Plant Area Research Articles

Cultivation Strategies to Modify Biomass Partitioning and Improve Yield in Controlled-environment Production of High-cannabidiol Cannabis (Cannabis sativa L.)

Two common challenges reported by cannabis growers are low yields and small profit margins. Although recent research of cannabis yield has focused on lighting and nutrition, little research has examined how changes in other cultivation practices may be beneficial. The objective of this study was to evaluate the following two techniques to potentially improve yield: fertilizer restriction (FR) to reduce plant size and, thus, increase plant density and shoot number manipulation (SNM) to reduce shoot length and improve biomass partitioning. The FR technique involves leaching the substrate and providing only tap water for 0, 1, or 2 weeks at the start of flower initiation, whereas SNM involves pinching shoot tips 2, 3, or 4 times to produce 4, 8, or 16 shoots/plant, respectively. This study used a full factorial treatment design for a total of nine treatments (three FR × three SNM). Plants were flowered under 12-hour photoperiods for 8 weeks and then destructively harvested for data collection. The results demonstrated that both techniques improve plant productivity in different ways. The FR technique reduced all mass measurements (g/plant) and decreased plant area (m2/plant); therefore, the yield metrics (kg·m−2) increased with the increasing FR treatments. The SNM technique did not affect plant area, but more pinching events resulted in a decrease in reproductive shoot length (cm/shoot) and an increase in inflorescence to trim the dry mass ratio (inflorescence:trim). Shorter shoot lengths are desirable for eliminating trellis support netting, which helps growers reduce material costs and improve labor efficiency during harvest. Increasing the inflorescence:trim may also reduce labor costs related to trimming, which comprise the largest cost of production by many growers. Although both techniques offer advantages, there are trade-offs that must be considered in the context of overall profitability.

Parental environment as a factor shaping salinity tolerance in halophyte Tripolium pannonicum L.

Parental environment can significantly influence a range of plant traits across different growth phases and developmental stages. The impact of parental salinity variability on offspring germination and environmental factor response still requires thorough investigation. Therefore, we investigated seeds of Tripolium pannonicum L. from low-saline (Cie) and high-saline (Ino) habitats to elucidate the germination potential and adaptation potential of progeny to varying salinity levels. Germination and growth experiments were conducted to analyze germination parameters, plant areas, water-related traits, the concentration of organic solutes, malondialdehyde, and the activity of crucial oxidative defence enzymes. In the germination experiment, Cie seeds demonstrated higher germination potential with longer germination time under 200–400 mM NaCl compare with Ino seeds. The Cie population achieved the highest shoot and roots area at 100 mM and 300 mM NaCl, respectively. The Ino population exhibited its highest shoot and roots area at 200 mM NaCl. The Ino population indicated an increase in stem cortex cell area at 400 mM NaCl. The Ino population enhanced the synthesis of osmolytes as part of the salinity tolerance mechanism. Antioxidant enzyme analysis indicated higher peroxidase activity in Ino and higher superoxide dismutase activity in Cie under salinity, suggesting distinct enzymatic roles in salinity adaptation between populations. Our findings highlight the critical role of parental environmental conditions in shaping progeny traits, enhancing germination potential, and enabling adaptation of progeny plants to diverse environmental niches. The study underscores population-specific responses to environmental factor, emphasizing the complexity of halophyte adaptation mechanisms to salinity.

Research and Application of Electromagnetic Heating Device for Digital Well Site Crude Oil Export

Abstract Most well sites have discontinued using the associated gas-fired furnaces in response to the current situation in the oil fields. Coal-fired heating furnaces are environmentally polluting and prohibited due to local environmental regulations. These two heating methods can cause high costs, poor heating efficiency, and environmental pollution, which cannot be achieved through remote digital monitoring. Research has been conducted on the digital electromagnetic heating device for crude oil in the well site, focusing on introducing its main components and functions, including the electromagnetic heating body, frequency conversion control cabinet, and digital remote monitoring terminal. This device provides one-way internal heating without a heat source, resulting in high thermal efficiency, safety, environmental friendliness, and energy conservation. It comprehensively addresses the drawbacks of traditional electric heating, characterized by low efficiency, susceptibility to damage, and difficult maintenance. In 2022, it was applied at three well sites in the Tongzhai operation area of the Third Oil Production Plant of Changqing Oilfield, replacing the existing gas-fired and coal-fired heating furnaces to heat crude oil, as well as heating the heating belt and various electric heating pipes. This device is highly efficient, safe, environmentally friendly, and energy-saving. Additionally, the temperature and pressure of electromagnetic heating crude oil can be digitally and remotely monitored.

