Appropriate soil conditions are important to the success of tomato culture. In fact, there are mineral elements that are essential for the good and healthy development of tomatoes, namely, nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, iron, and zinc. Additionally, organic matter and pH play an important part in the process. In this context, this study aimed to characterize a soil allocated to the production of an industrial tomato variety in the south of Portugal. As such, mineral elements content, pH, electrical conductivity, humidity, organic matter, and color (without humidity and having or not organic matter) were analyzed in 16 soil samples before any type of soil preparation. Through principal components analysis (PCA) was possible to observe that electrical conductivity and humidity are more correlated with each other than pH and organic matter. Besides, pH of soil varied between 6.9 (minimum) and 7.3 (maximum) being in accordance with the ideal range values for tomato production. Also, regarding quantification of mineral elements Fe showed a higher content, followed by K, Ca, P, Mg, S, Zn, and As. However, regarding the color of the soil without humidity and without humidity and organic matter, there were significant differences between CieLab parameters (L, Chroma, and Hue). Nevertheless, soil conditions of the field presented good requirements for tomato production, despite the higher levels of Fe in the soil and the presence of As.

Drought is one of the most important problems of crop production in arid and semi-arid regions of the world. The application of some materials, such as superabsorbent polymers in the soil, increases the water retention in the soil and thus reduces water consumption and leaching of fertilizers, therefore is one of the best solutions for water management in water deficit conditions. This study aimed to investigate the effects of superabsorbent on some characteristics of sesame under different irrigation intervals. This experiment was performed in a three replicated-split plot factorial, arranged in RCBD with three drought factors as the main plot (Irrigation interval using cumulative evaporation from class A pan: 80 mm (I₁), 160 mm (I₂), and 240 mm (I₃), and superabsorbent (SAPs) Stockosorb in three levels (0, 100, 200 kg ha^-1) (Z₀, Z₁, Z₂) as the subplots. The results showed that water deficit intensively decreased relative water content (RWC), Leaf area index (LAI), and crop growth rate (CGR) in both mild water stress (I₂) and sever water stress (I₃) compare to normal irrigation (I₁). SAPs mitigated the adverse effects of water deficit by improving RWC, LAI, and CGR. Due to the problem of water supply for plants in arid semi-arid regions, the use of 200 kg ha^-1 superabsorbents with 80 mm evaporation from class A pan be recommended as a successful method to maintain moisture and increase the growth and development of sesame.

Experimental chambers play an important role in agronomy and plant science by maintaining and providing ideal conditions so that experimental data is not affected. It is known that the environmental parameters of the experimental chambers can fluctuate, which can prevent the repetition of the experiments in the future (Lee and Rawlings, 1982; Potvin and Tardif, 1988). To ensure that the environmental parameters inside the chamber are within the required parameters, the best solution is to be able to record and monitor them. The recording and monitoring of environmental variables within an experimentation chamber are carried out to increase the repeatability of experiments in the future, in addition to providing researchers with real-time information on the conditions in which their tests are located.

Single board computers such as Raspberry Pi [www.raspberrypi.org], which use open software such as node-RED [nodered.org] offers the opportunity to develop such an intelligent system for monitoring the different light, temperature and humidity sensors of the experiment chamber.

Single board computers offer a high degree of flexibility and can be used in many different applications such as Internet of Things (IoT), Artificial Intelligence (AI), Application Programming Interface (API). IoT devices are objects connected to the Internet that are capable of collecting data and sending it over the Internet to store and process information in APIs, for example Google Cloud Platform. In addition, node-RED allows the creation of a chatbot in Telegram that interacts with the system, predicting and informing the user of possible problems that may arise during the course of the experiments, providing the AI ​​system.

