2024, Vol. 22, No. 1

Selle kollektsiooni püsiv URIhttp://hdl.handle.net/10492/9342

Sirvi

Nüüd näidatakse 1 - 20 23

Properties of chemically stabilized methanol-HVO blends : [Retracted]
(Estonian University of Life Sciences, 2024) Wang-Alho, H.; Sirviö, K.; Balogun, F.; Kaivosoja, J.; Nuortila, C.; Mikulski, M.; Niemi, S.
Effectiveness of reducing ammonia emissions from solid manure by using bio-covers
(Estonian University of Life Sciences, 2024) Knoknerienė, I.; Strelkauskaitė-Buivydienė, I.; Bleizgys, R.
According to the European Environment Agency, in 2021, 93 percent of ammonia was released into the environment due to agricultural activities. Almost half of the pollutants were released from cowsheds. The next significant source of pollution is liquid and/or solid manure storage facilities. Many dairy farms use liquid manure systems, but inevitably there is some solid manure produced in every cattle farm. Ammonia emissions increase when air penetrates the top layer of the manure pile. This is the reason why it is recommended to reduce the surface area of the manure piles that contact with open air. Straw, peat, sawdust, or other materials can be used as bio-covers. The purpose of this study is to determine the efficiency of bio-covers while covering solid manure. Experimental studies were carried out in field conditions, covering solid cattle manure with a > 10 cm thick layer of chopped straw. As the results show, chopped straw reduced ammonia emissions by up to 44.49 percent, but the emission declination rate is 1.85 times higher during the period when NH3 volatilization is the most intensive.
Theoretical study of the movement of the wide span machine in quasi-static turning mode
(Estonian University of Life Sciences, 2024) Olt, Jüri; Bulgakov, V.; Adamchuk, V.; Kuvachov, V.; Liivapuu, Olga; Estonian University of Life Sciences. Institute of Forestry and Engineering
Wide span machines represent sophisticated energy and technological tools for controlled traffic farming. The curvilinear movement (turning) of these machines are often decisive in the design of new or evaluation of existing models of equipment. The application of classical theory of turning in researching wide span machines faces certain challenges due to limitations imposed when describing the force or kinematic interaction of their movers with the supporting surface along a constant technological track. Additionally, non-traditional control schemes further complicate the use of the classical turning theory. The present research aims to study the curvilinear motion of wide span vehicles in a quasi-static turning mode, allowing for the modelling of their turns with combined or non-traditional movers under various control schemes. As a result of the conducted research, it was established that a promising non-traditional turning scheme for a wide span machine is one where one rear wheel is driving, and the other is braking, with controllable front wheels. In this case, the turning radius of the machine is 1.5 times smaller compared to traditional turning schemes. It was experimentally proven that the practical implementation of this new non-traditional turning scheme for the wide span machine is limited by the magnitude of the load on its front wheels relative to the rear ones.
Processing of Latvian peat and waste coffee as a biocomposite material for the oil spill collection
(Estonian University of Life Sciences, 2024) Irtiseva, K.; Zhylina, M.; Baumanis, R.; Kuzmina, J.; Ozolins, J.; Lapkovskis, V.
There is a growing interest in adsorbents of natural origin that are renewable, effective, and able to treat water contaminated by oil products. The current paper investigates a novel biobased ‘peat - spent coffee grounds’ SCG-HP bio-based composite pellets as a perspective adsorbent for spilt oil products. The preparation and characterisation of SCG-HP bio-based composite material in pellet form is described. This research used homogenised peat (HP) as an efficient, natural binder. The SCG in different proportions (from 12 wt% to 50 wt%) with HP were used for the different types of SCG-HP granulated sorbents. The granule size obtained ranged from 2 to 6 mm with a total porosity of 56–61%. The sorption of the test oil (fresh engine oil Pilot 10W-40 SJ/CF) was investigated. Sorption studies showed maximum adsorption (capacity) from 90 to 125 wt% for SCG-HP granules.
Influence of the farm location and seasonal fluctuations on the composition and properties of the milk
(Estonian University of Life Sciences, 2024) Ramadani, Xh.; Kryeziu, A.; Kamberi, M.; Zogaj, M.