Research and Application of Online Electromagnetic Wax Prevention Device for Oil Wells

Abstract Wax deposition in oil wells can affect normal production, increase the hanging point load of oil wells, increase system energy consumption, reduce system efficiency and pump efficiency, affect oil well production, and even directly block oil pipes, causing oil well shutdown. Wax deposition in oil wells is one of the prominent problems that affect the high and stable production of oil wells. Wax prevention in oil wells is an important maintenance measure to reduce oil well load, save energy and reduce consumption, and extend the maintenance free period of oil wells. There is an urgent need for a long-term wax prevention technology to prevent wax deposition in oil wells, reduce pipe and rod friction, and reduce hanging point load and load current. We conducted research on the electromagnetic wax prevention online device for oil wells, with a focus on introducing the composition and functions of the electromagnetic wax prevention online device for oil wells, which consists of a high-performance electromagnetic conversion device and a control unit. Through on-site application in 10 oil wells in the Tongzhai operation area of the Third Oil Production Plant in Changqing Oilfield in 2023, an electromagnetic anti wax online device was installed on the wellhead process. The anti wax effect not only affects the downhole process but also the surface process, effectively alleviating wax accumulation in the oil wells, replacing frequent hot washing, adding wax cleaning agents and other technologies, extending the well washing cycle and maintenance free period, avoiding wax blockage of pipelines or wax stuck wells, and effectively controlling production and operation costs, Improve the economic benefits of oil well development.

Research and Application of Online Electromagnetic Heating System with Internal Penetration in Oil Pipeline at Well Site

Abstract In response to the current situation of heating crude oil in the oil pipeline of Changqing Oilfield, most of the well sites have no associated gas, gas heating furnaces have been discontinued, and coal-fired heating furnaces pollute the environment. A study was conducted on the online through type heating system for the oil pipeline in the well site, with a focus on the composition and function of the digital heating system for the through type oil pipeline in the well site. The through type online heating system for the oil pipeline in the well site is mainly composed of a variable frequency electromagnetic controller The online controller and internal heating cable are composed of three parts. The oil pipeline generates heat by itself, while preventing the crystallization of paraffin and scale in the oil pipeline under the action of alternating electromagnetic fields, which is not easy to form wax. In 2023, on-site application was carried out on two oil pipelines in the Tongzhai operation area of the Third Oil Production Plant in Changqing Oilfield, replacing the existing gas heating furnaces and coal-fired heating furnaces to heat and transport crude oil in the oil pipelines. It does not generate heat itself and has a long service life. Due to the high thermal efficiency of the heat source coming from the inside of the oil pipeline, the buried pipeline renovation can be installed without breaking the soil. The flexible internal cable reduces the difficulty of construction and is safe and environmentally friendly, At the same time, it can remotely monitor the temperature of crude oil in the oil pipeline and the wellhead backpressure online.

Integrated Magnetic and Geochemical Assessment of the Soil from the Steam Power Plant Area of South Kalimantan Province

Abstract The magnetic proxy approach has proven to be efficient in the assessment of pollution by potentially toxic elements when targeting soils or areas with a homogeneous background where anthropogenic magnetic signals can be easily distinguished. It’s crucial to conduct research on the impact of fly ash on the vicinity of the PLTU in this particular area, as it’s a previously unexplored area. The unique thing about this research is that this PLTU uses coal containing Fe, Pb, and Mg as fuel and has a fairly high susceptibility value for fly ash and bottom ash. This study is due to an analysis of the magnetic susceptibility and heavy metal content in the soil of the area around the Asam-Asam steam power plant (PLTU) of South Kalimantan Province, where geogenic input and fly ash can influence it. Heavy metals that have passed the threshold at all locations are Ti, Cr, Mn, Fe, Ni, Cu, V, and Al. Most of the correlation coefficients are strong and significant between magnetic susceptibility values and heavy metal concentrations at each location. The correspondence between magnetic susceptibility values and heavy metal content reflects the potential of magnetic proxy methods at polluted spots, provided that the lithological conditions are carefully considered.

