Content Index Research Articles

Effects of Strong Geomagnetic Storms on the Ionosphere and Degradation of Precise Point Positioning Accuracy during the 25th Solar Cycle Rising Phase: A Case Study

Approaching the peak year of the 25th solar activity cycle, the frequency of strong geomagnetic storms is gradually increasing, which seriously affects the navigation and positioning performance of GNSS. Based on the globally distributed GNSS station data and FORMOSAT-7/COSMIC-2 occultation data, this paper explores for the first time the effects of the G4-class geomagnetic storm that occurred on 23–24 April 2023 on the global ionosphere, especially the ionospheric equatorial anomalies and F-layer perturbations. It reveals the precise point positioning (PPP) accuracy degradation during a geomagnetic storm. The results show that the ionospheric rate of total electron content index (ROTI) and near high latitude GNSS phase scintillations index have varying levels of perturbation during geomagnetic storms, with the maximum ROTI and phase scintillations index exceeding 0.5 TECU/min and 0.8, respectively. The equatorial ionization anomaly (EIA) shows an enhanced state (positive ionospheric storms) during geomagnetic storms, and the cause of this phenomenon is most likely the equatorward neutral wind. The variation of the S4 index of the FORMOSAT-7/COSMIC-2 satellite reveals the uplift of the F-layer during geomagnetic storms. During geomagnetic storms, the PPP accuracy degrades most seriously at high latitudes, the maximum MAE exceeds 2.3 m, and the RMS in the three-dimensional (3D) direction exceeds 2.0 m. These investigations can provide case support for space weather and GNSS studies of the impact of geomagnetic storms during peak solar activity years.

Combined use of seaweed extract and arbuscular mycorrhizal fungi for alleviating salt stress in bell pepper (Capsicum annuum L.)

Salinity is the most catastrophic abiotic stress that aggravating its detrimental effects on productivity of horticultural crop especially bell pepper that might be alleviated through judicious application of seaweed extract (SWE) and arbuscular mycorrhizal fungi (AMF). Therefore, the present study was focused on the interactive effects of SWE and AMF to improve growth, physiological responses and yield performance of bell pepper grown under salt stress. Factorial experiment consisted of three factors namely SWE dose (non-treated control, 2.5 g L–1, 5.0 g L–1 and 7.5 g L–1 designated as SWE0, SWE2.5, SWE5.0 and SWE7.5, respectively); water salinity levels (control- 0.54, 4, 8 and 12 dS m–1) and two levels of AMF inoculation (with AMF [+AMF] and without AMF [–AMF]). Factorial experiment was laid out where treatment combinations were assigned completely randomized design (CRD) with three replications. SWE treated plants upgraded leaf relative water content, leaf greenness and membrane stability index 16 %, 19 % and 13 %, respectively with lower electrolyte leakage (15 %) at 12 dS m–1 water salinity compared to non-treated plants. In addition, higher proline content (79 %) was observed at SWE5.0 in AMF inoculated plants over control (non-inoculated plants. Marketable fruit yields were higher (31 %) with the combined application of SWE and AMF at extreme salt stress conditions (12 dS m–1). Apart from that, SWE7.5 treated plants exhibited more accumulation of potassium (26 %) and phosphorous (32 %) while less accumulation of sodium (16 %) was displayed at higher salinity level (12 dS m–1) compared to control plants. Moreover, SWE and AMF treated plants showed better postharvest quality (pH, Brix) performance during storage condition compared with control. Taken together, it might be inferred that integrated application of SWE and AMF had boosted up morpho-physiological traits, yield and ion homeostasis to ameliorate the baleful effects of salt stress on bell pepper.

