Progressive type of controlled environment horticulture, such as plant factories, enables the precise control of cultivation environment parameters. The experiments were performed at the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry in the year of 2017. The aim of this study was to evaluate the effects of different irradiance levels produced by solid state light-emitting diodes (LEDs) on nitrates, nitrites and organic acids contents in tatsoi (Brassica rapa var. rosularis), cultivated in the controlled environment chambers. Plants were cultivated under combinations of red (640, 660 nm), blue (445 nm) and far red (731nm) LEDs at photosynthetic photon flux density (PPFD) level of 200 µmol mE-2 sE-1. At the pre-harvest stage, PPFD was increased to 300 µmol mE-2 sE-1 by elevating the fluxes of different spectral components for 3 days. The contents of nitrates, nitrites and organic acids were evaluated. The results propose the metabolic interface between nitrates, nitrites and organic acids in green vegetables, sensitive for lighting conditions. The higher intensity of LED light at pre-harvest stage led to decreased contents of nitrates in tatsoi. The increased intensity of blue 455 nm light led to lower contents of nitrates and higher of organic acids in comparison to red 640 nm. In addition, the increased intensity of red 640 nm led to significantly higher (p≤0.05) contents of nitrites. The target management of LED light spectra and intensity at pre-harvest stage could be used to reduced nitrates and increased organic acids in tatsoi.

Plant factories provide possibilities to get optimal yield of green leafy vegetables entire year independent from the season. The technology of light-emitting diode (LEDs) light has become one of the most powerful tools in photophysiological researches of various horticultural plants. In order to manage plant physiology and improve productivity, it is necessary to develop new LEDs technologies in horticulture. The aim of the study was to investigate different lighting intensities and elevated red light (660 nm) effect on tatsoi photosynthetic parameters. All plants were grown under the same light sources where overall photosynthetic photon flux density (PPFD) varied from 200 to 300 µmol mE-2 sE-1. Three days before harvesting red light intensity (640 and 660 nm) was increased until 132 µmol mE-2 sE-1 and 660 nm until 188 µmol mE-2 sE-1 at 16 hours photoperiod. In the last treatment merely 24 hours photoperiod was applied. The photosynthetic indices in tatsoi were determined by non-destructive methods using LI-6400XT portable photosynthesis system, OS5p fluorometer, DUALEX optical sensor and CID leaf spectrometer. Research was performed in 2017 – 2018 winter season. The obtained data revealed that the total photosynthetic photon flux density (PPFD) at level of 200 µmol mE-2 sE-1 was sufficient for optimal CO2 assimilation in tatsoi plants. The increased PPFD of LED light at pre-harvest stage resulted in reduced photosynthetic parameters of plants.

The objective of the study was to analyze measurements of the sires used in Latvian Warmblood (LWB) and Latvian Heavy Warmblood (LHWB) breeding programs in the period 2003 – 2017, two major horse populations in Latvia included in one studbook. The Latvian Warmblood has an open studbook for breeding sport horses, whereas the Latvian Heavy Warmblood is a partly closed studbook. Measuring information for all sires with at least one foal born (n=834) in the respective time period was retrieved from the Latvian horse database, with 673 stallions measured at least once. The data consisted of direct measurements – height at withers, chest circumference and cannon bone circumference – and two calculated indices – massivity index and boniness index. Average values of adult stallions were analyzed in four groups – LWB, LHWB, ‘other warmbloods’ and refining breeds, with LWB and ‘other warmbloods’ showing similar average values. Sires were divided by use in breeding into 3-year periods to observe a possible change in the breeding objective and stallion choice, however, no significant differences were found in LWB or LHWB. Average measurements of stallions used in the LWB breeding program (different breeds) were 168.6 ± 4.3 cm for height at withers, 194.4 ± 6.6 cm for chest circumference, 21.8 ± 1.0 cm for cannon bone circumference, massivity index 115.5 ± 3.1, boniness index 13.0 ± 0.5. Average measurements of stallions used in the LHWB breeding program (only LHWB stallions) were 167.6 ± 4.6 cm, 201.4 ± 7.3 cm, 23.7 ± 1.0 cm, respectively, and massivity index 120.0 ± 5.0, boniness index 14.1 ± 0.6. Significant differences between LWB and LHWB stallions were observed in all parameters, except height at withers, and between measurements at the age of 2, 3, 4 years and adult (5 and more years).