Improving plant nutrition and growth through the use of minerals extracted from the sea on Aubergine and cucumber plants

Research objective: The aim of this research was to evaluate the stimulating potential of a product (FertilTomix) obtained by an innovative extraction process from seawater with the addition of silver, copper and zinc on aubergine and cucumber plants. In addition, it was assessed whether the product improves the nutritional quality of the fruit. Materials and Methods: The experiments, which started in May 2024, were conducted in the CREA-OF greenhouses in Pescia (Pt), on aubergine (Solanum melongena L.) and cucumber (Cucumis sativus). Plants were placed in pots of ø 14 cm, 30 plants per thesis, divided into three replications of 10 plants each. The experimental groups were: i) control group; ii) conmmercial biofertilizer; iii) FertilTomix; iv) FertilTomix with added silver, copper and zinc. On 10 September 2024, plant height (aubergine), length of the central branch (cucumber), number of leaves, leaf area, vegetative weight, root volume, number and weight of fruits were determined. The nutritional properties of the fruits were also assessed, for aubergine (iron, calcium, sodium, potassium, phosphorus, zinc, riboflavin thiamnine, vitamin C, niacin, vitamin B6, folate) and for cucumber (potassium, phosphorus, calcium, magnesium, sodium, iron, pantothenic acid, pyridoxine, zinc, manganese, vitamin C, niacin, riboflavin, vitamin E, thiamine, vitamin K, folate). Results and Discussion: The experiment showed that the use of FertilTomix, can significantly increase the height, number of leaves, vegetative and root growth, and leaf area of aubergine and cucumber plants. The product FertilTomix with added silver, copper and zinc worked better than as such, stimulating plant growth more. The trial also showed an increase in the number and weight of fruits in both aubergine and cucumber, in the theses treated with FertilTomix compared to the control and the commercial control with algae. The leaves also appeared larger and more intensely green in the theses treated with minerals extracted from the sea. The analysis of the mineral and vitamin content of the fruits showed a significant increase in minerals and vitamins in the fruits treated with FertilTomix for most of the analysed parameters, to a greater extent with FertilTomix with added silver, copper and zinc Conclusions: Various extracts obtained from seawater using an innovative mineral process were found to significantly increase plant growth. The test also showed an increase in the mineral and vitamin content of the fruit, probably influenced by the increased presence of bacteria in the soil, in the theses treated with marine extracts, as demonstrated in other tests with the same product. As well as for those wishing to reduce the use of industrial fertilisers, the results obtained are particularly interesting for those growing in arid environments or those without drinking water

A crop disease severity index derived from transfer learning and feature fusion using enhanced OPTICS algorithm

The adoption of automated methods for the identification and assessment of tomato-related disorders is highly sought-after in the agriculture sector. Using this technology is crucial for reducing wasteful spending, increasing the efficiency of treatments, and ultimately growing more resilient crops by reducing losses in agricultural output and maximising the effectiveness of these processes. An automated method has been suggested for accurately identifying and classifying diseases using a single photograph. The described method for disease detection in tomato plants makes use of a computer vision-based technique. Image processing, ML, and deep learning are just a few of the methods that this strategy uses. The goal of this approach is to prevent tomato crops from being damaged by various illnesses by reducing the need of conventional procedures. Bacterial spot, early blight, late blight, leaf mould, spider mites, target spot, spotted spider mite, mosaic virus, and yellow leaf curl are all examples of these illnesses. The following ten diseases frequently strike tomato crops in India. By utilising picture segmentation in combination with the Enhanced OPTICS algorithm (EOPTICSA), the affected area of the tomato plant may be precisely detected and defined after image pre-processing procedures have been used. It may be necessary to look for certain visual signs in order to diagnose the previously mentioned illnesses. The primary goal of this study was to evaluate the efficacy of the EOPTICSA method for detecting diseases in plant leaves. To eliminate the geometric features associated with colour, texture, and leaf arrangement in the provided plant pictures, image segmentation and edge detection methods are employed. Using these methods allows us to achieve our goal. Various efficacy measures are used to assess and provide a technique recommendation. This research shows that when performance metrics are used to implement these strategies, the suggested strategy outperforms the current methods in terms of accuracy, precision, and F1-score. The process of detecting sickness involves several consecutive steps. Capturing images, segmenting them, detecting edges, and determining the infection’s severity are all steps in this process. To accomplish the goal of recognising and categorising different types of diseases that might impact tomato plants, the method of transfer learning is employed. As soon as the problem is identified, it is recommended to take proactive measures to help individuals and organisations involved in agriculture address the effects of these disorders using appropriate measures.

