Fruiting Branches Research Articles

Techno-economic performance analysis of biomass-to-methanol with solid oxide electrolyzer for sustainable bio-methanol production

The analysis of the technical and economic performance of an integrated biomass to methanol and solid oxide electrolysis process (BtM-SOEC) is studied to find more sustainable process of bio-methanol production. The oil palm empty fruit branch (EFB) which is abundant in Thailand is used as biomass feedstock. Modeling of the BtM-SOEC is done using Aspen Plus. For technical aspects, the production rate of oxygen and hydrogen from the SOEC can be enhanced through an appropriate adjustment of the number of cells and cell temperature. The BtM-SOEC offers higher methanol yield and overall efficiency, while consumes less energy than the conventional biomass to methanol process (BtM). The maximum methanol production rate of 0.4995 kmol h-1 derived from BtM-SOEC is achieved at a number of cells of 325 cells and a cell temperature of 700 oC, at this condition the overall efficiency is 64.79 %. The economic assessment indicates that the conventional BtM and BtM-SOEC are still not economically feasible. However, the conventional BtM is more economically feasible than the BtM-SOEC. The methanol cost of BtM-SOEC can turn out to be economically feasible when renewable electricity cost and SOEC cost decrease substantially. The methanol cost of the BtM-SOEC (620 USD ton-1) can be competitive to that of the BtM (703 USD ton-1) when the cost of input renewable electricity decreases by 80%. Consequently, this research highlights the potential of BtM-SOEC from agricultural residues for sustainable bio-methanol production in the future market condition that the cost of renewable electricity tends to continuously decrease with the technology development and increased technology adoption and the carbon policy tends to be tightened to relieve global warming.

Development of a Multiplex PCR Assay to Detect Neofusicoccum parvum and Botryosphaeria dothidea in Walnut.

In walnut orchards, frequent symptoms of cankers and dieback (fruit blight, twig and branch cankers up to tree death) are caused by different agents, in particular by Botryosphaeriaceae, primarily Neofusicoccum parvum and Botryosphaeria dothidea. This study aimed at developing a sensitive, rapid, specific and internally controlled multiplex PCR assay for the detection of these species. The ability of the multiplex PCR, with an internal inhibition control (i.e. E. coli DNA), to specifically and successfully detect members of the two targeted species was validated using 11 different isolates for each fungal target (inclusivity) and 20 tree-associated fungal species different from B. dothidea or N. parvum (exclusivity). Applicability to plant materials was further investigated and showed an absence of amplification for asymptomatic husk or twig samples while the amplification profiles of symptomatic tissues ranged from no amplification to amplification of both species, in correlation with the observed fungal contamination level. In conclusion, we developed a rapid diagnostic tool for simultaneous detection of two major fungal pathogens of walnut. Although this protocol was tailored for walnut husks and twigs, applicability to any plant sample contaminated by these pathogens can be considered.

Improving the Economic Feasibility of Small-Scale Biogas-Solid Oxide Fuel Cell Energy Systems through a Local Ugandan Biochar Production Method

A small-scale (up to 5 kWe) biogas-solid oxide fuel cell (SOFC) energy system is an envisioned system, which can be used to meet both electrical and thermal energy demand of off-grid settlements. SOFC systems are reported to be more efficient than alternatives like internal combustion engines (ICE). In addition to energy recovery, implementation of biogas-SOFC systems can enhance sanitation among these settlements. However, the capital investment costs and the operation and maintenance costs of a biogas-SOFC energy system are currently higher than the existing alternatives. From previous works, H2S removal by biochar was proposed as a potential local cost-effective alternative. This research demonstrates the techno-economic potential of locally produced biochars made from cow manure, jackfruit leaves, and jack fruit branches in rural Uganda for purifying the biogas prior to SOFC use. Results revealed that the use of biochar from cow manure and jack fruit leaves can reduce H2S to below the desired 1 ppm and substitute alternative biogas treatments like activated carbon. These experimental results were then translated to demonstrate how this biochar would improve the economic feasibility for the implementation of biogas-SOFC systems. It is likely that the operation and maintenance cost of a biogas-SOFC energy system can in the long run be reduced by over 80%. Also, the use of internal reforming as opposed to external reforming can greatly reduce the system capital cost by over 25% and hence further increase the chances of system economic feasibility. By applying the proposed cost reduction strategies coupled with subsidies such as tax reduction or exemption, the biogas-SOFC energy system could become economically competitive with the already existing technologies for off-grid electricity generation, like solar photovoltaic systems.