The aim of this research was to investigate the variations in the chemical composition as well as the physical and microbiological properties of raw milk depending on the farm location and the season. Seven dairy farms located in seven different geographic regions of Kosovo were included in the experiment. Milk composition (total solids – TS, milk fat – MF, solids nonfat – SNF, protein – P, lactose – L, active acidity – AA (pH), density – D, colony formatting unit – CFU, and somatic cells count – SCC) were analysed during a one-year period from December 2021 to November 2022. In a total of 252 analysed milk samples, the research showed an average good composition in accordance with the Kosovo regulation for milk quality: TS (13.71%), MF (5.12%), SNF (8.60%), P (3.25%), L (3.87%), AA (6.83), D (1.028 g cm-3), but higher number of CFU (194,048 mL-1), and SCC (418,429 mL-1). Farm location showed significant differences (P < 0.01) in TS, MF, SNF, P, D, CFU and SCC, whereas L content and AA value were statistically non-significant. The lower value of TS, MF, and CFU were detected in summer, AA, and P in spring, SNF and L in autumn, D value was similar in all seasons, whereas only SCC was present in winter season. The differences in all analysed parameters with respect to the season were statistically non-significant.
Fusarium head blight in winter wheat: development peculiarities and protective strategies
(Estonian University of Life Sciences, 2024) Avagyan, G.V.; Martirosyan, H.S.
Fusarium head blight (FHB, caused by the fungal plant pathogen Fusarium graminearum Schwabe) is a widespread fungal disease in the Republic of Armenia, affecting various cereal crops, including wheat, leading to a decrease in productivity and grain quality. However, comprehensive research aimed at selecting proper fungicides and determining the optimal application timing has not been conducted before. FHB can undergo epidemic development during years characterized by favorable weather conditions. Conversely, during periods of adverse weather conditions, the severity and incidence of FHB tend to decrease notably. Abundant rainfall and mild temperatures render plants more susceptible, facilitating the spread of infection not only during the flowering of winter wheat but also at the waxy ripening stage, thereby increasing the risk of an FHB epidemic. The experiments were carried out during the 2022 and 2023 growing seasons under rain-fed conditions, with the primary focus on treating winter wheat with triazole group fungicides. During years with adverse weather conditions for FHB development, a single application of Falcon (0.5 L ha-1 ) or Prosaro (1.0 L ha-1 ) at Feekes 10.5.1 proved to be an effective strategy for managing FHB, particularly when integrated with cultural practices. These treatments provided a biological efficacy of 80.6% to 83.3% at Feeks 11.2, and from 76.6% to 79.4% at harvest, respectively, increasing wheat yield by 37.62% to 42.9%. In the case of epidemic development of FHB during years with more favorable weather conditions, a double fungicide treatment (Falcon or at Feekes 10.3 and Prosaro at Feekes 10.5.1) was the most effective option, showing high biological efficacy (97.4% at Feeks 11.2 and 90.3% at harvest) against FHB of winter wheat, increasing wheat yield by 40.1%.
Spatial variability of methane and carbon dioxide gases in a Compost-Bedded Pack Barn system
(Estonian University of Life Sciences, 2024) Ferreira, J.C.; Ferraz, P.F.P.; Ferraz, G.A.S.; Oliveira, F.M.; Cadavid, V.G.; Rossi, G.; Becciolini, V.