The conserved transcriptional regulation mechanism of ADH1 gene in Zanthoxylum armatum to waterlogging stress

Waterlogging stress negatively affects plant growth and survival. However, the ability of Zanthoxylum armatum, a valuable tree species, to tolerate and adapt to waterlogging stress remains poorly understood. Here we report how alcohol dehydrogenase 1 (ZaADH1) confers waterlogging stress tolerance in Z. armatum. ZaADH1 expression was induced after waterlogging treatment. ZaADH1 overexpression increased waterlogging stress by modulating the metabolite levels of the ADH enzyme, soluble sugar, and trehalose, promoting glycolysis and carbohydrate metabolism. The overexpression of ZaADH1 in Arabidopsis thaliana increased the total plant area and chlorophyll content, thereby increasing resistance to waterlogging stress. Physiological and overexpression transcriptome analyses in A. thaliana indicated that ZaADH1 overexpressing lines generated more carbohydrates to meet energy demands, employing a “static” strategy to increase tolerance to waterlogging stress, which confirms the conservation of the ADH1 response to waterlogging stress and represents a potential crucial measure for improving waterlogging tolerance in Z. armatum.

Integrative plant area index retrieval and spatiotemporal analysis in Taihu Lake Basin via synergistic active-passive remote sensing techniques

ABSTRACT The Taihu Lake basin is one of the fastest-growing regions in China, where the natural environment has been seriously affected by humans. The plant area index (PAI) is an important parameter reflecting the change in vegetation growth, which plays a crucial role in studying vegetation growth and protecting the ecological environment. Advancements in remote sensing technology, complemented by machine learning techniques, have facilitated the accurate and efficient acquisition of PAI over large areas. In this study, the Taihu Lake Basin vegetation area was taken as the research object. Global Ecosystem Dynamics Investigation (GEDI) point cloud data and Landsat-8 remote sensing images were the primary information sources. MODIS land cover types were utilized to classify the vegetation into six categories. Three classical machine learning models, namely, Random Forest (RF), Support Vector Regression (SVR), and Back Propagation Neural Network (BPNN), were used to estimate the PAI in the Taihu Lake Basin. It was found that the RF model showed the best performance. The determination coefficients (R2) for grassland, evergreen forest, mixed forest, deciduous forest, farmland, and wetland were 0.71, 0.67, 0.69, 0.66, 0.65, and 0.69, respectively. Over 2000-2022, the PAI exhibited an absolute change rate of 0.035, with an overall increasing trend. The area of improved and degraded vegetation accounted for 58.33% and 41.67% of the total area, respectively. The study also revealed that PAI was positively correlated with precipitation (R = 0.64, P < 0.05) and negatively correlated with temperature (R = -0.58, P < 0.05). Different land types’ effects on PAI were also analyzed, with wetland PAI having the smallest mean value and evergreen forest PAI having the most considerable mean value. This research underscores the effectiveness of integrating GEDI data and Landsat-8 imagery in PAI assessment, providing valuable insights for environmental monitoring and analysis in the Taihu Lake Basin.

