Plant fertility and soil quality are determined by many environmental factors. Good quality crops occur when plants are grown with optimal development, nutrition and formation of crop structural elements. With the intensification of agricultural production, the use of plant protection products and mineral fertilizers is increasing. This has led to a decrease in the humus content of the soil and to a deterioration of soil quality. One of the most effective measures to maintain soil fertility is fertilization with organic fertilizers. Recently, with the declining use of organic fertilizers, a partial solution to the problem may be fertilizers enriched with humus, amino acids, seaweed extracts and other plant nutrition activators. Microbiological products strengthen the root system, accelerate the process of photosynthesis, strengthen the plant's immune system, increase resistance to adverse environmental factors and improve soil structure. Rising prices of energy resources and the EU ecological policy goals are forcing farmers to seek solutions to reduce production costs and energy resources. At the same time, new and efficient measures are sought to increase soil fertility and quality.

The investigations were carried out at the Experimental Station of Vytautas Magnus University Agriculture Academy, Lithuania, in 2019–2020, in Calc(ar)i-Endohypogleyic Luvisol, a semi-neutral (pH_KCl 6.9), high phosphorus (232.6 mg kg^-1 P₂O₅), mid-potassium-level (111.0 mg kg^-1 K₂O), mid-humus-level (2.39%) soil, in order to evaluate the effect of biological preparations on winter wheat crop. Treatments of the experiment: Factor A – biological preparations: 1) without spraying, 2) complex of fulvic and humic acids with microorganisms (biological preparation A) was sprayed (norm 1.0 L ha^-1) in autumn, 3) complex of industrial biological waste (molasses) with microorganisms (biological preparation B) was sprayed (norm 2.0 L ha^-1) in autumn. Factor B - nitrogen rates: 1) fertilized with N₁₀₅, 2) fertilized with N₁₆₅.

Available phosphorus content was significantly higher in the soil where was applied biological preparation B at both levels of nitrogen fertilization. Biological preparation A increased available potassium content in the soil where the higher amount of nitrogen rate was used compared with the control. The use of biological preparations did not have a significant effect on the germination of winter wheat but tended to promote the tillering of winter wheat and increase the number of productive stems. The use of biological preparations tended to increase the assimilation area of winter wheat leaves, the weight of 1000 grains, quantity of grain per spike, mass of grain per spike and significantly (P≤0.05) increased winter wheat yield to compare with the control. Application of biological preparations significantly (P≤0.05) increased the decomposition of winter wheat straw.

A primary challenge for the horticultural industry is to ensure high yield and product quality while using resources in an efficient and sustainable way. Decision Support Systems-DSS are important tools to manage greenhouses and significantly affect resource efficiency and environmental impacts, but are not extensively used due to their complexity and lack of easy-to-use interfaces. Besides, greenhouses are complex dynamic non-linear systems with different simultaneous physical, chemical and biological processes and with different timescales, difficult to control with conventional control techniques.

HortiMED (H2020 PRIMA Grant No. 1915) aims to improve resource efficiency in greenhouses through an innovative and easy-to-use DSS supported by Artificial Intelligence-AI. HortiMED DSS integrates sensors, smart algorithms and efficient greenhouse control procedures, and applies AI techniques to deliver: 1-Expert advisory services to help farmers in intensive knowledge tasks where climatic, crop & nutrient variables decisively influence crop growth & productivity (e.g. precise water & fertilisers’ needs), and 2-Cost-effective partial or full automation of greenhouses (e.g. fertigation, ventilation, heating).

HortiMED takes advantage of the large datasets available in greenhouses to fuel AI algorithms, unleashing the power of greenhouse data and AI to shift from input-intensive to knowledge-intensive farming. HortiMED DSS relies on the use of: 1-Hybrid modelling combining well-known mechanistic models with AI techniques for the smart determination of setpoints; 2-Multilayer hierarchical control architecture to deal with the different time scales of greenhouse dynamics; and 3- Internet of Things to integrate information from diverse sources (e.g. sensors, actuators, growers’ field book, historic records, weather forecasts, etc.).