A Novel Fusion Perception Algorithm of Tree Branch/Trunk and Apple for Harvesting Robot Based on Improved YOLOv8s

Aiming to accurately identify apple targets and achieve segmentation and the extraction of branch and trunk areas of apple trees, providing visual guidance for a picking robot to actively adjust its posture to avoid branch trunks for obstacle avoidance fruit picking, the spindle-shaped fruit trees, which are widely planted in standard modern apple orchards, were focused on, and an algorithm for apple tree fruit detection and branch segmentation for picking robots was proposed based on an improved YOLOv8s model design. Firstly, image data of spindle-shaped fruit trees in modern apple orchards were collected, and annotations of object detection and pixel-level segmentation were conducted on the data. Training set data were then augmented to improve the generalization performance of the apple detection and branch segmentation algorithm. Secondly, the original YOLOv8s network architecture’s design was improved by embedding the SE module visual attention mechanism after the C2f module of the YOLOv8s Backbone network architecture. Finally, the dynamic snake convolution module was embedded into the Neck structure of the YOLOv8s network architecture to better extract feature information of different apple targets and tree branches. The experimental results showed that the proposed improved algorithm can effectively recognize apple targets in images and segment tree branches and trunks. For apple recognition, the precision was 99.6%, the recall was 96.8%, and the mAP value was 98.3%. The mAP value for branch and trunk segmentation was 81.6%. The proposed improved YOLOv8s algorithm design was compared with the original YOLOv8s, YOLOv8n, and YOLOv5s algorithms for the recognition of apple targets and segmentation of tree branches and trunks on test set images. The experimental results showed that compared with the other three algorithms, the proposed algorithm increased the mAP for apple recognition by 1.5%, 2.3%, and 6%, respectively. The mAP for tree branch and trunk segmentation was increased by 3.7%, 15.4%, and 24.4%, respectively. The proposed detection and segmentation algorithm for apple tree fruits, branches, and trunks is of great significance for ensuring the success rate of robot harvesting, which can provide technical support for the development of an intelligent apple harvesting robot.

Integrating RTM-GWAS and meta‑QTL data revealed genomic regions and candidate genes associated with the first fruit branch node and its height in upland cotton.

Two genomic regions associated with FFBN and HFFBN and a potential regulatory gene (GhE6) of HFFBN were identified through the integration of RTM-GWAS and meta‑QTL analyses. Abstract The first fruit branch node (FFBN) and the height of the first fruit branch node (HFFBN) are two important traits that are related to plant architecture and early maturation in upland cotton. Several studies have been conducted to elucidate the genetic basis of these traits in cotton using biparental and natural populations. In this study, by using 9,244 SNP linkage disequilibrium block (SNPLDB) loci from 315 upland cotton accessions, we carried out restricted two-stage multilocus and multiallele genome-wide association studies (RTM-GWASs) and identified promising haplotypes/alleles of the four stable and true major SNPLDB loci that were significantly associated with FFBN and HFFBN. Additionally, a meta-quantitative trait locus (MQTL) analysis was conducted on 274 original QTLs that were reported in 27 studies, and 40 MQTLs associated with FFBN and HFFBN were identified. Through the integration of the RTM-GWAS and meta‑QTL analyses, two stable and true major SNPLDBs (LDB_5_15144433 and LDB_16_37952328) that were distributed in the two MQTLs were identified. Ultimately, 142 genes in the two genomic regions were annotated, and three candidate genes associated with FFBN and HFFBN were identified in the genomic region (A05:14.64-15.64Mb) via RNA-Seq and qRT‒PCR. The results of virus-induced gene silencing (VIGS) experiments indicated that GhE6 was a key gene related to HFFBN and that GhDRM1 and GhGES were important genes associated with early flowering in upland cotton. These findings will aid in the future identification of molecular markers and genetic resources for developing elite early-maturing cultivars with ideal plant characteristics.