Detection and assessment of heavy metals concentration in wheat leaves collected from the vicinity of Sahiwal coal power plant, Pakistan, employing a modern data analysis approach

ABSTRACT Heavy metal pollution in food crops has become a global issue, especially in staple crops like wheat and rice. Electricity production utilising coal, ignites this issue in crops grown in the surrounding areas of coal power plants. Keeping this view in mind, the concentration of six heavy metals (HMs) Calcium (Ca), Cadmium (Cd), Chromium (Cr), Cobalt (Co), Lead (Pb) and Magnesium (Mg) in wheat leaves have been assessed in this study. Fifty samples of wheat leaves have been collected from the surrounding areas of the coal power plant in Sahiwal. The samples were prepared using the wet digestion method (WDM). Finally, these samples have been sent for analysis via atomic absorption spectroscopy (AAS). The limit of detection (LOD) and limit of Quantification (LOQ) of AAS were calculated with the help of blank samples. The concentration of Ca, Cd, Cr, Co, Pb and Mg in wheat leaves were 1.0187 ± 0.549 mg/kg, 0.00484 ± 0.00403 mg/kg 00,416 ± 0.00334 mg/kg, 0.0534 ± 0.0351 mg/kg, 0.035 ± 0.018 mg/kg, 0.464 ± 0.200 mg/kg respectively. The concentration of all understudy metals was below the Food and Agriculture Organization/World Health Organization (WHO/FAO) standards except for Co, in one sample. However, the concentration of heavy metals may increase, which may have profound repercussions. Therefore, preventive measures should be taken in this regard. The neutrosophic approach has been utilised to examine the variation of the heavy metals content in wheat leaves. This study provides a solid scientific foundation for future appropriate actions and management of heavy metals contamination in food crops near coal-fired power stations.

Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs.

In a production environment, delayed stress recognition can impact yield. Imaging can rapidly and effectively quantify stress symptoms using indexes such as normalized difference vegetation index (NDVI). Commercial systems are effective but cannot be easily customized for specific applications, particularly post-processing. We developed a low-cost customizable imaging system and validated the code to analyze images. Our objective was to verify the image analysis code and custom system could successfully quantify the changes in plant canopy reflectance. 'Supercascade Red', 'Wave© Purple', and 'Carpet Blue' Petunias (Petunia × hybridia) were transplanted individually and subjected to increasing fertilizer treatments and increasing substrate pH in a greenhouse. Treatments for the first trial were the addition of a controlled release fertilizer at six different rates (0, 0.5, 1, 2, 4, and 8 g/pot), and for the second trial, fertilizer solution with four pHs (4, 5.5, 7, and 8.5), with eight replications with one plant each. Plants were imaged twice a week using a commercial imaging system for fertilizer and thrice a week with the custom system for pH. The collected images were analyzed using an in-house program that calculated the indices for each pixel of the plant area. All cultivars showed a significant effect of fertilizer on the projected canopy size and dry weight of the above-substrate biomass and the fertilizer rate treatments (p < 0.01). Plant tissue nitrogen concentration as a function of the applied fertilizer rate showed a significant positive response for all three cultivars (p < 0.001). We verified that the image analysis code successfully quantified the changes in plant canopy reflectance as induced by increasing fertilizer application rate. There was no relationship between the pH and NDVI values for the cultivars tested (p > 0.05). Manganese and phosphorus had no significance with chlorophyll fluorescence for 'Carpet Blue' and 'Wave© Purple' (p > 0.05), though 'Supercascade Red' was found to have significance (p < 0.01). pH did not affect plant canopy size. Chlorophyll fluorescence pixel intensity against the projected canopy size had no significance except in 'Wave© Purple' (p = 0.005). NDVI as a function of the projected canopy size had no statistical significance. We verified the ability of the imaging system with integrated analysis to quantify nutrient deficiency-induced variability in plant canopies by increasing pH levels.

Experimental and numerical study on explosion resistance of polyurea-coated shelter in petrochemical industry

To reduce the number of casualties in explosion accidents, blast-resistant shelters can be used to protect personnel in high-risk areas of petrochemical processing plants. In this work, the deformation behaviours of uncoated and polyurea-coated blast-resistant plates were studied through gas explosion tests. An ANSYS/LS-DYNA model of a polyurea-coated shelter was established, and the dynamic responses of the shelter under various explosion loads were analysed. A series of fuel–air explosion tests were carried out to investigate the explosion resistance of the full-scale shelter. The results showed that compared with the uncoated blast-resistant plate, the deformation of the polyurea-coated blast-resistant plate was significantly reduced. The overall deformation of the shelter was the central depression of the wall and the inward bending of the frame. The damage effect of a typical high-overpressure, low-duration load was greater than that of typical low-overpressure, long-duration load. The shelter remained intact under three repeated explosive loads, with cracks appearing on the inner wall but no collapse or debris splashing. The shock wave attenuation rate of the shelter reached over 90%, which could significantly reduce the number of indoor casualties.