The dairy sector significantly contributes to global food production, however, it is closely associated with environmental concerns, specifically the emission of greenhouse gases such as methane (CH4) and carbon dioxide (CO2). The research problem focuses on the environmental impact of livestock farming, particularly in relation to the emission of greenhouse gases (GHG) such as methane (CH4) and carbon dioxide (CO2). Therefore, the objective of this paper was to assess the spatial variability of CH4 and CO2, as well as the thermal environment through the Temperature and Humidity Index (THI) and of air velocity (V, m s-1) in a Compost Bedded Pack (CBP). The experiment was carried out in October 2023, in a commercial dairy cattle facility measuring 54×22×4.5 m (length×width×height) that housed 80 lactating cows. Measurements were collected at 75 points, 0.25 m above the bedding, for one minute in each point. To characterize the distribution of gases and the thermal environment, the data were underwent geostatistical techniques and kriging maps. THI values ranged from 72.4 to 78.4, categorizing the animals into two environments within the facility, comfort and alert to thermal conditions. The maximum recorded for CO2 was 713.60 ppm in the region with a low ventilation incidence. CH4 reached a ranging from 103.38 to 196.73 ppm in areas with low ventilation and higher temperatures. The use of geostatistics enabled the characterization of spatial variability of greenhouse gases CH4 and CO2, as well as THI and V. Analyzing these variables is crucial for implementing mitigation actions and developing an increasingly sustainable production system.
System dynamics modeling for precision beekeeping: Queen rearing optimization for advanced apiary management
(Estonian University of Life Sciences, 2024) Smilga-Spalvina, A.; Spalvins, K.; Veidenbergs, I.
The authors propose system dynamics modelling as a new direction in Precision Beekeeping. By modeling the production process in beekeeping, it is possible to forecast the potential production capacity before the season, using the resources available to the beekeeper. The model included in this article reflects one specialisation of beekeeping - queen bee rearing, from the process of queen bee breeding up to the sale of queen bees throughout the entire season. The model helps beekeepers make decisions about the workforce needed to maintain the desired production volume, expected income and costs and resource allocation.
Semi-natural grassland abandonment in relation to agricultural land management under Common Agricultural Policy in boreonemoral Europe
(Estonian University of Life Sciences, 2024) Rūsiņa, S.; Lakovskis, P.; Ieviņa, L.
The Common Agricultural Policy (CAP) has had a major impact on agricultural land use changes in Europe. While grassland abandonment in mountain areas is well-documented, there is a gap in research regarding lowland regions. We investigated how changes in CAP regulations between two periods (2007–2013 and 2014–2020) influenced the pattern of semi-natural grassland (SNG) abandonment in boreonemoral Europe. We used 25 km2 grid cells as the basic research unit. The relationship between agricultural land management variables and SNG abandonment was analyzed by regression methodology and non-linear relationships were detected. We observed a decrease in the overall rate of SNG abandonment during the second CAP period (2014–2020), suggesting that recent CAP modifications have had some positive impact on grassland conservation. However, the impact of CAP on SNG abandonment varied between the two regions differing in land capability for agriculture and between productive and unproductive SNG types. The study highlights the importance of understanding the complex processes that influence abandonment in strongly non-linear ways. It underscores the importance of tailored conservation strategies and the role of the CAP in shaping SNG management practices.
Balance and coefficients of usage of nitrogen, phosphorus and potassium from the soil and fertilizers by tomatoes and peppers in the conditions of Ararat Plain of Armenia
(Estonian University of Life Sciences, 2024) Matevosyan, L.G.; Harutyunyan, S.S.; Galstyan, M.H.; Osipova, R.H.; Mkrtchyan, A.T.; Sargsyan, K.Sh.; Sadoyan, R.R.
The aim of the research is to reveal the biological removal, balance and coefficient rates of nitrogen, phosphorus and potassium use from soil, organo-mineral fertilizers and microbiological concentrates by tomato and sweet pepper in the conditions of Ararat Plain of Armenia. Field experiments were carried out in 2017–2019, on typical irrigated meadow brown soils in triplicate. It has been established that at tomato yields of 50–75 t ha-1, the biological removal of nitrogen ranges from 110 (without fertilizers) to 178 kg ha-1 (N150P80), P2O5: 61–89, K2O5: 166–289 kg ha-1, and at pepper yields of 23–32 t ha-1, respectively - 55–76, 38–49 and 77–106 kg ha-1. Tomato utilization rates from the soil (unfertilized version) are: N: 118, P2O5: 37, K2O: 8%, and the negative balances are respectively: 107, 67 and 109 kg ha-1, similar data for pepper were recorded at: N: 59, P2O5: 23, K2O: 4% and 52, 44, 20 kg ha-1. From fertilizers, tomato absorbs 27–45% nitrogen, 11–48% P2O5 and 48–72% K2O with negative balances (N: 15–55, P2O5: 14–76, K2O: 34–79 kg ha-1), in poultry litter the balance P2O5 = + 94.2 kg ha-1. For pepper, however, these data were respectively amounted to: N: 6–14, P2O5: 10–15, K2O: 9–20%, and the balances were positive. Microbiological concentrates (Azoto + phosphate Barvar) showed poor effectiveness as compared to organo-mineral fertilizers. It was also found that the lower the amount of a mobile element in the soil, or in the fertilizer dose, the higher its utilization rate and vice versa.