The influence of sodium selenite and the phytopreparation Emelin on indicators of natural resistance, safety and laying hen product quality

Food products produced in Ukraine must meet safety and quality indicators in accordance with regulatory and legal acts and provide ordinary consumers with nutrients. Phytoadditives are widely used in most countries of the world, including Ukraine, of great importance in the technological process of growing agricultural animals, especially poultry. The aim of the work was to study the influence of sodium selenite and the herbal preparation "Emelin" on indicators of natural resistance, safety and quality of products of laying hens. To obtain scientific information, the following methods of observation were used: biological, hematological studies, statistical. 260 laying hens of the "Adler silver" breed at the age of 6–11 months were used for experimental research (tests). Optimum sanitary and hygienic conditions for feeding and keeping the birds were created. It was established that the phytosupplement "Emelin" in combination with sodium selenite stimulates hematopoietic processes, which is confirmed by an increase in the hemoglobin content by 12.1-19.5% (p<0.01) and erythrocytes by 11.5-19.9% (p<0 .01) in the peripheral blood of laying hens compared to the control group. The leukocyte content index and erythrocyte sedimentation rate during the research were within the physiological norm in all experimental groups. In the laying hens of the second experimental group, which were fed sodium selenite and the phytopreparation "Emelin", an increase in the weight of eggs compared to the control group was observed by 2.15- 2.51% (р<0.05. It should be noted that with an increase in the weight of the eggs increases and the weight of its constituent parts increases. The use of feed enriched with sodium selenite in the amount of 0.25 mg/kg of dry matter of compound feed and phytopreparation "Emelin" made it possible to increase by 13.5% the number of carcasses of the 1st commodity category in the first and second experimental groups compared with the control (p<0.05), and with the combined use of sodium selenite and the phytonutrient "Emelin" in the third experimental group - by 19.6% (p<0.05), respectively. In addition, the use of feeds enriched with sodium selenite and the phytopreparation "Emelin" allowed not only to minimize the number of non-standard carcasses, but also the possibility of their appearance, which is confirmed by the results of the absence of non-standard carcasses in the third experimental group. The overall economic efficiency of the comprehensive use of the combination of sodium selenite and the herbal preparation "Emelin" was mainly determined by the increase in productivity (egg production) of laying hens, as well as the cost of the herbal preparation, which was (0.97 UAH/kg) and sodium selenite (3.5 UAH/kg) . Thus, feeding the sodium selenite complex in the form of an organic form, at a dose of 25 μg/kg, and the herbal phytopreparation "Emelin", at a dose of 7.0 ml per experimental group, had a positive effect on the productivity, preservation and quality of the carcasses of laying hens. Key words: laying hens, keeping conditions, conservation, productivity, egg production, morphological indicators of blood, phytopreparation, ecologically harmless, food safety, consumer.

Does the Harvest Type Affect Olive Health? Influence of the Harvesting System and Storage Time on the Chemical, Volatile and Sensory Qualities of Extra Virgin Olive Oils.

With the aim of investigating the effect of bruising and its development during the postharvest time, olive fruits (Frantoio and Moraiolo), manually and mechanically harvested, were stored in climatic chambers at two different temperatures (5 °C and 18 °C) for five days. Visual observations highlighted changes in the olive peel with discoloration in the damaged areas and tissue bruising. Olive fruit polyphenols, volatile organic compounds (VOCs) and other oil quality parameters (phenolic content, free acidity and peroxide index) and sensory assessment were evaluated. Analyses were carried out on fruits and experimental extra virgin oils at harvesting and after 5 days of fruit storage. The results highlight that low-temperature storage (5 °C for 5 days) may contribute to the maintenance of high olive oil quality, and the quality of olives stored at room temperature drastically decreases after 5 days of storage. Moreover, mechanical harvesting, compared to manual harvesting, does not seem to affect the final oil quality, at least at harvesting, but seems to determine differences in the long-term storage period. Finally, the samples stored at 18 °C showed a quality deterioration with the development of sensorial defects.

Impact of multi‐pin atmospheric cold plasma on dynamic rheological characteristics of kodo millet starch

AbstractKodo millet's popularity grows due to its diverse applications and health benefits, primarily as a starch source for industries like food processing, requiring modifications to overcome raw starch limitations. In this study, raw kodo starch underwent treatment with cold plasma, varying in voltage (10, 20, and 30 kV) and duration (10, 20, and 30 min). The treated samples were designated as S1 to S9. The results showed that the modified starch exhibited significantly higher G' and G" values compared to the control sample. Three different models were attempted to describe the flow behavior, with the most suitable model selected. This analysis led to an increase in yield stress from 86.55 to 217.98 Pa and an increase in the flow index from 0.31 to 0.56 for the modified starch. This understanding of the rheological characteristics of modified starch can be invaluable for innovating new products, blending novel ingredients, and optimizing manufacturing processes.Practical applicationsKodo millet has gained significant popularity in recent times owing to its high fiber content and low glycemic index. In this research, starch extracted from kodo millet underwent plasma treatment, resulting in a modified starch with enhanced functional properties. The study focused on exploring the rheological properties of this treated starch, and the findings revealed notable improvements in dynamic rheological parameters, including the storage modulus, loss modulus, and viscosity of the starch, all of which increased due to the plasma treatment. The enhanced viscosity makes kodo millet starch particularly suitable for a wide range of food applications. This modified starch finds practical use in the preparation of porridges, soups, and as a reliable filling agent in various food products. This emerging technology has captured the attention of food manufacturers in the grain processing sector, offering a means to elevate the quality and desirability of new food products.