Radiological characterisation of freshwater fish species from strategic locations in Bangladesh

A radiological assessment of inland freshwater fishes of wetland haor zones, near a uranium mine and Rooppur Nuclear Power Plant (RNPP) areas, was performed. Gamma spectrometric analysis showed the accumulation of 226Ra, 228Ra, and 40K in all studied fishes, with varying degree levels of concentrations. The average radioactivity levels of 226Ra, 228Ra and 40K in haor fish samples ranged from 2.76 ± 1.51 to 22.02 ± 3.81 Bq kg−1, 1.78 ± 0.69 to 21.53 ± 1.40 Bq kg−1 and 405.51 ± 22.04 to 749.80 ± 42.65 Bq kg−1, respectively. Conversely, the respective values for Bata fish samples of Rooppur Nuclear power plant sites varied from 2.66 ± 0.80 to 6.62 ± 0.81 Bq kg−1, 2.31 ± 0.62 to 5.18 ± 49.81 Bq kg−1 and 342.00 ± 4.98 to 461.45 ± 18.00 Bq kg−1, respectively. Activity levels of Taki fish (Channa punctatus) from haors zones were almost 3–4 times higher than the Meni fish (Nundus nundus) of the same locations and Bata fish (Labeo bata) of the RNPP site. The general public may attain doses of 244.54 µSv from the consumption of haor fish and 84.02 µSv from the fish of the RNPP sites yearly. The chance of an increase in cancer risk from intake of haor fish was higher than the ICRP values of 2.9 × 10−4. Univariate statistics showed that 226Ra and 228Ra radionuclides do not normally distribute, whereas 40K is normally distributed in the studied fish species. Multivariate statistical analysis demonstrated that the radioactivity and estimated radiological parameters are strongly positively correlated with 226Ra and 228Ra, and also positively correlated with 40K. Hence, it indicated that the contents in the freshwater fish species are usually controlled and influenced by similar geogenic sources and occur together. It is presumed that the radiological risk is mostly associated with and dominated by the uranium and thorium series and non-series 40K radionuclides in the freshwater fish species.

Integrated Assessment of Disturbed Ecosystems Using Remote Sensing Technique

Introduction. Today, there is a need for a shared vision of restoration of disturbed ecosystems, which is defined as “the process of stopping and reversing degradation, leading to improved ecosystem services and restoration of biodiversity.”Problem Statement. The assessment and restoration of disturbed ecosystems has become especially relevant for the Ukrainian society now, as warfare has caused large-scale changes in environment and both short-term and long-term consequences for ecosystems in Ukraine.Purpose. Assessment of ecosystems disturbed as a result of warfare impact by remote sensing.Materials and Methods. Multispectral satellite imagery, ground truth data and ecosystems characteristics of study area have been used. Remotely sensed data processing, geospatial modelling, and mathematical statistics have been applied.Results. A warfare impact on the ecosystems of Ukraine has been overviewed. Possibility of using remote sensing methods have been considered; their advantages and disadvantages have been generalized. A demo example of the described technique for assessing the ecosystem conditions along the E40 highway on the west of Kyiv has been shown with the use of multi-time satellite imagery of very high resolution (0.5 m on the ground) between May 2020 and March 2022. The analysis of the obtained maps allows us to assess short-term changes in land cover: a decrease in the area of water bodies, coniferous and leafy plants, an increase in the open soil area. The ecosystem conditions map of the studied area enables identifying plots of high risk.Conclusions. Integrated remote assessment of the condition of disturbed ecosystems and geospatial analysis of corresponding risks are useful tools for the territory management. Remote sensing techniques are particularly important in the context of largescale warfare. In many cases, only remote sensing techniques can provide information on the condition of ecosystems that areinaccessible or dangerous for ground-based research. Currently, the proposed approach has been elaborated and tested over other territories, different ecosystems and other data sources. Completed and tested integral geo-information technology will be relevant for the post-war recovery of the territory of Ukraine. Further research should be focused on building a pool of quantitative models for probabilistic assessment of the risk of disruption of various ecosystems under diff erent conditions, as well as on obtaining an array of statistical data to increase the reliability of the resulting maps.