The most prevalent medium for conveying research findings and developments within and beyond the domain of agriculture is text whether in the form of scholarly publications, reports, articles, or posts on websites and social media channels. Mining information from text is of utmost importance in order to allow the agricultural (research) community to keep track of the most recent advancements, as well as to update ontologies and other structures that are used to model and formally represent domain-specific knowledge. However, the pace and volume at which texts are currently being produced render the manual extract of information impossible. Therefore, we need to reside in technology-supported, machine learning-based methods capable of mining information from large corpora of unstructured text. Within this context, the aim of this paper is to describe a model for the automated identification and extraction of agricultural terms mentioned in texts that has been built upon spaCy – a free, open-source library for Natural Language Processing in Python. The model has been trained on a properly selected corpus of agriculture-related texts, manually annotated in regard to mentions of agricultural terms. The performance of the model has been evaluated against standard metrics and compared to other similar and baseline term recognition approaches. A detailed discussion is made about the exploitation of the proposed model in terms of further research.

Abstract: Organic food is progressively boosting the market and getting more attractive to consumers, who usually feel more confident about these products because of their safer, healthier, and more eco-friendly characteristics when compared to conventional agriculture products (Gomiero, 2018). On the other hand, the agricultural sector needs to face specific challenges and find long-lasting solutions towards agricultural and food sustainability. With this objective, some tools such as better farming systems, new technologies, quality education, and effective business models have been proposed as potential tools (Movilla-Pateiro et al., 2020). The EcoChestnut European project offers an innovative vocational training process to support the development of organic chestnut production in Europe, integrating into a common curriculum all aspects of the development of organic farming, processing, and production of chestnut products; from farming techniques and production methods of organic chestnuts and chestnut products as a specific and traditional product to more transversal topics such as marketing, communication, and corporate social responsibility. The project aims to develop a comprehensive training course on organic chestnut farming and chestnut products manufacturing that will help to bring organic agriculture within reach of traditional farmers. EcoChestnut will also provide the vocational trainers with learning methods and material to encourage farmers in their initiative. In this context, the updating on the latest techniques and methods of farming to be competitive and up to date together with socioeconomic factors must be considered since all this knowledge claims to be transmitted to farmers, to set and apply the basis of a sustainable business in the field of agronomy and organic production.

Acknowledgments: The research leading to these results was supported by MICINN supporting the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891); by Xunta de Galicia for supporting the program EXCELENCIA-ED431F 2020/12, and the pre-doctoral grant of M. Carpena (ED481A 2021/313). Authors are grateful to Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003), to the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019). The JU receives support from the European Union’s Horizon 2020 research and innovation program and the Bio Based Industries Consortium. The project SYSTEMIC Knowledge hub on Nutrition and Food Security, has received funding from national research funding parties in Belgium (FWO), France (INRA), Germany (BLE), Italy (MIPAAF), Latvia (IZM), Norway (RCN), Portugal (FCT), and Spain (AEI) in a joint action of JPI HDHL, JPI-OCEANS and FACCE-JPI launched in 2019 under the ERA-NET ERA-HDHL (n° 696295). The authors would like to thank EcoChestnut Project (Erasmus+ KA202) supporting this research and initiative.

Bibliography:

Gomiero, T. (2018). Food quality assessment in organic vs. conventional agricultural produce: Findings and issues. Applied Soil Ecology, 123, 714–728. https://doi.org/10.1016/j.apsoil.2017.10.014

Movilla-Pateiro, L., Mahou-Lago, X. M., Doval, M. I., & Simal-Gandara, J. (2020). Toward a sustainable metric and indicators for the goal of sustainability in agricultural and food production. Critical Reviews in Food Science and Nutrition, April, 1–22. https://doi.org/10.1080/10408398.2020.1754161

Abstract

The objective of this work is the evaluation of some biochemical, pharmacological and nutritional properties of flaxseed (Linum usitatissimum L.) with a view to its application as a dairy dessert. Five dessert formulations were developed by substituting the milk powder and the carrageenan gelling agent with flaxseed powder. Biochemical analysis and sensory quality assessment of the different formulations were carried out.