Adaptability of apricot varieties in the Right-Bank Subzone of the Western Forest-Steppe of Ukraine
(Estonian University of Life Sciences, 2024) Ignatenko, O.; Moiseichenko, N.; Makarova, D.; Trokhymchuk, H.; Vasylenko, V.; Havryliuk, O.; Kishchak, O.; Honcharuk, Y.; Hrusha, V.
The research reveals the main reasons that prevent the extension of commercial apricot plantations in Ukraine and worldwide. This brief description includes eight cultivars from Ukrainian and foreign breeding programmes. The trials conducted in the Right-Bank subzone of the Western Forest Steppe of Ukraine. The plants from Ukrainian breeding programme ‘Melitopolskyi Ranniі’, ‘Botsadivskyi’, ‘Siaivo’, ‘Kumir’, ‘Osoblyvyi Denysiuka’, as well as the foreign one – ‘Robada’, ‘Harogem’, ‘HJA-19’, were distinguished by high adaptability to the complex of adverse overwintering factors in the above-mentioned region. These samples did not lose the acquired level of frost resistance under the influence of provoking thaws. A comprehensive assessment of drought resistance, based on water-holding capacity, turgor recovery degree, water deficiency, and leaves' hydration of the presented varieties, established that all variants of the experiment were not inferior to the best popular cultivars. According to the the biological feature of buds' formation at an early age, the cultivars ‘Robada’ and ‘HJA-19’ were characterized as early-fruiting. The yield and quality indicators for the 2021–2022 years of research were evaluated. Average fruit weight was noted in all samples, with the cultivar ‘Siaivo’ exceeding the average. To improve the assortment and enrich the apricot gene pool collections with the best samples suitable for cultivation in the Forest-Steppe Zone of Ukraine, according to the results of the study, the following researched cultivars were included in the collection of valuable samples of the common apricot gene pool of the Institute of Horticulture of the National Academy of Sciences of Ukraine: ‘Melitopolskyi Ranniі,’ ‘Botsadivskyi,’ ‘Siaivo,’ and ‘Osoblyvyi Denysiuka’. These cultivars are sources of productivity and adaptability to abiotic factors of cultivation (winter and frost resistance, drought resistance). They are certified by the National Center of Plant Genetic Resources of Ukraine.
Breeding and genetic screening of F1 hybrids of soft winter wheat (Triticum aestivum L.) by manifestation of resistance to Fusarium graminearum Schwabe
(Estonian University of Life Sciences, 2024) Demydov, O.A.; Kyrylenko, V.V.; Murashko, L.A.; Humenyuk, O.V.; Suddenko, Yu.M.; Mukha, T.I.; Volohdina, H.B.; Zamlila, N.P.; Novytska, N.V.; Mazurenko, B.O.
Diseases of field crops significantly reduce yield and the quality of agricultural products. Developing resistant varieties is one of the tasks for enhancing agroecosystem resilience. The creation of infectious material for the background pathogen and heterosis analysis of F1 hybrids of soft winter wheat for resistance against Fusarium graminearum Schwabe (F. graminearum) and elements of spike productivity was the goal of the conducted research. The analysis of F1 genotypes of wheat for resistance against F. graminearum was carried out in field infections and natural nurseries of the wheat breeding laboratory of The V.M. Remeslo Myronivka Institute of Wheat of the NAAS of Ukraine (located in the northern part of the Right-Bank Forest-Steppe of Ukraine) during 2021 and 2022. The most aggressive isolates of the F. graminearum fungus were identified for developing inoculum and creating an artificial infection background in field conditions. In terms of the inheritance of resistance and spike productivity traits, 29.4% of hybrid populations of the first generation were selected. Positive dominance for the complex of investigated traits was found in hybrid combinations where sources of resistance against Fusarium graminearum (MV 20-88 × Smuhlianka, (Mikon × ALMA) × Lehenda Myronivska and local winter wheat varieties MIP Knyazhna, MIP Vyshyvanka were involved in the crossbreeding. It was established that cytoplasmic genes enhance the dominance of genes for complex resistance in one crossbreeding group. The best combinations with positive dominance in resistance to fusarium can be utilized in the development of highly resistant varieties.