Citrus fruits are considered in Algeria as a strategic crop, given their importance in food and human health. The latter attract a phytophagous fauna as well as their natural enemies, quite remarkable ensuring a natural regulation. The parasitoid inventory was conducted out in three citrus orchards of the University of Mostaganem's experimental farm in Mazagran during the 2018-2019 year, with a total of thirty citrus trees studied. The parasitoids insects were identified in the laboratory using a binocular lope and direct inspection while processing leaves gathered. This study enabled the identification of a group of distinct parasitoids that grow on harmful insects such as aphids and cochineal insects and some of which have been found as adults, who are belong to different families: Aphelinidae, Trichogrammatidae, Braconidae, Chalcidoidea, Figitidae, among which we can quote: Encarsia sp., Aphytis sp., Trichogramma sp., Lysiphlebus sp. Bracon sp, Aphidius matricariae, Praon sp, Alloxysta sp and several other parasitiods are yet to be identified. Natural enemies reflect the natural ecological integrity of ecosystems, Elekçİoğlu, 2007 have found natural enemies such as Aphytis melinus, Chrysoperla carnea., Conwentzia sp. Chilocorus bipustulatus., Exochomus quadripustulatus., and Adonia variegata. These findings may be sufficient for an effective first step in learning about auxiliary insects in order to establish proper breeding methods and then carry out a biological control.

Batagur affinis (Southern river terrapin or locally known as "tuntung sungai") in the Indochina region is a critically endangered freshwater turtle species. Despite numerous fundamental studies on the biological properties of B. affinis, there are significant concerns regarding the extent of population differentiation, genomic structure, and genetic variability within their populations due to a lack of genetic-based investigations. A lack of basic circumstances such as phylogenetic relationships and population genetic structure would harm their long-term conservation. As a result, this study was carried out for the first time to characterise the genetic structure of two B. affinis subspecies (B. affinis affinis and B. affinis edwardmolli) using cross-amplification of Batagur trivittata microsatellites and a total of 80 collected specimens from four Malaysian populations. Each sample's genomic DNA was taken for polymerase chain reaction (PCR) amplification and fragment analysis. Five microsatellite primers were used to identify polymorphic loci in B.affinis samples. In B. affinis, the number of alleles per locus ranged from 21 to 37. Microsatellites analysis revealed that there was little genetic heterogeneity among the B. affinis populations. The average observed heterozygozygosity (HO = 0.51) was lower than the typical heterozygozygosity found in most aquatic populations (HO = 0.79). The presence of inbreeding across distinct populations of B. affinis was also supported by the high FIS values (mean FIS = 0.3850) and low FST values (mean FST = 0.0893). Finally, this study offered light on the population structure of B.affinis in the Indochina region.

Since ancient times, honey has been considered not only a sweet food but also known as a remedy against diseases, due to its antioxidant properties.

The purpose of this study was to assess the total phenolic and flavonoid contents from Romanian raw monofloral honey and to establish their correlations with several qualitative parameters. In 2019, 28 samples were harvested: 8 acacia; 7 linden; 5 rapeseed, 5 sunflower and 3 mint, then analyzed in accordance with standardized methods, to measure: color intensity, water insoluble solids content, refractive index, moisture content, solid substances content, total soluble substances content, specific gravity, pH, free acidity, ash content, electrical conductivity, total phenols content and total flavonoids content.

Pearson test shown several correlation levels of total phenols content with other compounds: strong positive with total flavonoids (r=0.76) and color intensity (r=0.72); moderate positive with free acidity (r=0.57), ash content (r=0.51) and electrical conductivity (r=0.53); weak negative with pH (r=-0.23).

For total flavonoids content, correlations were: strong positive with color intensity (r=0.81), ash content (r=0.76) and electrical conductivity (r=0.73); fairly strong positive with free acidity (r=0.65); low positive between total flavonoids content and moisture (r= 0.35).

The relevant levels of polyphenols and flavonoids identified in the analyzed honey demonstrate its antioxidant potential, as essential nutritional and sanogenic features in human nutrition.