The results of the phytochemical analysis show that flaxseed is rich in bioactive substances, namely flavonoids, carotenoids, alkaloids, tannins, quinines and mucilage. The extraction yield of the latter is of the order of 7.08%. In addition, it is rich in unsaturated fatty acids: linolenic acid (52.69%), linoleic acid (15.96%) and oleic acid (20.21%). The evaluation of the antioxidant activity of the aqueous extracts and mucilage of this seed, carried out using the DPPH free radical scavenging method, indicated that the two extracts showed considerable antioxidant activity of, respectively, 18.97±4.27% and 12.31±4.96% at a concentration of 0.025g/ml (crude extract).

Formulation F1, composed of 50g of flaxseed powder without cocoa, was chosen as the best formulation by tasters for its texture, smell, taste and color. It is also rich in flavonoids.

Dairy dessert based on flaxseed powder could be considered as a new functional dessert containing healthy food.

Nuclear technology can play an important role in innovating weapons capabilities and energy. The use of the influence of radioisotopes, the agricultural sector has made tremendous progress. Fertilizers are used in agriculture to increase soil fertility, thereby increasing crop yields. Radioisotopes are used to produce high-yield crop seeds to increase agricultural production. Which may have produced such a high crop yield due to the use of fertilizers in many countries/regions, the use of chemical fertilizers is very expensive, improper use will lead to a waste of money/resources and may damage the environment. Radioisotopes can be applied in a variety of ways to solve many problems in the agricultural industry and improve industry efficiency. These applications are particularly important for resource-poor developing countries or regions like water is scarce due to drought, and for protecting natural resources while addressing food security challenges.This article will explore how to use radiation to improve plant nutrition in fertilizers and produce seed variants, both of which have created higher efficiency in the production.

Sorghum (Sorghum bicolor L.) was mutated and bred for the purpose of securing food shortages in drylands and grain varieties as a substitute. From the color of the seeds, a promising variety suitable for food and feed was obtained with drought resistance and high total protein content.Our experience has shown that using radiations for crop improvement has come to stay as an efficient plant breeding method complementing the conventional methods. Clearly, the nuclear technologies have benefited the farmers, traders and end-users and will continue to play a significant role in addressing food and nutritional security.

The potato cultivars may differ in chemical, physical, sensory and functional properties. Therefore, the correct identification of potato cultivars is of great importance for both processing and cultivation. The application of machine learning enables the non-destructive, objective, repeatability and inexpensive quality evaluation. The objective of this study was to discriminate potato cultivars using models developed based on textures of tuber images. The potatoes belonging to cultivars ‘Irga’, ‘Riviera’ and ‘Colomba’ were harvested from fields located in Poland. The washed, cleaned and air-dried tubers of each cultivar were imaged using a digital camera in one hundred repetitions. The acquired images were converted to color channels R, G, B, L, a, b, X, Y, Z, U, V. In the case of each potato tuber image, about two thousand texture features were calculated and were used to build discriminative models. The most successful model included 29 selected attributes (1 from color channel R, 2 from channel G, 1 from channel B, 7 from channel a, 2 from channel b, 1 from channel X, 3 from channel Z, 2 from channel U, 10 from channel V). The highest accuracies of cultivar identification of potato tubers reached 99% for the IBk classifier from the group of Lazy, 98% for Multilayer Perceptron (Functions), 97% for Logistic (Functions), PART (Rules) and J48, LMT, Random Forest (Decision Trees), 96% for Bayes Net (Bayes), 95% for Logit Boost (Meta), 94% for Naive Bayes (Bayes). The developed models can be used to avoid mixing potato cultivars. Postharvest cultivar authentication can contribute to providing consumers with high-quality products.