Importance of mosaic augmentation for agricultural image dataset
(Estonian University of Life Sciences, 2024) Kodors, S.; Sondors, M.; Apeinans, I.; Zarembo, I.; Lacis, G.; Rubauskis, E.; Karklina, K.
The yield estimation using artificial intelligence is based on object detection algorithms. Firstly, the object detection algorithms identify the number of fruits on images, then tree fruit load is predicted using regression algorithms. YOLO is a popular convolution neural network architecture for object detection tasks. It is sufficiently well studied for fruit yield estimation. However, the experiments are traditionally restricted to only one specific fruit category and growing season. This is a big shortcoming for the smart solutions like agro-drones, which must automatically complete yield monitoring of the most popular fruit species in commercial orchards. Therefore, the modern studies related to yield estimation increasingly raise attention to multi-stage, multi-state and multi-specie detection tasks. The multi-stage datasets can be described as a collection of multiple sub-datasets, e.g. flowers, fruitlets and fruits. The multi-state dataset can contain classes like mature, immature or damaged fruits. Meanwhile, the multi-specie dataset contains images with representatives of multiple cultures. However, if classic object-detection tasks like urban or indoor object detection have multiple classes presented in one image, then yield estimation datasets usually have images with only one class presented on them. Therefore, an image shuffle or mosaic augmentation are the intuitive training strategies of YOLO for object detection working with a collection of multiple single class datasets. We applied the YOLOv5m model to test both strategies, which were verified on three datasets: apple fruits (MinneApple), pear fruits (Pear640) and pear fruitlets (PFruitlet640). Our experiment showed that mosaic augmentation improves mAP@0.5:0.95 better than simple image shuffle. The mean difference between both strategies is equal to 0.0438.
Control of subacute ruminal acidosis in high-yielding dairy cow herd by measuring the rumen wall thickness
(Estonian University of Life Sciences, 2024) Sematovica, I.; Malniece, A.; Duritis, I.
The study aimed to investigate whether the rumen wall thickness (RWT) follows with the data from the collar sensor system and how deeply it depends on feeding management used in the high-yielding dairy cow farm, as well as what benefit it could bring to diagnose subacute rumen acidosis (SARA) in cows. The data obtained from the collar sensors about chewing activity were analysed in relation to milk recording results, the rumen wall thickness (RWT) and the context of the composition of feed easily digestible carbohydrate changes during the intensive lactation phase. The dynamic of RWT was evaluated concerning milk amount and quality, its relation to fertility, and the size of the cows, which were taken into account. The results showed that the sensor system provides information about cow behaviour but does not provide direct information about the SARA problem in the herd. The RWT was related to the changes in feed easily digestible carbohydrate content and chewing activity. In conclusion, the sensor system allows monitoring of feed ingestion, but overall data about productivity and milk composition are necessary to make conclusions and induce ideas about corrections. Additional RWT measures are necessary to monitor rumen health and SARA presence timely, so monitoring the RWT may lead to a longer productive life for the cow.
Testing outcomes of IoT based continuous crop weight and PAR sensors at industrial greenhouse
(Estonian University of Life Sciences, 2024) Avotins, A.; Potapovs, A.; Gruduls, J.; Ceirs, R.
