Sustainable Applications of Nanofibers in Agriculture and Water Treatment: A Review

Natural fibers are an important source for producing polymers, which are highly applicable in their nanoform and could be used in very broad fields such as filtration for water/wastewater treatment, biomedicine, food packaging, harvesting, and storage of energy due to their high specific surface area. These natural nanofibers could be mainly produced through plants, animals, and minerals, as well as produced from agricultural wastes. For strengthening these natural fibers, they may reinforce with some substances such as nanomaterials. Natural or biofiber-reinforced bio-composites and nano–bio-composites are considered better than conventional composites. The sustainable application of nanofibers in agricultural sectors is a promising approach and may involve plant protection and its growth through encapsulating many bio-active molecules or agrochemicals (i.e., pesticides, phytohormones, and fertilizers) for smart delivery at the targeted sites. The food industry and processing also are very important applicable fields of nanofibers, particularly food packaging, which may include using nanofibers for active–intelligent food packaging, and food freshness indicators. The removal of pollutants from soil, water, and air is an urgent field for nanofibers due to their high efficiency. Many new approaches or applicable agro-fields for nanofibers are expected in the future, such as using nanofibers as the indicators for CO and NH3. The role of nanofibers in the global fighting against COVID-19 may represent a crucial solution, particularly in producing face masks.

E-Gadget to Detect Food Freshness using IoT and ML

The food we consume plays an important role in our daily life. It provides us energy which is needed to work, grow, be active, and to learn and think. The healthy food is essential for good health and nutrition. Light, oxygen, heat, humidity, temperature and spoilage bacteria can all affect both safety and quality of perishable foods. Food kept at room temperature undergoes some chemical reactions after certain period of time, which affects the taste, texture and smell of a food. Consuming spoiled food is harmful for consumers as it can lead to foodborne diseases. This project aims at detecting spoiled food using appropriate sensors and monitoring gases released by the particular food item. Sensors will measure the different parameters of food such as pH, ammonia gas, oxygen level, moisture, etc. The microcontroller takes the readings from sensors and these readings then given as an input to a machine learning model which can decide whether the food is spoilt or not based on training data set. Also, we plan to implement a machine learning model which can calculate the lifespan of that food item. Index Terms: Arduino Uno, Food spoilage, IoT, Machine Learning, Sensors.

IoT System on Dynamic Fish Feeder Based on Fish Existence for Agriculture Aquaponic Breeders

Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed hardware. The controller controls the feeding and feedback mechanism based on attached sensors. An ultrasonic sensor is programmed with the controller to detect the level of food and waterproof ultrasonic to detect existing fish. The humidity sensor was used to measure the humidity in the food container to control the food freshness. Two servo motors were used to move the waterproof sensor to attract the fish and to dispense the food to the fish when existed. The result presents four measured levels that are the temperature of the food container, the quality of food based on humidity measured, fish detection counter and level of fish food in the container. Data analytics on all the measured levels was presented on the ThingSpeak platform by using Blynk to get data collections from all sensors. This research is significant for fish breeders that support IR4.0 system connected online and mobile apps which also contribute to today’s agriculture.

Multicolor PEGDA/LCNF Hydrogel in the Presence of Red Cabbage Anthocyanin Extract

Colorimetric indicator gels were developed by incorporating anthocyanin (AC) obtained from red cabbage into poly (ethylene glycol) diacrylate (PEGDA)-based hydrogel containing lignocellulose nanofiber (LCNF). The PEGDA-based hydrogel was prepared by mixing all of the mentioned components at the specific composition, and the hydrogels were cured under UV light (245 nm) for 1 min. The pH-response, UV absorption, swelling ratio, and mechanical properties of PEGDA/LCNF were determined. It was further found that PEGDA and LCNF mount play an important role in adjusting the mechanical properties of PEGDA/LCNF. In general, the presence of LCNF improved the mechanical properties and swelling ratio of PEGDA. The incorporation of red cabbage anthocyanin into the PEGDA/LCNF film showed multicolor response when specific pH buffers were introduced. Based on the multicolor response of PEGDA/LCNF/CA, this gel film indicator can be developed as a food freshness indicator that focuses on the detection of ammonia and amine compound.

Firms’ Investment Behaviours in Temperature-Controlled Supply Chain Networks

Delivering high-quality food into markets is a vital expectation of modern customers. The significant increase in consumers’ awareness of food freshness, nutrition, and safety makes the temperature-controlled supply chain (TCSC) the focus of food logistics safety. However, a large number of Chinese companies are still reluctant to invest in the food supply chain, resulting in a high rate of supply chain logistics loss. This research aims to establish an economic model to explain why these companies do not invest and under what conditions they will do. The results show that high economic investment is the main reason that hinders companies’ willingness to build TCSC. Large companies with bigger production are more willing to invest in TCSC than small companies. Besides, larger companies running with high-quality products could get more profit while small companies operating with normal products are less competitive.

Single Nanowire Gas Sensor Able to Distinguish Fish and Meat and Evaluate Their Degree of Freshness

A non-invasive, small, and fast device is needed for food freshness monitoring, as current techniques do not meet these criteria. In this study, a resistive sensor composed of a single semiconductor nanowire was used at different temperatures, combining the responses and processing them with multivariate statistical analysis techniques. The sensor, very sensitive to ammonia and total volatile basic nitrogen, proved to be able to distinguish samples of fish (marble trout, Salmo trutta marmoratus) and meat (pork, Sus scrofa domesticus), both stored at room temperature and 4 °C in the refrigerator. Once separated, the fish and meat samples were classified by the degree of freshness/degradation with two different classifiers. The sensor classified the samples (trout and pork) correctly in 95.2% of cases. The degree of freshness was correctly assessed in 90.5% of cases. Considering only the errors with repercussions (when a fresh sample was evaluated as degraded, or a degraded sample was evaluated as edible) the accuracy increased to 95.2%. Considering the size (less than a square millimeter) and the speed (less than a minute), this type of sensor could be used to monitor food production and distribution chains.