mechanistic explanation; it assumes unfavorable substrate-microorganism relationships, which cause disintegration to become a limiting factor in the process. In addition, biogas production in the new model is primarily associated with carbohydrate degradation, as well as low concentrations and rapid consumption of intermediary metabolites, which do not favor the proliferation of acetanogenic or methanogenic communities. En este trabajo se propone un nuevo modelo de las etapas de desintegración e hidrólisis y un modelo de co-digestión, siguiendo la estructura del Anerobic Digestion Model No. 1 (ADM1). En el nuevo modelo, las relaciones sustrato-microorganismo se representan mediante la ecuación de Contois en lugar de los modelos de primer orden utilizados anteriormente para representar el proceso de degradación de los sustratos. Este modelo se validó evaluando la producción de biogás a partir de la co-digestión de vegetales (V) y estiércol (M) con variaciones en la relación V/M en la alimentación. Los niveles más altos de biogás y rendimiento se obtuvieron cuando la relación de alimentación fue de 50/50 V/M. Este hallazgo se reprodujo ejecutando simulaciones del ADM1 original y modificado. El ADM1 original explica la baja digestibilidad del estiércol para la producción de biogás como consecuencia de una etapa de desintegración e hidrólisis lenta, que depende exclusivamente de las constantes de desintegración e hidrólisis utilizadas. El nuevo modelo ofrece una explicación más mecanicista; asume relaciones de sustrato-microorganismo desfavorables, lo que hace que la desintegración se convierta en un factor limitante en el proceso.

Optical systems are used for analysing the internal composition and the external properties in food. The measurement of the lycopene content in fruits and vegetables is important because of its benefits to human health. Lycopene prevents cardiovascular diseases, cataracts, cancer, osteoporosis, male infertility, and peritonitis. Among the optical systems focused on the estimation and identification of lycopene molecule are high-performance liquid chromatography (HPLC), the colorimeter, infrared near NIR spectroscopy, UV-VIS spectroscopy, Raman spectroscopy, and the systems of multispectral imaging (MSI) and hyperspectral imaging (HSI). The main objective of this paper is to present a review of the current state of optical systems used to measure lycopene in fruits. It also reports important factors to be considered in order to improve the design and implementation of those optical systems. Finally, it was observed that measurements with HPLC and spectrophotometry present the best results but use toxic solvents and require specialized personnel for their use. Moreover, another widely used technique is colorimetry, which correlates the lycopene content using color descriptors, typically those of CIELAB. Likewise, it was identified that spectroscopic techniques and multispectral images are gaining importance because they are fast and non-invasive.

The inclusion of the Internet of Things (IoT) in indoor agricultural systems has become a fundamental tool for improving cultivation systems by providing key information for decision-making in pursuit of better performance. This article presents the design and implementation of an IoT-based agricultural system installed in a plant growth chamber for hydroponic cultivation under controlled conditions. The growth chamber is equipped with sensors for air temperature, relative humidity (RH), carbon dioxide (CO₂) and photosynthetically active photon flux, as well as control mechanisms such as humidifiers, full-spectrum Light Emitting Diode (LED) lamps, mini split air conditioner, pumps, a Wi-Fi surveillance camera, remote monitoring via a web application and three Nutrient Film Technique (NFT) hydroponic systems with a capacity of ten plants each. An ATmega2560 microcontroller manages the smart system using the MODBUS RS-485 communication protocol. To validate the proper functionality of the proposed system, a case study was conducted using lettuce crops, in which the impact of different nutrient solution concentrations (50%, 75% and 100%) on the phenotypic development and nutritional content of the plants was evaluated. The results obtained from the cultivation experiment, analyzed through analysis of variance (ANOVA), show that the treatment with 75% nutrient concentration provides an appropriate balance between resource use and nutritional quality, without affecting the chlorophyll content. This system represents a scalable and replicable alternative for protected agriculture.