Combining high-throughput deep learning phenotyping and GWAS to reveal genetic variants of fruit branch angle in upland cotton

Cotton (Gossypium spp.), an economically and strategically significant crop in China, faces challenges such as rising cultivation costs and conflicts between grain and cotton cultivation. These challenges underscore the need for enhancing yields per unit area. In response, this study employs deep learning techniques, combined with high-throughput angle detection, to conduct genome-wide association studies (GWAS) on 355 upland cotton accessions, identify key SNPs and candidate genes for plant architecture by fruit branch angle (FBA) influences planting density, yield, and mechanized harvesting. A convolutional neural network (CNN)-based software was developed for rapid and accurate branch angle detection, showing high correlation with both AutoCAD and manual measurements. Significant phenotypic variation in FBA was observed across various cotton planting regions, with the Northwest Inland Region (NIR) exhibiting notably smaller angles. In total, 107 significant Single Nucleotide Polymorphisms (SNPs) were detected across 45 quantitative trait loci (QTL), and three potential candidate genes (Ghir_A11G034910, Ghir_D05G007790, and Ghir_D05G031350) were identified, providing insights into the genetic basis of FBA and presenting valuable genetic resources for cotton breeding programs.

Effect of natural ageing on germination and seedling growth of Palmyrah (Borassus flabellifer) seeds

Experiments were conducted to evaluate the seed longevity period of Palmyrah. The matured fruit branches were selected based on yellow tinge in the stylar region. After manually removing the fruit exocarp and mesocarp, the uniform size seeds were shade dried for fourteen days and stored in ambient condition. The seeds were sown in raised nursery beds containing nursery mixture of red earth, sand and farmyard manure in a ratio of 2:1:1. The experiment was conducted in a randomized block design with three replications of 50 seeds each, sown at monthly intervals up to 18 months. The germination percentage was recorded at 15 days interval till the completion of germination. One year after sowing, the results revealed that fresh seed recorded highest germination of 78.67% followed by one month of stored seed (63.33%), two months of stored seed (53.33%) and nil germination was observed beyond five months of stored seed.

Effects of different proportions of fruit tree branches on nicotine content and microbial diversity during composting of tobacco waste

Adding fruit tree branches to the compost pile in appropriate proportions is one of the methods used to address the challenge of tobacco waste recycling. However, the effects of different proportions of fruit tree branches on nicotine concentration and microbial diversity during tobacco waste composting have not been reported. In this study, a composting system with tobacco waste, cow dung, and fruit tree branches was established in a laboratory fermenter to assess the impact of adding 10%, 20%, and 30% fruit tree branches on quantity changes. In addition, the relationships between nicotine degradation, compost properties, enzyme activities, and microbial diversities were determined using biochemical assay methods and high-throughput sequencing. The results showed that adding appropriate proportions of fruit branch segments affected changes in physical and chemical properties during composting and promoted tobacco waste compost maturity. Aerobic composting effectively degraded nicotine in tobacco waste. Increased proportions of fruit branch segments led to elevations in nicotine degradation rates and enzyme activities related to lignocellulose degradation. The addition of fruit branches influenced the relative abundance and species of dominant bacteria and fungi at the phylum and genus levels. However, it did not significantly affect the relative abundance of the main bacterial genera involved in nicotine degradation. Nevertheless, it reduced the sensitivity of enzyme activity to nicotine content within heaps, increasing reliance on total nitrogen changes. The results of this study provide a theoretical basis for the utilization of tobacco waste in composting systems and indicate that fruit tree branches can enhance nicotine degradation efficiency during tobacco waste composting.

GhGASA14 regulates the flowering time of upland cotton in response to GA3.

The silencing of GhGASA14 and the identification of superior allelic variation in its coding region indicate that GhGASA14 may positively regulate flowering and the response to GA3. Gibberellic acid-stimulated Arabidopsis (GASA), a member of the gibberellin-regulated short amino acid family, has been extensively investigated in several plant species and found to be critical for plant growth and development. However, research on this topic in cotton has been limited. In this study, we identified 38 GhGASAs that were dispersed across 18 chromosomes in upland cotton, and all of these genes had a GASA core domain. Transcriptome expression patterns and qRT-PCR results revealed that GhGASA9 and GhGASA14 exhibited upregulated expression not only in the floral organs but also in the leaves of early-maturing cultivars. The two genes were functionally characterized by virus-induced gene silencing (VIGS), and the budding and flowering times after silencing the target genes were later than those of the control (TRV:00). Compared with that in the water-treated group (MOCK), the flowering period of the different fruiting branches in the GA3-treated group was more concentrated. Interestingly, allelic variation was detected in the coding sequence of GhGASA14 between early-maturing and late-maturing accessions, and the frequency of this favorable allele was greater in high-latitude cotton cultivars than in low-latitude ones. Additionally, a significant linear relationship was observed between the expression level of GhGASA14 and flowering time among the 12 upland cotton accessions. Taken together, these results indicated that GhGASA14 may positively regulate flowering time and respond to GA3. These findings could lead to the use of valuable genetic resources for breeding early-maturing cotton cultivars in the future.