Incremental learning for crop growth parameters estimation and nitrogen diagnosis from hyperspectral data

Nitrogen is an essential nutrient in crop growth cycle and directly affects the photosynthesis of crops. The leaf chlorophyll content (LCC) and leaf area index (LAI) are important for characterizing photosynthetic capacity of crops and are critical indicators for diagnosing nitrogen status of crops. Hyperspectral remote sensing technology provided a means to achieve crop LCC and LAI estimation. However, the redundancy of spectral data and canopy structure effect can cause poor robustness of the estimating models, further hindering the development and application of estimating models across different crop species. In this study, a method based on incremental learning was proposed for the simultaneous estimation of LCC and LAI, and for nitrogen diagnosis across crops. First, for the spectral dataset generated by the PROSAIL model, a deep neural network was used to construct LCC and LAI estimation models (called DNNCA model). Secondly, for the hyperspectral data collected from field crops (soybean, canola and wheat), incremental learning using regularization (LwF algorithm) was used to update the DNNCA model parameters. Finally, the dilution curve model based on the LCC-LAI anisotropic growth relationship was developed to assess crop nitrogen status. The results showed that: (1) The constrained bi-objective optimizated DNNCA model can consider the interactive effect of LAI and LCC on spectral reflectance, and achieved reliable estimation on PROSAIL simulation data set (LAI:R2 = 0.82, RMSE = 0.77 m2/m2; LCC:R2 = 0.91, RMSE = 6.4 ug/cm2). (2) By incremental learning, DNNCA model has continuous learning capability and stable estimation on cross-crop (canola, soybean and wheat) field-measured data (LAI:R2 = 0.64–0.82, RMSE = 0.58–1.02 m2/m2; LCC:R2 = 0.56–0.82, RMSE = 3.9–10.5 ug/cm2). (3) The relationship between the NNILCC and the NNILNC was significant. The NNILCC derived from the anisotropy relationship between crop LAI and LCC was an effective tool for crop nitrogen status diagnosis. (4) The process of crop LAI, LCC and NNILCC reflected the effect of water and nitrogen supply on crop growth. The appropriate water-nitrogen treatments contributed to LAI increase and LCC accumulation. The study demonstrated that hyperspectral remote sensing technology combined with incremental learning is an effective method for cross-crop growth monitoring and nitrogen diagnosis. These results provide a reference and basis for filed water-nitrogen supply and management.

Contents Index to Volume 36

Contents Index to Volume 36

Physicochemical characterization and antioxidant capacity of the extracted oil from date pits and its effect on storage stability of margarine

Background and aims: The present work deals with the valorization of the date kernel oil of Mech-Degla variety by assessment of its physicochemical and antioxidant properties as well as its use in the formulation of margarine. Methods: Kernels’ oil was extracted using Soxhlet method and its total phenolic (TP), flavonoid and carotenoid contents and DPPH• scavenging activity were estimated using colorimetric assays. After that, this oil was incorporated into margarine. The determined physicochemical parameters were the pH, the salt content, the solid content, the melting point, and the peroxide index. Finally, the elaborated margarine's oxidative stability was evaluated by the Rancimat test. Results: The yield of fat in the extracted oil was 9.84 ± 1.45% and the amount of TP, flavonoids and carotenoids were 112.92 ± 26.57 mg gallic acid equivalent /kg of oil, 15.7 ± 0.7 mg quercetin equivalent/kg of oil and 125.534 ± 0.109 mg β-carotene equivalent/kg of oil, respectively. As regards the anti-DPPH effect, the cold and hot date kernel oil extracts exhibited a moderate capacity by reducing 55.91% and 30%of the free radicals, respectively. After that, table enriched margarine has been industrially elaborated at the Cevital agri-food complex by adding 50 and 100 ppm of date kernel oil. Texture of this margarine was plastic and easy to spread, with an acceptable color and a brilliant and homogeneous appearance. At 37 °C, the solid fat content (SFC) index is lower than 6%, which attested that this margarine melts easily in the mouth. The physicochemical characteristics of the formulated product were also assessed and demonstrated that its pH value was 4.2, its peroxide value was 0.32 meq of O2/Kg of margarine and its melting point was 36.0°C. It was also revealed using the rancimat test that the margarine enriched in date kernel oil proved to be more resistant to oxidation, than the control one. Conclusions: Date kernel oil can be used as a natural additive to enrich table margarine without affecting its properties while improving its oxidation stability. Keywords: Date kernels oil, antioxidant activity, margarine formulation, physicochemical characteristics, oxidative stability.