Farming outputs in agriculture depend on the nature of production, i.e. different farming systems generate different outputs. All these outputs are important for the society, and, therefore, require an integrated approach in view of the specific farming characteristics, where market and non-market outputs are taken into account. Therefore, the paper focuses on analysis of farming system outputs and methods of their evaluation. The objectives of this paper are to define the features of different farming systems and their outputs, then, to analyse the methods of evaluation of farming system outputs used in the studies. In order to achieve the research aim, analysis of economic scientific literature has been conducted; characteristics of farming systems and their outputs have been analysed; evaluation methods of the market and non-market farming system outputs, revealing their advantages and disadvantages, have been examined. Methods of systemic and logic analysis have been applied to analysis of the farming system outputs and their evaluation. The analysis has shown that intensive farming systems generate more market goods, while extensive farming systems – more public goods. Price-based methods are mostly used for the evaluation of market outputs of farming systems. Stated preferences methods are the most universal techniques used for the determination of the values from non-market farming system outputs. Hedonic pricing approaches are used for evaluation of specific agricultural public goods related to recreation or leisure and related to the particular groups of users.

Every day millions of new data records with spatial component are produced in the world, which provide valuable information to make decisions and solve business-related issues. However, a large part of this data is hardly analysed because of their different structures and schemas. The aim of the paper is to improve the integration, processing and analysis of unstructured spatial data. During the research, the author analysed geospatial data types and sources, explored NoSQL solutions for geospatial data processing and chose the open-source tools which are the most appropriate for the stated goals, as well as analysed the coverage of forest areas with protected zones using MongoDB database capabilities and visualized results in a map, using QGIS software. MongoDB is a useful tool for geospatial data analysis and has a large number of embedded topology analysis functions and has drivers for widespread programming languages like JavaScript, Python, PHP, Java, Scala, CNo., C, C + +, etc. QGIS has extensions that allow to make connections to databases, including a connection with MongoDB. Using these features, the developers can develop geographic information systems to analyse geospatial data – structured, semi-structured and unstructured. Generally MongoDB is used for real-time data analysis; however, complicated analysis of large data sets can take up to hours and even days, so it is still necessary to find the best solution to get results in an acceptable time for users. Using MongoDB together with Apache Hadoop – the framework to support big data applications – could be a possible solution for this problem.

This article presents theoretical and practical aspects of content marketing decisions for the customer value creation in social networks by using the case of the organic farm ʻIlzenberg manor’. Focus of this paper is to determine which content marketing decisions create the biggest value for the customer in social networks. The first part of the paper deals with theoretical insights into the content marketing decisions and their ability to create the customer value in social networks. Findings of theoretical analysis disclose that there are interfaces between content marketing, separate content marketing decisions and the customer value in the context of social networks. Respectively, it leads to an assumption that the usage of content marketing decisions can be valuable for the customer value creation in social networks. The second part of the paper focuses on the case analysis of the organic farm ‘Ilzenberg manor’. In order to determine which content marketing decisions create value for the customer in social networks, authors examine a correlation between separate content marketing decisions and consumer value indicators by using data from ʻIlzenberg manor’ Facebook page. The obtained results expose that not all content marketing decisions create value for the customer in social networks. Hence, it means that a selection of separate content marketing decisions in social networks can be made through the customer value perspective. The article ends with insights, conclusions, limitations and future research possibilities.

One of the factors affecting winter wheat grain yields are leaf blotches. The two-factorial trial was conducted in the Research and Study farm ‘Pēterlauki’ in 2017/2018 and 2018/2019 (Latvia). Four nitrogen rates and five fungicide treatment schemes were used. The aim was to clarify the impact of leaf blotches on the winter wheat yield. In winter wheat plots, the tan spot (caused by Pyrenophora tritici-repentis) dominated but also Septoria leaf blotch (caused by Zymoseptoria tritici) was found. The severity of leaf blotches in winter wheat was low in both years due to dry and warm weather. The development of leaf blotches was influenced by fungicide application schemes, but not by nitrogen fertilizer rate. The total disease impact during the vegetation period was estimated by calculation the area under the disease progress curve (AUDPC). AUDPC for both diseases were significantly higher in the variant without fungicides (F0) and in the variant, where half of dose of fungicides at the growth stage (GS) 55–59 (F1) was used. The using of full dose of fungicide at the GS 55–59 (F2) as well as using of fungicides two (F3) or three (F4) times in growing season significantly decreased the values of AUDPC for both diseases, but differences among AUDPC values in mentioned three variants were not significant. Results showed that the nitrogen fertilization significantly increased the average per both years grain yield until the nitrogen rate N180. Fungicide treatment schemes had no significant effect on the average grain yield.