A convolutional neural network (Seg-CNN) for recognition, classification, and segmentation of apple fruit branches and stems in images

This article reports the results of research studies conducted in 2023–2024 on transfer learning of Segmentation Convolutional Neural Networks (Seg-CNN) models for classification, recognition, and segmentation of branches with apple fruits and stems in images. State-of-the-art convolutional neural network architectures, i.e., YOLOv8(n,s,m,l,x)-seg, were used for a detailed segmentation of biological objects in images of varying complexity and scale at the pixel level. An image dataset collected in the field using a GoPro HERO 11 camera was marked up for transfer model training. Data augmentation was performed, producing a total of 2500 images. Image markup was performed using the polygon annotation tool. As a result, polygonal contours around objects were created, outlines of branches, apple tree fruits, and stems were outlined, and segments of objects in the images were indicated. The objects were assigned the following classes: Apple branch, Apple fruit, and Apple stem. Binary classification metrics, such as Precision and Recall, as well as Mean Average Precision (mAP), were used to evaluate the performance of the trained models in recognizing branches with apple fruits and stems in images. The YOLOv8x-seg (mAP50 0.758) and YOLOv8l-seg (mAP50 0.74) models showed high performance in terms of all metrics in recognizing branches, apple fruit, and fruit stems in images, outperforming the YOLOv8n-seg (mAP50 0.7) model due to their more complex architecture. The YOLOv8n-seg model has a faster frame processing speed (11.39 frames/s), rendering it a preferred choice for computing systems with limited resources. The results obtained confirm the prospects of using machine learning algorithms and convolutional neural networks for segmentation and pixel-by-pixel classification of branches with apple fruits and stems on RGB images for monitoring the condition of plants and determining their geometric characteristics.

Evaluation of Quality Traits in Relation to Mechanical Harvesting for Screening Excellent Materials in Gossypium barbadense L. Germplasm Resources

Sea Island cotton is renowned for its superior fiber quality. Although mechanical harvesting has the potential to significantly increase efficiency and reduce the production cost of Sea Island cotton, there is still little research in this area. In this study, we analyzed 240 Sea Island cotton germplasm resources and evaluated 19 traits related to mechanical harvesting. The coefficient of variation ranged from 5.42% to 66.96%, and the genetic diversity index spanned from 1.57 to 2.07. In most traits studied, there was a strong correlation between the height of the first fruiting branch and the defoliation rate. The 19 traits were categorized into 6 factorial groups by principal component analysis, in which the defoliation factor contributed the most (30.89%). The cluster analysis divided the 240 cotton accessions into four main groups, with the second group exhibiting favorable mechanical harvesting characteristics such as higher defoliation rate and first fruit branch height. Using stepwise regression, a model was constructed with the joint evaluation score F-value as the response variable and eight traits (X1: PH, X2: SNB, X3: SBN, X4: MBL, X5: AFBM, X7: MLIA, X8: NB, and X13: 15 d DR) as predictors: Y = −7.2 + 0.01X1 + 0.23X2 + 0.192X3 + 0.038X4 + 0.007X5 + 0.014X7 + 0.025X8 + 2.952X13. Selected materials suitable for machine harvesting, such as MoShi729, were identified. This study provides valuable theoretical insights into the mechanical harvesting of Sea Island cotton germplasm resources and identifies promising materials for targeted breeding and improvement programs.