Retrieval of leaf chlorophyll content using drone imagery and fusion with Sentinel-2 data

Leaf chlorophyll is an important dynamic biochemical parameter to assess crop phenology, health stress, and yield. Optical remote sensing data is a widely used technique for the estimation of vegetation leaf chlorophyll. Drone technology is a promising solution for high-resolution monitoring of the leaf chlorophyll content and employed in this study. Image fusion was also accomplished to provide high-resolution multi-spectral images by combining Sentinel-2A and drone imagery. Support vector machine regression was adopted to determine the best vegetation indices for the retrieval of leaf chlorophyll content. Random forest regression and support vector machine regression algorithms were adopted to develop the best models for chlorophyll retrieval. The 34 models derived from drone data and the 46 models derived from fusion data were evaluated for chlorophyll retrieval. It was found that the best support vector machine model, based on anthocyanin content index and enhanced vegetation index (M31), had the best correlation coefficient (r = 0.732) and root mean square error (1.93). The random forest regression models M32 (based on chlorophyll vegetation index and visible atmospherically resistant index) and M16 (based on canopy chlorophyll content index and visible atmospherically resistant index) for drone data were found to be the best, which performed equally well in terms of correlation coefficients (r = 0.77) and root mean square error (1.51). The multiple vegetation indices of drone-based leaf chlorophyll content random forest regression models (M16 and M32) provided higher performance than single vegetation indices-based linear (simple linear fit) and nonlinear leaf chlorophyll content models. Out of 46 models of fusion products, the random forest regression M14 (green normalized difference vegetation index with narrow near infrared band and visible atmospherically resistant index) offered the best performance for leaf chlorophyll content retrieval, as can be observed through a comparison of correlation (r = 0.77) and RMSE (=1.71) values. It was also investigated that inversion performances (r ∼ 0.8 and RMSD ∼ 1.4 with standard deviation ∼ 2.6) of fusion data-based models in cross-applicability and transferability were found to be suitable for large-scale inversion of Sentinel-2A data products.

Field Testing and Evaluation of a Seven-Row Inclined Plate Planter for Mustard Cultivation

Mustard seed (Brassica nigra) is a crucial oilseed crop extensively cultivated in several countries, especially in South Asia. Enhancing seed planting techniques is essential to optimize crop output and overcome the challenges faced by farmers. Traditional manual planting methods are inefficient and time-consuming, creating obstacles to overall agricultural productivity. To address this issue, a field test and evaluation of a seven-row inclined plate planter for mustard cultivation were conducted. Precision planting, which involves accurate seed placement at desired intervals, is vital for maximizing crop productivity. The study encompassed a comprehensive analysis of soil parameters, including soil type, moisture content, bulk density, and cone index. Various operational parameters such as seed spacing, row spacing, and ground wheel slip were evaluated. The economic aspects, including cost analysis, breakeven point, payback period, and benefit-cost ratio, were considered to assess the financial feasibility of the tractor-operated planter.
 Calibration results revealed variations in seed rates among different rows and hopper capacities, impacting seed placement uniformity. Additionally, the study examined seed breakage under different operational parameters, emphasizing its influence on germination rates. Field performance data included soil moisture (12.61%), bulk density (1.45 g/cc), and field efficiency (82.30%), offering insights into real-world planter operation. The cost analysis determined a favorable economic outlook, with a benefit-cost ratio of 1.2, signifying the economic viability of machine harvesting compared to manual methods.