Genes of photoperiod sensitivity and early maturity E1-E4: dynamics of soybean growth in different daylength conditions

Background. Morphometric indicators are crucial for evaluating the development and productivity of soybeans. They are influenced by genetic and environmental factors. The use of nearly isogenic soybean lines is a convenient model for determining the impact of early maturity genes and daylength on growth indicators. The aim of this study was to determine the influence of different daylengths and early maturity genes on soybean morphometric indicators under conditions of the temperate zone (at the latitude of Kharkiv – 50° N). Materials and Methods. The study involved nearly isogenic soybean lines of the “Clark” cultivar with varying sensitivity to daylength. The research covers the results of field experiments over three seasons using different soybean lines. After reaching the V3 stage, some plants were subjected to short-day conditions for 14 days. Morphological indicators of ten plants per experimental variant were determined: plant height, dry weight, leaf number, and leaf surface area of soybean plants. Morphometric measurements were taken on the day of the beginning of different daylength treatments and on days 7, 14 and 21. The study results are presented as the mean values of the investigated parameters (plant height, dry weight, number of leaves and leaf surface area of soybean plants). Results. It was shown that under long-day conditions, dominant alleles of the E1 and E3 genes increased the dry weight of plants, while the dominant allele E2 increased plant height. The dominant allele E4 had no significant effect on plant height and weight indicators of soybean plants. Plants with dominant alleles of genes E1-E4 under long-day conditions had smaller leaf area compared to lines with recessive alleles of these genes. Conclusions. The obtained results on the relationships between genetic and environmental factors in influencing soybean plant height, weight, and leaf area can be useful in improving soybean yield and selecting cultivars that will be productive in high latitude conditions.

Growth and Yield Performance of Tomato (Solanum Lycopersicum L.) Swayed by Mulching and Organic Fertilizers

The utilization of organic fertilizers is currently on the rise to sustain higher food quality while minimizing environmental pollution. Mulching with organic materials maintains soil physical conditions, crucial for realizing a crop’s genetic yield potential even when all other requirements are met. Hence, a field experiment was conducted to investigate the effects of mustard oil cake (MOC), poultry manure (PM) and vermicompost (V) alone and in combination with mulching (Mu) on growth and yield parameters of Tomato. Significant increases were (p ≤ 0.05) observed in plant height, leaf number, leaf area, stem girth, root length and root girth of tomato plants compared to the control (T1), where no fertilizers were applied. At 90 days after transplantation (DAT), the T9 (V8Mu0) treatment resulted in the highest plant height (142 cm) and the longest root length (25 cm) while the maximum quantity of fresh weight (154.63 g plant-1) for tomato plant was obtained from the treatment T6, which received vermicompost at 4 t ha-1 with mulching. Application of poultry manure at the rate of 8 t ha-1 without mulching (T8) resulted in a significant higher number (14 fruits plant-1) of green tomatoes. Fresh weight of green tomatoes were varied significantly (p ≤ 0.05) among the treatments with the maximum fresh weight obtained from the T₉ (128.97 g plant-1) and the minimum from T₁ (12.73 g plant-1) treatments. Nitrogen, P, K, Ca, Mg and S of green tomatoes varied significantly among the treatments. The utmost P, K, S, Ca and Mg contents (0.72, 6.26, 0.23, 0.54 and 0.31 g kg-1, respectively) of green tomatoes were recorded in the treatment T₆ (V₄Mu). Hence, the utilization of organic fertilizers, either alone or in conjunction with mulching, markedly enhanced the growth and yield of the tested vegetable, offering viable strategies for enhancing the yield potential. Dhaka Univ. J. Biol. Sci. 33(2): 53-65, 2024 (July)