桑葚机械振动收获参数优化与试验研究

The mechanized harvesting of mulberry is important for its production. In the process of harvesting, it is considered not only the mechanical damage of mulberry fruit but also its harvesting efficiency. It is very important to improve the vibration harvesting efficiency of mulberry. In this study, modal analysis of mulberry trees and harmonic response analysis of branches were carried out to determine the harvesting frequency of the branch's vibration and other parameters. The effects of excitation frequency and vibration position on the triaxial acceleration of the mulberry branch at different positions were analyzed by vibration test. Then the triaxial acceleration of branches at different positions was analyzed. The conditions of the mulberry fruit shedding were obtained through theoretical analysis. Through the 20-order modal analysis of mulberry, it is concluded that a better vibration effect can be achieved when the vibration frequency is controlled at 4-16 Hz. According to the harmonic response analysis, the best excitation frequencies are 5-6 Hz, 10-13 Hz, and 14-16 Hz. The harmonic response analysis of fruit branches was carried out, and the stress of fruit stalks at 5 Hz, 10 Hz, and 15 Hz were analyzed. The result shows that the maximum stress is 2.9252×107 Pa, the excitation position is the first-order branch, and the excitation frequency is 15 Hz. The frequencies obtained from modal analysis and harmonious response analysis were used to conduct experiments. When the excitation frequency was 15 Hz, the triaxial accelerations aX, aY, and aZ were 2.12 g, 4.16 g, and 3.99 g, respectively, which were more conducive to the shedding of mulberry fruits.

Comparative Study of the Agronomic Performance of Two Sesame Varieties (Sesamum indicum L.): The Case of Local Variety of Central African Origin and Pakréssaya Variety of Burkinabe Origin

Sesame (Sesamum indicum L) is a crop with high economic potential in Central African agriculture. This speculation is the subject of a booming international trade for its seeds, oil and meal. The objective of this study is to characterize the agro morphological variability of the two sesame accessions. The trial was conducted at the Bakéré Agricultural Research Station in Bossembele. The plant material used was composed of two sesame accessions from various sources (Central African Republic and Burkina Faso). The choice of land is marked by the delimitation of the plot, the staking and the surveying. The preparation of the soil was carried out in several stages. It is a plot of land of 0.75 hectares divided into three blocks of 0.25 hectares. Sowing took place on August 20, 2022. Before sowing, the sesame is mixed with the sand to respect the rate per hectare because the seeds are too fine. The different parameters measured are: stem length, number of branches per plant, number of pods per plant. The different parameters were assessed using the two-criteria analysis of variance (ANOVA) with the R software version 3.1.3. The results obtained showed that the Pakressaya variety is the earliest and gave the first flower at 31-32 days after sowing and reached 50% flowering at 33-34 days after sowing, thus reflecting the earliness in this variety. The variety (of Central African origin) is the latest and gave the first flower at 52-53 days after sowing and reached 50% flowering at 56-57 days after sowing with many more fruiting branches. The pakressaya variety proved to be productive and was selected for the rest of our project. In perspective, it is envisaged to determine the genetic diversity of the Pakréssaya accession using microsatellite markers.

Enhanced Cotton Yield and Fiber Quality by Optimizing Irrigation Amount and Frequency in Arid Areas of Northwest China

Optimizing irrigation strategies is crucial for sustaining cotton production in the face of growing water scarcity. The three-year experimental study (2020–2022) focused on the impact of varying irrigation amounts (320, 370, and 420 mm) and frequencies (4-, 8-, and 12-day intervals) on cotton growth, yield, yield components, and fiber quality in southern Xinjiang. Employing a completely randomized design with three replications, the results indicated higher irrigation amounts resulted in numerically 2.5–7.5% higher lint yields compared to those under medium and low irrigation amounts, notably significant in 2021. Boll density emerged as the primary yield component influencing yield loss due to irrigation amount, followed by seed cotton weight boll−1. Increased boll density was associated with a greater total number of fruiting sites. Additionally, the increased seed cotton weight boll−1 could be linked to an increased seed number boll−1 and a decreased boll fraction at the lower fruiting branches with lower seed cotton weight boll−1. Higher irrigation frequency improved lint yield by increasing boll density, though a significant effect was observed only in 2020. Increased irrigation amounts generally led to longer fiber lengths but lower micronaire values, while increased irrigation frequency resulted in longer, stronger fibers and reduced micronaire values. Furthermore, the highest yield stability was observed under the condition of high irrigation amount and high frequency. This study holds certain guiding significance for water resource management in cotton production in arid regions.