Influence of flowering on the anatomical structure, chemical components and carbohydrate metabolism of Bambusa tuldoides culms at different ages.

Bamboo forests, which have come to occupy large areas in recent years, naturally undergo the process of blooming. However, bamboo culms and rhizomes degenerate after the plants bloom, resulting in widespread loss of raw materials. Systematic research on the properties and physiology of bamboo culms after flowering is lacking, and whether flowering bamboo culms could be used as raw materials in industry is unclear. In this paper, we compared and measured the fiber morphology, chemical components, and sugar metabolism indexes of non-flowering and flowering Bambusa tuldoides culms at different ages. The results showed that the fibers in the middle internodes of both non-flowering and flowering B. tuldoides culms had the longest length. The fibers completed their elongation within 1 year, but the fiber walls were continually deposited with age. The levels of the chemical components in the nonflowering culms also continually increased with age. The nonstructural carbohydrate (NSC) content and sugar metabolism indexes showed the highest levels in the 2-year culms and then declined in the 3-year culms. Compared to young culms that had not yet flowered, the 3-month-old and 1-year-old flowering culms had a significant decrease in the fiber length and tangential diameter, and their holocellulose and lignin levels also decreased, while the levels of ash, SiO2, 1% NaOH extractives, and benzene-ethanol extractives increased. A correlation analysis showed that sugar catabolism was accelerated in the flowering cluster, which could lead to "starvation death" in bamboo and which had a significant negative impact on the anatomical and chemical properties of the bamboo culms. Generally, the flowering bamboo culms had shorter fibers, higher levels of extractives and ash, and lower holocellulose content, which indicated that bamboo flowering has an adverse effect on the application of such components in the production of pulp, in papermaking, and in other processing and utilization activities. This study revealed the physiological changes in flowering B. tuldoides culms and provided a theoretical basis to inform the utilization of culms in this species.

Hygrothermal performance of natural building materials: Simulations and field monitoring of a case study home made of wood fiber insulation and clay

This contribution presents temperature and relative humidity data monitored over nearly two years for a case study building made of natural building materials. The case study building is a single-family house located in Denmark made of wood fiber insulation, wood fiber boards and indoor clay plaster without any membranes. Three different types of cladding systems have been tested: 1) mineral plaster rendering; 2) wood cladding applied directly over wood fiberboards; 3) wood cladding with a ventilated cavity. Monitored data is provided and compared with simulations performed with a commercial hygrothermal software. The moisture content and mold growth index are calculated from monitored data. The data indicates that the hygrothermal performance of the roof is excellent (RH < 70%); the hygrothermal performance of the walls with the three different cladding systems is good; one out of two sensor groups in the floor exhibits a moisture content up to 18% at the cold side of the insulation during summer and fall. Securing sufficient and evenly distributed crawlspace ventilation is recommended for eliminating concerns of eventual mold growth. Measurements show that materials employed in this house respond quickly to moisture changes, more quickly that simulated data. This work highlights the need for validating and adjusting WUFI simulation results with measured data to provide reliable results for building envelopes composed of highly hygroscopic plant-based materials. For these assemblies in these conditions, including a vapor retarder is not needed for achieving a satisfactory hygrothermal behavior.

Effect of wheat dextrin on corn flour extrusion characteristics

Wheat dextrin is a modified wheat starch, classified as water-soluble. This study investigated the effect of wheat dextrin as an ingredient in corn flour blends on extrusion characteristics. Blends were prepared at 0, 10 and 20 % fibre content. DOE was used to design experiments and investigate the effects of variables selected to be studied. Feed moisture content was set at 18–25 %, temperature at 110–150 °C and specific feeding load at 0.100–0.150kg/rev. Moisture content, water absorption and solubility indices, color, sectional expansion index, density, hardness, crispiness (work (Wc) and number of spatial ruptures (Nsr)) and specific mechanical energy were evaluated. A regression model was established using response surface methodology, and processing conditions for optimal quality were generated (e.g., WSI: 96.9 %, SME: 96.9 %, final MC: 93.9 %). Wheat dextrin solubility characteristics for moisture content, WAI and WSI were inconclusive, showing a high tendency to insoluble behavior. For expansion, lightness and SME characteristics depended on processing conditions, especially temperature. Crispness was highest at low MC (18.87 %) x high fiber content (20 %) (e.g., Nsr: 1.2–1.5/mm), whereas values were the lowest at high MC (25.70 %) x low fiber content (0 %) (e.g., Nsr: 0.5–0.7/mm). Optimal conditions were set at 12 % fiber content, 19 % feed moisture content, 130 °C and a specific feeding load of 0.146 kg/rev. This study showed that it is impossible to classify wheat dextrin as acting strictly according to soluble fiber characteristics based on extrudate characteristics.