Leaves of vines affected by the grapevine trunk disease esca complex show different degrees of severity throughout the growing season. Affected plants can still yield satisfactorily, although some berries present sclerotic spots. Little information is available on the relationship between foliar symptom severity and the quality of berries. The aim of this work was to evaluate the effect of esca complex severity on the primary metabolites of healthy berries. Berry samples were collected from healthy (control) and symptomatic vines of the white varieties Viosinho and Malvasia-fina grown 100 m apart. All plants evaluated have expressed initial symptoms in August, but showed different degrees of severity at harvest, namely chlorotic and scorched leaves (severity level 1) and tiger stripe leaves (severity level 2). The total fatty acid content was reduced in both varieties, and the reduction was mostly attributed to saturated fatty acids. On the contrary, levels of polyunsaturated fatty acids increased, probably as a defense mechanism. Among organic acids, tartaric acid levels were unchanged in Malvasia-fina, but increased with symptom progression in Viosinho; the opposite was observed for malic acid. The total free sugar content increased with symptom progression, and fructose showed the most significant variation. Varietal differences were observed in the response of amino acids, whose levels increased in Malvasia-fina and decreased in Viosinho. These varietal differences might have resulted in different degrees of host resistance, and this might explain why disease incidence and severity were more pronounced in Malvasia-fina than Viosinho.

The paper presents research of production possibilities of miscanthus (Mischantus x giganteus Greef et Deu) in agroecological conditions of Serbia. For that purpose, an experiment was set up in Srem on the site of Podunavlje village of Surduk. The soil on which the plantation was established in 2012 belongs to the type of carbonate chernozem on a loess plateau, at an altitude of 150 m. Morphological characteristics and yield of dry miscanthus stalks during five years, from 2015 to 2019, as well as the content of cellulose in dry stalks depending on agroecological conditions and variants of fertilization without top dressing and with spring top dressing of 30 kg ha¹ of nitrogen fertilizer were analyzed. The highest recorded yield of dry stalks was in 2019 (34,525 kg ha¹), and the lowest recorded yield in the dry year of 2017 (17,980 kg ha¹) both in the variant with top-dressing.

Identifying annual forage legumes suitable for summer cultivation in terms of forage yield and quality can be a solution to provide a part of required forage. In order to evaluate the quantitative and qualitative traits of three types of summer legumes, including cowpea (Mashhad cultivar), mung bean (Parto cultivar) and guar (local cultivar of Sistan), an experiment was conducted in the Seed and Plant Research Improvement Institute (SPII), Karaj, Iran for two years in 2019-2020. The study included four irrigation treatments (irrigation after 60, 100 and 140 mm of evaporation pan, Class A cumulative pan evaporation) as the main plot and the three legume species as subplots, was carried out as a split plot experiment in a randomized complete block design with three replications. The combined analysis and comparison of means showed that the highest mean fresh forage yield was obtained for cowpea and mung bean (22.29 and 20.39 ton per hectare, respectively), while 9.37 tons per hectare was obtained for guar, although dry forage yield difference between cowpea and mung bean was not significant (4.58 and 3.77 Tha^-1, respectively). Also, dry forage yield difference between two irrigation levels (60 mm and 100 mm) was not significant (5.03 and 4.71 tons per hectare, respectively). The highest percent of crude protein was observed at normal irrigation level for mung bean (16.97%). Also, the highest levels of insoluble fiber in neutral detergent (NDF) and metabolizable energy (30.90 and 2.30, respectively) were observed for mung bean at severe stress level. Finally, the based on the results, for saving irrigation water in area where water resource is limitation, irrigation after 100 mm evaporation in the three legume species can be recommended.