The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and the protection of small-scale farmers’ practices. These issues are integral to food security and environmental health. Remote sensing technologies can assist precision agriculture in effectively addressing these complex problems by providing farmers with high-resolution lenses. The use of vegetation indices (VIs) is an essential component of remote sensing, which combines the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. A wide array of VIs can be used to classify the crops and evaluate their state and health. However, precisely this high number leads to difficulty in selecting the best VI and their combination for specific objectives. Without thorough documentation and analysis of appropriate VIs, users might find it difficult to use remote sensing data or obtain results with very low accuracy. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the effective use of VIs for the discrimination and monitoring of several important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities. The current review has shown that VIs appear to be suitable for mapping and monitoring agricultural crops, forage crops, meadows and pastures. Sentinel-1 and Sentinel-2 data were the most utilized sources, while some of the frequently used VIs were EVI, LAI, NDVI, GNDVI, PSRI, and SAVI. In most of the studies, an array of VIs needed to be employed to achieve a good discrimination of crops or prediction of yields. The main challenges in using VIs are related to the variation of the spectral characteristics during the vegetation period and to the similarities of the spectral signatures of various crops and semi-natural meadows. Thus, further studies are needed to establish appropriate models for the use of satellite data that would prove to have greater accuracy and provide more relevant information for the efficient monitoring of agricultural crops.

The paper aimed to present high pressure processing of food used to process liquid and solid foods with a high content of moisture. When using high pressure processing, microorganisms are destroyed, but covalent bonds do not break and the effect on processed food is minimal. In addition, the positive effect consists of the avoidance of excessive thermal treatments and chemical preservatives. High pressure has a small effect on low-molecular-weight compounds such as flavor compounds, vitamins, and pigments compared to thermal processes. Therefore, the quality of high pressure pasteurized food is very similar to that of fresh food products. The quality of foodstuffs during their shelf life is influenced to a greater extent by subsequent distribution and storage temperatures or by packaging rather than by the pressure treatment itself. Food products can be HPP in a batch system or a semi-continuous process. During HPP, the pressure is applied uniformly and simultaneously in all directions. After HPP the food will not return to its original size and shape due to pressure differences between the compressibility of air and water, unless the food is perfectly elastic. Pressure is instantaneously and uniformly transmitted independent of the size and geometry of food. Resultant pressure regulates most subsequent biochemical reactions occurring in treated products. This article provides an overview of current technology status

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, a slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and protection of the small-scale farmers’ practices, all issues integral to food security and environmental health. Remote sensing technologies can assist precision agriculture to effectively address these complex problems, by providing farmers with a high-resolution lens. The use of vegetation indices (VIs) is an essential component of remote sensing, which combine the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. Currently a wide array of VIs is available that could be used to provide a classification and an evaluation of the state and health of crops. However precisely this high number leads to difficulties in selecting the best VI and combination of VIs for a specific objective. Without a thorough documentation and analysis of appropriate VIs, users might be confronted with difficulties in using remote sensing data or even with a very low accuracy of the results. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the most important features related to the effective use of VIs for the discrimination and monitoring of the most important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities (from farmers, researchers up to institutions dealing with the centralization and monitoring of agricultural crops).

There is a worldwide trend that supports the rational use of chemicals in agriculture. It has become common knowledge that irresponsible application of pesticides can cause food security issues, by endangering human and animal health while also having negative environmental consequences. The aim of this experiment was to assess the qualitative parameters of spraying treatments in vineyards. To achieve this, a vineyard and orchard sprayer machine was used for the application of treatments under a gradient of pressures (3, 5, 7, 9 bar). Water-sensitive collectors were placed at three heights (0.8 m, 1.5 m, 2.5 m). Following spraying was determined using DepositScan: the volume median diameter characterization of droplets (DV 1, DV 5, DV 9), and coverage degrees of sprayings. Results indicated that best coverage degree and larger droplets tend to be deposited 1.5 m from the ground, which corresponds with the highest proximity to the positioning of the nozzles of the machine during application, and lowest coverage is found at the top, where droplets deposited also tend to be smaller. For the anti-drift nozzle model used in the study, the best coverage was obtained at a pressure of 5 bar. For sustainability of agricultural practices and rational use of pesticides, more research is required for optimization of increased precision spraying that could ensure high coverage at lower doses of chemicals and coarse droplets. In this way the quantity of product sprayed is expected to be reduced, due to minimization of off-target losses and increased efficiency. This can ensure that negative environmental impacts are lowered. Improved treatment application at higher positioning of the canopy remains a challenge and shall receive more attention.

Changing the degree to which animals feed is grinded can be done for hammer mills in several ways, namely: the use of sieves with different diameters, different hammers, different engine speeds.Grain milling energy consumption is influenced by the type of material used, its moisture content, size and type of hammers, sieves holes etc.In the present study we determined the influence of moisture and sieve mesh size on milling maize grain moisture of 11.1% and 17.6% using conventional hammer mill. Using three kinds of sieve apertures with a diameter of 4, 6 and 8 mm was determined from the specific grinding energy.

In the context of modern agriculture knowledge of soil properties becomes essential for the optimization of crop production. An increasing interest can be observed in last few years for conservative soil management practices such as no-tillage, that promise many long-term benefits for soil health. Aim of this research was to investigate the soil preparation mode for three models of disks (one flat and two corrugated) across different sowing speeds (3, 8 and 11 km/h) in order to identify ways to optimize no-tillage technology for crops with higher row spacing. Results have shown that soil cone index is a useful indicator for characterization of the general effect of sowing equipment on seedbed quality and consequently on root growth and plant development. More attention should be given in the future to possibilities to develop furrow openers and machines adapted to particular soil conditions as well as with real-time adjustment, in order to increase precision and feasibility of no-till sowing.