Environmental influence on summer survival of Manila Clam Ruditapes philippinarum: A case study in an aquaculture bay

The aquaculture of Manila clam (Ruditapes philippinarum) is under threat due to its high mortality in summer. To investigate the environmental influence on mortality of the species, we have conducted field surveys in the aquaculture area in Laizhou Bay, during the summers of 2019 and 2020. Environmental and biological data were collected. The results of data analysis have shown that in 2020, large-scale mortality events were not recorded and spatial variations of environmental variables were no significant within the survey area. However, in August 2019, significant variations of environmental variables were detected in the middle tidal area. This area was charactered with relatively high-water temperature (with maximum temperature of 31.49 °C and mean value of 26.17 ± 1.62 °C), elevated hydrogen sulfide concentrations (with a maximum concentration of 24.72 μmol/L and a mean concentration of 7.89 ± 4.14 μmol/L), and low dissolved oxygen concentrations (with a minimum concentration of 3.35 mg/L and a mean concentration of 6.27 ± 0.42 mg/L). Correspondingly, high mortality of the clam was recorded in the area, the abundance of live Manila clams has decreased by 80%. No significant abnormalities of environmental variables and clam growth were observed in other regions in 2019. Glycogen content and condition index of the clam were analyzed to investigate the relationship between environmental stress and the health of the clam. Compared to the condition index, glycogen content is a more sensitive indicator of the health status of the clam because changes in glycogen content appeared earlier than changes in condition index and mortality. A principal component analysis further indicated that the high mortality of the clam corresponds with a few environmental variables, including elevated temperature, hypoxia and the concentration of hydrogen sulfide. The simultaneous presence of these multiple environmental stressors could have triggered alterations in the physiological responses of the clam.

Spatial and Temporal Variability of Vegetation Indices with Industrial Tomato Yield

Vegetation indices indicate crop development and help identify areas with potential productivity reduction in the desired crop. Thus, this study aimed to determine the spatial and temporal influence of vegetation indices on industrial tomato (Solanum lycopersicum L.) yield. The research was conducted at Barcelos Farm in Anápolis, GO, covering a 55-hectare area. A sampling grid of 61-point pairs, spaced at 90 x 90 meters, was established using a GPS receiver. Vegetation indices were characterized by measuring the Soil Plant Analysis Development (SPAD) index, foliar nitrogen content through the Kjeldahl method, and Normalized Difference Vegetation Index (NDVI) using both a spectroradiometer and satellite imagery. Industrial tomato yield was assessed during harvest. Through the results, it was observed that temporal variability between vegetation indices and actual foliar nitrogen content exhibited a significant and positive correlation with industrial tomato productivity, particularly during the flowering stage. However, temporal variability between vegetation indices and foliar nitrogen content displayed low correlation across the mapped areas over time. Determining foliar nitrogen content and vegetation indices during the flowering stage is recommended for the industrial tomato crop. The relationship between ground-based remote sensing NDVI and orbital NDVI displayed a 55% positive correlation during the flowering stage.