Industrial greenhouses have automated control systems for climate, lighting, irrigation, ventilation, and heating regulation using different types of feedback sensors. Nowadays it is a trend to increase the data precision and measurement data amount, thus various additional IoT sensors are installed, and the regulation becomes more precise, due to available data, which enables new analytical features to create new control rules or strategies. The general aim is to raise the level of process automation, quality, energy efficiency, and other important parameters. Still, further, we go into data resolution and amount, and the problem of data reliability and interpretation starts to become a challenging problem. In this article, authors focus on earlier developed PAR sensor modules and continuous tomato crop weight sensor modules (TWS) testing and received data analysis from an industrial greenhouse. Both sensors were tested in detail at the tomato greenhouse of ‘Latgales Darzenu Logistika’ in Mezvidi parish, with a total growing area of 5,062.4 m2 from 1.05.2022 to 30.06.2022., and gathered data is analysed for this period. Received sensor data can be used as the main feedback signal to create a lighting control strategy, same time increasing energy efficiency and reducing also costs. As artificial lighting energy consumption costs make 20–40% of total greenhouse costs, it is worth having a more precise lighting control system algorithm, integrating the crop growth increase and accumulated light energy during the day from the sun, and then adding only the missing amount (also period) of light provided by artificial lighting. Experimental studies of both sensor data, show that plants reaction can be monitored, as by decreasing the lighting period and temperature setpoint by 6% each, the plants daily weight gain decreases by 14%, and it can be measured already in first day after the new settings were set in place.
Integration of low-cost technologies for real-time monitoring of pigs in pre-fattening stage
(Estonian University of Life Sciences, 2024) Montoya, A.P.; Obando, F.A.; Osorio, J.A.; Gonzalez, V.
Measurement of environmental, behavioural, and physiological variables is essential for decision making in intensive animal production systems. Data collection and analysis, in real time, employing low-cost tools are fundamental to increase competitiveness and animal wellness. In this context, the goal of this research was to develop a low-cost measurement system for monitoring bioclimatic and behavioural parameters in the production of pigs in the pre-fattening stage. Internet of things technologies was employed in order to increase control over the production and as a tool for decision-making in real time. Sensor Networks were developed using low-cost sensors open-source platforms and code. The system was validated in a pig farm located in Antioquia-Colombia with two groups of 10 pigs in the pre-fattening stage. Parallel tests with three sequential repetitions were carried out. The system was validated through continuous environmental data collection and periodic physiological measurements. The developed system includes temperature, relative humidity, global radiation, wind speed, pressure, and lighting sensors. A high microclimatic variability was found inside the facilities, presenting thermal discomfort conditions in some hours of the day, which impacted the development and behaviour of the animals. The adaptation of low-cost technologies for real-time monitoring of pigs is viable and facilitate decision-making in real time improving the productive efficiency, supplying important information at a productive and scientific level.
Agro-biological evaluation of different groundnut (Arachis hypogaea L.) varieties on the background of phosphorous-potash fertilizers in conditions of semi-desert soil zone
(Estonian University of Life Sciences, 2024) Matevosyan, L.G.; Barbaryan, A.A.; Ghazaran, R.H.; Ghukasyan, A.G.; Galstyan, M.H.; Harutyunyan, S.S.
In conditions of semi-desert soil zones of Armenia (1,130 m high above the sea level) the agro-biological properties of groundnut varieties Lia, Virginia, Mocket, TMV 3, Sevahatik (Black Seed) and Chinese have been studied with the aim of selecting their best options for further regionalization in the piedmont zones. The field experiments were conducted in 2020–2022. The calculations and laboratory analyses have indicated that the field germination capacity of the mentioned varieties is rather high fluctuating within the range of 77.5–81.0%, whereas the weight of 1,000 grains equaled to 515–545 g, the average yield - 2.77–3.33 t ha-1, the total nitrogen in the grains were 4.39–4.61%, crude proteinհում (per 5.70 factor of nitrogen) - 25.02–26.28%, total sugar contents - 14.11–16.63%, and fat content - 44.8–48.0%. The Mocket and Chinese varieties were distinguished by their yield capacity and qualitative indices of the yield and thus, the latter have been recommended for the cultivation in the farm households of the mentioned zone.
In vivo evaluation of antioxydant potential and antihyperglycemic effect of Stevia rebaudiana Bertoni
(Estonian University of Life Sciences, 2024) Aissaoui, O.; Terki, L.; Ait Ameur, S.; Bitam, A.