Puccinia striiformis is a biotrophic pathogen able to cause broad scale epidemics in wheat growing regions. P. striiformis is genetically highly variable pathogen. New, aggressive genetic lineages, adapted to warm temperatures have been observed in the last decades worldwide. The study aimed to ascertain the structure of genetic lineages of P. striiformis in Latvia. Forty one wheat leaf samples with yellow rust symptoms were collected in 2017–2019. Fenotyping and genotyping methods were used for identification of genetic lineages in Global Rust Reference Center, Denmark. Assessments of leaf diseases on winter wheat differentials – ‘Ambition’, ‘Mariboss’, ‘Moro’, ‘Compair’, ‘Rendezvous’, ‘Spalding Prolific’ and local variety ’Fredis’ were made during the research. Five genetic lineages of P. striiformis – PstS4, PstS7, PstS10, PstS13 and PstS14 were found. 56% from the samples belonged to PstS14, 17.1% PstS10, 12.2% PstS4 and PstS7, 2.4% PstS13. Genetic lineages identified from Latvian wheat samples are found in the biggest cereal growing regions in Europe and are able to cause epidemics on wheat. Genetic lineages of P. striiformis from Latvian samples have not been identified before. All differential varieties were infected with P. striiformis in 2017, ‘Ambition’ and ‘Moro’ in 2018, no infection was observed on differentials in 2019 despite the presence of P. striiformis on winter wheat variety ‘Fredis’. The identification of genetic lineages of P. striiformis on wheat in Latvia is necessary to continue.

In Lithuania, forests are managed by Lithuanian State Forest Enterprise, municipalities, ministries, etc. and private forest owners. About 50% of all forest land is State importance, privately owned forests cover 40% of forest land, and about 10% of forest land belongs to forests reserved for restitution. Forest management of private ownership force many challenges, because private forest owners are people, who have purchased or received the property after restitution, and often lacks knowledge about forest resources, its dynamics and sustainable forest management. As remote sensing is a valuable source for forest monitoring, because it provides periodic data on forest resource and condition status, these methods are gaining increased attention worldwide. In this context, more scientific efforts are made at developing remote sensing derived geo-spatial data services for sustainable forest management through a web service platform, which would integrate geo-information into daily decision making processes and operation for private forest owners. This article presents a review of privately owned forests’ statistics, questionnaire-based survey about GIS usage and demand for forest owners in Lithuania and links available sources of open geo-spatial data useful for sustainable forest management.

The aim of the study is to evaluate carbon stock in litter and organic forest soils in Latvia as well as to characterize accumulation of carbon in litter in afforested lands. The study is providing empirically valid information about soil and litter carbon changes for the National greenhouse gas (GHG) inventory by using data from National forest inventory (NFI), forest soil monitoring demonstration project BioSoil and other studies. The study proves significance of organic forest soil carbon pool in Latvia and demonstrates necessity to extend NFI incorporated forest soil monitoring program to improve data on soil density in wet organic soils, as well as to integrate data characterizing water regime in forests. The acquired data also proves that the conservative approach of calculation of carbon stock changes in litter in afforested lands applied in the Latvia’s National GHG inventory avoids overestimation of CO2 removals. The data on litter carbon stock collected in this study is sufficient to estimate total carbon stock for stands dominated by most common tree species and long term impact of changes of species composition. Measurements of organic soil and litter thickness should be continued by NFI and integrated with more detailed soil monitoring to increase accuracy of carbon stock estimates and gather data necessary for verification of modelling data, particularly in afforested lands and due to change of dominant species.