Valorization of sorghum ash with digestate and biopreparations in the development biomass of plants in a closed production system of energy

Replacing chemical fertilizers with non-toxic waste that meet all fertilizing purposes, including ash from plant biomass and their management is becoming the important goal of sustainable agriculture concerning energy plants production in a closed system. This study aims to explore a novel strategy for utilizing natural sorghum ash together with digestate and ecological compounds, to replace synthetic fertilizers, for the energy plant development improvement and thus reduction of the environment pollution. Sorghum, as an energy plant, cultivated in low quality sandy and podzolic soils, in Central and North Poland climate, was fertilized with different doses of YaraMila Complex, a synthetic fertilizer (0, 150, 300 kg ha−1 Each dose was supplemented with different amounts of sorghum ash (0.5, 1, 2 and 4 t ha−1), used alone or with addition of APOL-HUMUS (soil improver; 10 L ha−1), biogas plant digestate (30 m3 ha−1) and Stymjod (nano-organic leaf fertilizer; 5 L ha−1). Added to each YaraMila Complex dose, the applied ash amounts (optimally 2–4 t ha−1), increased growth of plants, crop biomass, index of chlorophyll content, net photosynthesis, transpiration, stomatal conductance, content of intercellular CO2, activity of acid and alkaline phosphatase, RNase and dehydrogenase and energy properties. Sorghum ash used with the lesser YaraMila Complex doses of 0 or 150 kg ha−1 caused the enhanced growth of plants more than the doubled YaraMila Complex amounts applied alone (150 or 300 kg ha−1, correspondingly). Additionally, applied biogas plant digestate, APOL-HUMUS and Stymjod further increased the plant growth. This indicates that the application of natural sorghum ash accelerates energy plant development, can reduce by half the recommended synthetic fertilizer doses on poor and marginal soil and enables the cultivation of sorghum in a closed production cycle.

206 Development and Validation of an Indigestible Protein Index to Investigate the Effects of Protein Content in Weaned Pigs: A Multivariate Approach

Abstract Increased proteolytic fermentation may lead to negative effects on gastrointestinal health and function, which ultimately impact on performance. The objective was to develop and validate, by investigating performance and gut structure outcomes, an index of indigestible protein content (IDP) in weaned pigs. Ninety-four studies reporting growth performance [average daily gain (ADG), average daily feed intake (ADFI), gain: feed (GF), initial (IBW) and final body weight (FBW)] and duodenal histomorphometries [villus height (VH), crypt depth([CD), and villus height: crypt depth ratio (VCR)] variables of pigs fed different protein content (CP) and sources in the diet were included. Diets were recalculated using a common database to generate the IDP from each study. Studies were grouped by similarity in performance in two clusters (C1 and C2) by hierarchical clustering on principal components (HCPC). The effects of cluster were investigated. Quadratic response plateau (QRP) models were fitted to assess the interrelationships between ADG, ADFI, GF, VH, CD, and VCR with the dietary CP or calculated IDP content within cluster. Pigs from C2 had greater IBW (6.3 vs. 8.8 ± 0.2kg), FBW (10.2 vs. 17.2 ± 0.7kg), ADG (0.2 vs. 0.4 ± 0.0kg/d), and ADFI (0.3 vs. 0.6 ± 0.1kg/d) compared with C1 (P < 0.05). There was no effect of cluster (P > 0.05) on VH (405.5 vs. 405.5 ± 15.8μm), CD (232.5 vs. 220.7 ± 10.1μm), or VCR (1.9 vs. 2.0 ± 0.3μm). Pigs from C1 achieved break point (BP) and plateau (Pl) for VH (BP = 24.25%, Pl = 96.32μm; P < 0.05) when fed increasing CP content and for ADG (BP = 2.32%, Pl = 0.28kg/d; P < 0.05) and GF (BP = 2.18%, Pl = 0.83kg/kg; P < 0.05) when fed increasing calculated IDP content. Pigs from C2 fed increasing content of calculated IDP achieved BP and Pl for ADG (BP = 3.04%, Pl = 0.54kg/d; P < 0.05). Our findings suggest that calculated IDP might be a reliable index to investigate the effects of proteolytic fermentation on pig performance, particularly in the immediate post-weaning phase.

Effect of Scion Dip Treatments and Growing Condition on Physiological Parameter of Mango (Mangifera indica L.) Wedge Graft cv. Dashehari

The current study was carried out on wedge grafting in Mango (Mangifera indica L.) cv. Dashehari during the2022-23 at the Fruit Research Station, Imaliya, Department of Horticulture, JNKVV Jabalpur. This research includes the use of many different plant growth regulators, ZnSo4, and growing conditions. The research was carried out using a statistical design known as Factorial Completely Randomized Design (FCRD).The primary objective of this study is to determine the influence that different scion dip treatments and growing conditions have on the physiological characteristics of the plant. According to the findings, among the various treatments, IAA 200 ppm + ZnSo4 500 ppm under shade net condition was proved superior with respect to maximum chlorophyll content index (27,18.5), leaf area duration (2720.67 cm2/day, 2,620.67 cm2/day), leaf area index (8.65,1035) and light transmission ratio (24.05,18.15) at 60 and 120 days after grafting (DAG). It was also noticed that scion dip treatments with IAA 200 ppm in combination with ZnSo4 500 ppm under the shade net condition were favorable as compared to the open condition.