Predicted increases in the atmospheric CO₂ concentration and the earth's mean surface temperature will be accompanied by a higher incidence of drought events. These environmental changes are likely to adversely affect crop productivity and quality, including wheat, an essential food in the human diet. We investigated the primary C-N metabolism response to drought stress at the whole-plant level and its dependence on plant development in bread wheat grown under combined elevated CO₂ and temperature. With this aim, the content of carbohydrates, nitrate, proteins and amino acids, together with the biomass were assessed in flag leaves and roots of wheat grown in controlled environment chambers at both ear emergence and anthesis stages. Multifactorial analysis revealed that the organ was the main factor explaining data variation. The physiological and biochemical traits in the flag leaves were more affected by drought than growth stage, leading to an accumulation of soluble carbohydrates, nitrate and amino acids. By contrast, roots were affected by the developmental stages but not by the treatment. The root content of fructose, glucose, starch and amino acids was higher at ear emergence than anthesis, whereas the accumulation of sucrose, fructans, proteins and nitrate increased at the latest growth stage. This study provides new insights into the reprograming of primary metabolism at whole plant level throughout the development in response to the future climate scenario, which could help to select traits ensuring sustainable food production systems that strengthen capacity for adaptation to climate change following the Sustainable Development Goals of 2030 Agenda.

This paper focuses on livestock monitoring in smart farm to improve animal well-being and production. The great potential for increased automation and technological innovation in agriculture help livestock farmers in monitoring the welfare of their animals for precision livestock farming. A new acoustical method exploiting contextual information is introduced for cattle vocal classification. The proposed scheme considers the raw recordings which contain cattle sounds. Then a set of contextual acoustic features is constructed as input to the MSVM classifier to track the types of cattle vocalizations. Categorized noisy cattle calls are finally classified into four types of calls (i.e. cattle food anticipating call, animal estrus call, cough sound, and normal call) with an overall classification accuracy of 89.80% outperforming the results obtained using conventional MFCC features. We have used an open access dataset consists of 270 cattle classification records acquired using multiple sound sensors. Promising results are obtained by the proposed method for livestock monitoring enabling farm owners to determine the status of their cattle.

Material and energy metabolism takes place continuously between plants and their surrounding environment. Plants not only create biomass but also reduce technological pollutants in the environment. Temperature pulsations in the plant's gas exchange system induce thermodynamic processes that are involved in energy conversion. It has been found that during the sunny day of the day, the plant leaf is powered by a thermal jet engine (a biological prototype of a thermal engine) that generates mechanical energy. The operation of a plant leaf heat engine (biological prototype) is based on the change in pressure potential energy in the leaf gas exchange system. The generated mechanical energy in the plant leaf stimulates gas exchange with the environment and intensifies the assimilation process. Theoretical and experimental studies are presented, which show plant leaf temperature fluctuations, plant leaf stomata pressure pulsations. The thermal efficiency coefficient η_t of a plant leaf heat engine is very low. η_t = 0.003 and depends on the natural environmental conditions of the solar radiation density provided to the plant leaf, and the mechanical energy is converted from 0.06 to 0.6W/m². Energy conversion is 0.3% of the heat involved in the convective heat exchange of the sheet with the environment. The principle and possibility of transforming the thermal energy used in the vital processes of plants into mechanical energy have been used in the technique of plant leaf relatively recently.

Urban agriculture is receiving increased research attention not only for food security and public health but for mitigating the impacts of urbanization and climate change. In cities, rooftop urban farms provide a solution for the limited space at the ground level. However, rooftop urban farming poses several challenges, including increased need for workforce and site visits and demand for efficient water use. Recent advancements in Information and Communication Technology (ICT) and the Internet of Things (IoT) have enabled a tremendous suite of low-cost, wireless sensor nodes. In this work, an IoT-enabled approach is introduced to improve water management in an urban rooftop farm in downtown Toronto, Canada. Low-cost resistive water level sensors were calibrated and integrated into wireless sensor nodes to send data through LoRaWAN, an IoT protocol, to The Things Network (TTN) console, after which the processed data is visualized to the user dashboard. This paper addresses the main design stages, field deployment, and suggestions for maintenance learned through monitoring the growing season of 2021. The combination of low-cost sensors, user-friendly microcontrollers and open-source platforms provides an opportunity to improve decision-making, lower costs and reduce reliance on labour.