Stevia rebaudiana Bertoni (SR) has a high concentration of phytochemicals that promote health and well-being in conditions such as diabetes. This study aims to assess the antihyperglycemic, antioxidant, and antihyperlipidemic effects of SR on diabetes in male rats caused by Alloxan. Forty adult male rats were divided into five groups. For 28 days, SR was administered by gavage. Spinreact and ELISA kits were used to detect serum levels of blood glucose, insulin, liver function, lipid profiles, antioxidant enzymes, and lipid peroxidation. Histopathology was also investigated. Stevia’s free radical scavenging capabilities have an IC50 value of between 34.49 and 39.66 mg L-1. Stevia therapy reduced biochemical markers in diabetic rats (DR). After 28 days, SR raised fasting blood glucose, insulin, and lipid peroxidation serum levels by 52%, 40%, and 27%, respectively. Also, in DR treated with SR, there was a substantial increase in high-density lipoprotein cholesterol (35.8%), superoxide dismutase (30%), total antioxidant status (20%), glutathione peroxidase and reductase. SR improves DR’s pancreas and liver function by enhancing the endogenous antioxidant system. These findings revealed that SR counteracted Alloxan’s necrotic effects by reducing insulin resistance in DR, hence revitalizing pancreatic β–cells.
Tomato nutrition with the application of Trichoderma spp. on different soils
(Estonian University of Life Sciences, 2024) Conte, E.D.; Fiorini, D.; Vargas, N.M.B.; Bertoni, L.F.B.; Santos, L.N.T.; Magro, T.D.; Silvestre, W.P.; Cocco, C.; Schwambach, J.
The present work aimed to evaluate the effect of Trichoderma spp. on the nutrition and development of tomato plants in three soil types under protected environments. One experiment was conducted with ferralsol and acrisol soil (conducted in pots in a greenhouse), and another used cambisol soil (conducted in beds in a commercial greenhouse). The experiments were carried out in a randomized block design with twelve replications. The treatments consisted of a control (no application of Trichoderma spp.), an application of Trichoderma spp. before seedling transplantation, and monthly Trichoderma spp. applications in tomato plants cv. Itaipava®. The evaluations included plant nutrition at full flowering, development (height and fresh and dry mass of shoots), crop yield components of number, weight, and diameter of fruits, and average yield per plant. A second nutritional evaluation was repeated in the cambisol. The application of Trichoderma spp. in the soil did not modify the nutrition parameters of plants until flowering. However, at the end of the cycle in cambisol, the treatment increased the available contents of N, P, Cu, and Mn. The application of Trichoderma spp. did not affect the development and yield of tomato plants in the conditions tested.
Mathematical model for detecting tomato ripeness using chlorophyll fluorescence
(Estonian University of Life Sciences, 2024) Abdelhamid, M.A.; Rawdhan, S.A.; Shalaby, S.S.; Atia, M.F.
A precise assessment of tomato ripeness is crucial in the harvesting and marketing procedures. Chlorophyll fluorescence is being relied on as a harmless approach for tracking the maturity of tomatoes in postharvest research. In this study, mathematical model is proposed based on measuring the intensity of fast chlorophyll fluorescence of tomatoes depending on their degree of maturity. In the experimental study, four stages of tomato ripening (green, turning, pink, and red) for three varieties (‘Alkazar’, 'Lezginka’, and ‘Rosanchik’) were used. The Fluorescence Intensity (FI) data over time were represented using a third-degree polynomial function and finding its first derivative curve. The FI parameter was obtained as the fluorescence level at the first inflection point on the fluorescence induction curve (at time tI on the first derivative curve). According to the obtained mathematical models, the optimal time for monitoring the degree of ripeness of tomatoes was tI = 129 ± 4 ms. According to the results of experimental studies, there is a general trend, regardless of the variety used, that the FI decreases with tomato maturity. The FI may assist in sorting and grading processes for fresh vegetables and fruits. It can also be used as a system that can be integrated into harvest and post-harvest machinery for agricultural products.

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