Diversity and Structure of Soil Bacterial Communities in the Area of Non-ferrous Metal Plant Revealed by 16S rRNA Gene Retrieval

The goals of the study were to assess the diversity and structure of the bacterial communities within the soil depth along a gradient of heavy metal (HM) contamination and to identify indigenous bacterial species in the agricultural area of a non-ferrous metal plant KCM 2000 Group (Plovdiv) by using 16S rRNA gene retrieval. 16S rRNA gene clone libraries were constructed for nine samples, which were collected from two soil depths in June 2020. From each library, up to 100 clones were analysed and grouped into operational taxonomic units (OTUs) by restriction fragment length polymorphism (RFLP). The representatives of the OTUs were sequenced, followed by phylogenetic analysis. The results revealed that phyla Proteobacteria (11.11–71.43%) and Actinomycetota (3.57–33%) were the most abundant. Surface soils (12 phyla and 15 classes) were more diverse than subsurface ones (7 phyla and 12 classes). The lowest diversity at both phylum and class levels was calculated for the moderately contaminated soils from the two studied depths. Thirteen 16S rDNA sequences were identified to a species level, and they belonged to Proteobacteria, Actinomycetota and Firmicutes. This study highlighted that both HM contamination and soil depth caused shifts in diversity and structure of soil bacterial communities.

Assessment of Heavy Metal Contamination and Its Impact on Water Quality and Aquatic Life in Mine Surface Plant Areas

The Copper mining industry accounts for the country’s largest export earning and creates several jobs. Despite this the mines have been known to be the major contributor to the environmental pollution. It has been observed that in one province of the country, there is high presence of iron and other heavy metals in the surrounding areas. Unfortunately these heavy metals find themselves in water bodies and consequently affect the aquatic life. This study was conducted to develop suitable machine learning prediction models that estimate the impact of mine pollutants on fish production in the Kalumbila area of North-Western Province. The Machine Learning techniques employed include Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), Random Forest (RF) and K-Nearest Neighbors (KNN). These models were evaluated and, in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) with the values of 0.25 (25%) and 0.22 (22%) indicating that Random Forest appear to be the best-performing models in terms of prediction accuracy compared to other models. In addition, the RF model also achieved the highest R2 score of 0.94, indicating its ability to explain a greater proportion of the variance in the dependent variable compared to the other models. This means that RF provides a strong prediction accuracy than other models in terms of determining heavy metal contamination in impact on Water Quality and Aquatic Life in Mine Surface Plant Areas. Therefore this study shows the potential of Machine Learning models to assist decision makers in understanding the pollution levels in water bodies.

Root-promoting Biostimulant Enhances Salinity Tolerance in Wild and Cultivated Rocket Salads

AbstractRocket salads (Diplotaxis spp. and Eruca spp.) are leafy vegetables appreciated for their typical taste and nutritional value. When exposed to salt stress, these plants undergo morpho-physiological and metabolic changes. The aim of the study was to investigate the efficacy of a “root-promoting biostimulant” (Radifarm®) applied during germination (Experiment 1) and during the growth cycle (Experiment 2) on two rocket species under salt stress. Experiment 1 explored if Radifarm® can protect seed from salt stress in early-stage development. Different salt levels (0, 150 and 200 mM NaCl) were combined with different Radifarm® concentrations (0, 0.5, 1, 2.5, 5 mL L− 1). Experiment 2 investigated how Radifarm® can promote plant growth after transplantation when irrigated with saline water (0, 150, and 200 mM NaCl) until harvest. Experiment 1 showed that salt stress significantly affected the germination of rocket salads. The addition of Radifarm® did not improve the germination of D. tenuifolia grown under any salt conditions, but it was beneficial for E. sativa when the highest level of Radifarm® was applied. In Experiment 2, the application of Radifarm® significantly reduced the symptoms of salt stress in both species. In E. sativa, salt stress affected all growth parameters (plant height, leaf number and area). However, under 200 mM NaCl, plants fully recovered when Radifarm® was applied. The same recovery was observed for chlorophyll content in both species. Radifarm® also contributed to increase protein and lipid content compared to plants under salt stress. This study showed that Radifarm® was able to protect both species from salt stress.