Bioenergy crops monitoring using Sentinel-2 and UAV-derived imagery

Purpose. Establishing the regularities for the monitoring of the bioenergy crop conditions using Sentinel-2 and UAV-derived imagery. Methods. A field experiment was carried out in an experimental field of the Institute of Bioenergy Crops and Sugar Beet National Academy of Agrarian Sciences of Ukraine (50.023194, 30.173895), located in a zone of unstable soil moisture in the Right Bank Forest Steppe, in 2022−2023. Results. Among the studied traditional crops, sugar sorghum, sugar beet, and fodder beet are interesting crops from the standpoint of biomass for energy, as they can produce 110 t/ha, 120 t/ha, and 135 t/ha of biomass, respectively, or 20 t/ha, 26 t/ha, and 24 t/ha of dry matter, respectively. The yield of energy crops can be predicted with an acceptable level of accuracy using many known vegetation indices. However, the relationships between vegetation indices and crop yield are not consistent at every stage of plant growth and development, leading to low accuracy in yield estimation. The combination of vegetation indices related to the structural characteristics of the canopy and chlorophyll content in the aboveground biomass can improve the accuracy of yield estimation. Moreover, combining vegetation indices related to canopy structure, chlorophyll content, and stress indices as input to yield prediction models may provide even higher correlations for yield prediction. Conclusions. Usually, plantations of miscanthus and switchgrass are fertilised annually, while willow and poplar are fertilised every 3–4 years, after each harvesting. Therefore, the nutrient provision of tree species may not be sufficient. It was found that the content of total nitrogen in the soil of bioenergy plantations highly correlates with NDVI. To use NDVI for bioenergy crop prediction, an algorithm for determining the level of plant nutrients should be developed. It was found that at the end of the growing season (September or early October), the use of vegetation indices allows for the accurate estimation of the size and condition of bioenergy plantations since most crops in this period are already harvested. Sentinel-2-derived imagery is useful for monitoring bioenergy crop plantations as it provides images with a resolution of 10 m at 3–5-day revisiting time. We investigated NDVI on a total area of Miscanthus × gigantheus plantations of 2.9 ha. The satellite-derived data accumulated and aggregated by the OneSoil application as of August 20 and September 19 resulted in NDVI values of 0.80 and 0.70, respectively, while the NDVI obtained with UAV imagery was 0.82 and 0.77, respectively. Consequently, the satellite can provide quite acceptable NDVI data for use in the monitoring of bioenergy plantation yield at the national level.

QSPR study to predict some of quantum chemical properties of anticancer imidazo[4,5‐b]pyridine derivatives using genetic algorithm multiple linear regression and molecular descriptors

AbstractPyridine and its derivatives have been applied clinically for the treatment of a wide range of diseases and in the synthesis of novel drugs. In the present work, imidazo[4,5‐b]pyridine derivatives as anticancer drugs were exhibited to select the important descriptor for quantum chemical properties. Two of the fundamental thermodynamic properties are heat capacity (Cv) and entropy (S), which are important in the field of chemical kinetics and are key in the understanding and design of chemical processes involving chemical reactions. A Quantitative Structure–Property Relationship (QSPR) study was used to predict the quantum chemical properties like Cv and S of 105 imidazole derivatives using molecular descriptors and the genetic algorithm–multiple linear regression (GA–MLR). The best QSPR models were selected using criteria coefficients such as R2, R2adj, RMSE and Fisher ratio. Different internal and external validation metrics were adopted to evaluate the stability, fit and predictive power of the QSPR models. The validation results and statistical analysis show that the models possess good prediction power and robustness, and the total size (TS) and Sanderson electronegativity(RDF060e) and total information content index(TIC1) of imidazo[4,5‐b]pyridine derivatives are increasingly related to the studied properties.