Mango is the second most commercialized tropical fruit in the world, and Mexico is the major exporter. In terms of mango production, Manila´s variety represents a quarter of the total mangoes production in Mexico. However, the changes that occur on the phenolic compounds during the Manila mango ripening process are unknown. Quantitative analysis of the major phenolic compounds was conducted at different maturity stages, using several spectrophotometric measurements and by high-performance liquid chromatography (HPLC). At the late ripening stage was observed the biggest content in pulp and peel of total phenols (577 and 10547 mg EAG /100 g), flavonoids (95.33 and 537 mg EQ/100 g), and antioxidant capacity by DPPH (25 and 347 mmol TE/100 g). Some bioactive compounds achieve their highest values at optimal consumption ripening. Although they diminish when the fruit reaches a senescence appearance. This is the first study to prove that mangiferin by itself shows a higher correlation in antioxidant capacity compared to other phenolic compounds in mango peel, and this suggest that phenolic compounds may have an important role in the postharvest antioxidant metabolism in Manila mango fruit. On the other hand, the results show that the peel compared to the pulp contains higher amounts of total phenols, flavonoids, gallic acid, mangiferin and antioxidant capacity, so its use as an ingredient in the preparation of functional food products is recommended. More studies are needed to go in-depth in the changes of the content of phytochemicals during the ripening process in the peel and pulp mango, which ones could be caused by the hormones responsible for ripening in the fruit, such as ethylene, and bioavailability of these compounds at different stages of maturation. El mango es la segunda fruta tropical más comercializada del mundo y México es el principal exportador. En términos de producción de mango, la variedad Manila representa una cuarta parte de la producción total de mangos en México. Sin embargo, se desconocen los cambios que ocurren en los compuestos fenólicos durante el proceso de maduración del mango Manila. El análisis cuantitativo de los principales compuestos fenólicos se realizó en diferentes etapas de madurez, utilizando varias medidas espectrofotométricas y mediante cromatografía líquida de alta resolución (HPLC). En la etapa de madurez tardía se observó el mayor contenido en pulpa y cáscara de fenoles totales (577 y 10547 mg EAG / 100 g), flavonoides (95.33 y 537 mg EQ / 100 g) y capacidad antioxidante por DPPH (25 y 347 mmol TE / 100 g). Algunos compuestos bioactivos alcanzan sus valores más altos en el punto de madurez óptima. Aunque disminuyen cuando el fruto adquiere una apariencia de senescencia. Este es el primer estudio que demuestra que la mangiferina por sí misma presenta una alta correlación con la capacidad antioxidante en comparación con otros compuestos fenólicos de la cáscara de mango, y esto sugiere que los compuestos fenólicos pueden tener un papel importante en el metabolismo antioxidante postcosecha en el mango Manila. Por otro lado, los resultados muestran que la cáscara comparada con la pulpa contiene mayores cantidades de fenoles totales, flavonoides, ácido gálico, mangiferin y capacidad antioxidante por DPPH, por lo que se recomienda su uso como ingrediente en la elaboración de productos alimenticios fucionales. Se necesitan más estudios para profundizar en los cambios del contenido de fitoquímicos durante el proceso de maduración en la cáscara y pulpa del mango, los cuáles podrían ser provocados por las hormonas responsables de la maduración en el fruto, como el etileno, y la biodisponibilidad de estos compuestos en diferentes etapas de maduración.

Measuring lycopene in tomatoes is fundamental to the agrifood industry because of its health benefits. It is one of the leading quality criteria for consuming this fruit. Traditionally, the amount determination of this carotenoid is performed using the high-performance liquid chromatography (HPLC) technique. This is a very reliable and accurate method, but it has several disadvantages, such as long analysis time, high cost, and destruction of the sample. In this sense, this work proposes a low-cost sensor that correlates the lycopene content in tomato with the color present in its epicarp. A Raspberry Pi 4 programmed with Python language was used to develop the lycopene prediction model. Various regression models were evaluated using neural networks, fuzzy logic, and linear regression. The best model was the fuzzy nonlinear regression as the RGB input, with a correlation of R² = 0.99 and a mean error of 1.9 × 10⁻⁵. This work was able to demonstrate that it is possible to determine the lycopene content using a digital camera and a low-cost integrated system in a non-invasive way.