GENETIC VARIABILITY OF ROSELLE (HIBISCUS SABDARIFFA L.) GENOTYPES

Roselle is more than an eye-catching crop and has been used in a number of dishes, beverages, and conventional remedies for diseases for centuries. It is a source of antioxidants and anthocyanin, which acts as a free radical scavenger and inhibits lipid peroxidation. Five Roselle genotypes were evaluated in the Kharif 2 season in 2021 to assess genetic variability, association of traits, and path differentiation of different characters. A field experiment was conducted at the BIRTAN regional station farm in Noakhali, Bangladesh, in a randomized complete block design with three replications. Data were collected on twelve plant attributes. Analysis of variance indicated significant differences among the five genotypes for most of the characters studied except petiole length (cm) and fruit diameter (cm). The phenotypic coefficient of variation was higher than the corresponding genotypic coefficient of variation for all the studied traits. Phenotypic as well as genotypic coefficients of variability were high for the trait branches per plant (75.92% and 77.81%) and fruits per plant (69.33% and 77.01%), whereas they were medium for calyx per fruit and low for fruit diameter. High heritability estimates (>0.70) were recorded for plant height (cm), leaves per plant, branches per plant, fruit length (cm), calyx per fruit, fruit weight (g), and fruits per plant. On the other hand, the yield components showed medium heritability estimates (<0.70). Medium heritability coupled with a high expected genetic gain was observed for leaves per plant and fruit yield per plant. The highest genetic advance as a percent of men was also observed in branches per plant (152.59%). Fruit yield per plant was found to have a positive and highly significant correlation with branches per plant and fruits per plant, both at genotypic and phenotypic levels, whereas only at the genotypic level for leaf length and fruit diameter. Partitioning the correlation coefficients of various components direct effects on fruit yield into direct and indirect contributions revealed that fruits per plant have the maximum direct effect on fruit yield, followed by fruit weight and branches per plant at the genotypic level. High positive correlation coefficients for branches per plant were due to the indirect effects of fruits per plant. Hence, selection for the traits fruits per plant, branches per plant, and leaf length may be successful for fruit yield improvement in roselle. According to morphological traits and yield attributes the genotype RL 2 is the best among the studied genotypes.

Effect of Cutting Size in the Composting Process of Oil Palm Empty Fruit Branches (EFB) Using Active Organic Liquid Fertilizer (AOLF) as Co-Composting

The size of organic waste materials plays a pivotal role in the composting process, influencing parameters such as decomposition rate, microbial activity, aeration, and nutrient availability. Currently, the study of compost has focused on the degradatiom of organic matter. The study began by varying the sizes of oil palm EFB to 1-3, 3-5, and 5-7 cm. Subsequently, the EFB were placed into a basket composter (33 cm length x 23 cm width x 40 cm height), and active organic liquid fertilizer was added to achieve a moisture content of around 55-65%. The observation period lasted for 60 days. Throughout the composting process, the moisture content was maintained at 55-65% by adding active organic liquid fertilizer, and the composter was turned every 3 days. Analyzed parameters during the composting process included temperature, pH, volatile suspended solids, electrical conductivity, and water holding capacity. The best results were obtained with a cutting size of 3-5 cm, yielding the following values: temperature 26.75 °C, pH 7.5, volatile suspended solids 211,640 mg/L, electrical conductivity 4.05 dS/m, and water holding capacity 65%.

The Investigation of Effect of Bacteria in Biological Control of Red Spider Mite (Tetranychus spp.) and Plant Yield Parameter in Cotton (Gossypium hirsutum L.)

The purpose of this study was to assess the usability of two bacterial strains, namely Bacillus subtilis PA1 and Paenibacillus azotofixans PA2, for the biological control of red spider species, and their effects on plant quality and yield in cotton under field conditions. The experiments were conducted at three different locations with multiple replications. As a control, a commercial preparation containing Lambda-Cyhalothrin as the active ingredient was used. The obtained results from the study revealed that the application of the bioagent formulation led to a significant decrease in the density of Tetranychus spp. at different biological stages, ranging from 59.22% to 61.07%, when compared to the control group. Additionally, several important plant growth parameters showed remarkable improvements. The number of fruit branches increased by 130.20%, plant crown diameter by 88.16%, plant height by 40.15%, the number of flowers by 21.25%, the number of wood branches by 18.13%, the average number of cocoons by 126.53%, and cocoon weights by 54.65% significantly across all three trial parcels. The successful implementation of the bacterial application for pest control had a positive impact on cotton yield. Bulk cotton yield increased by 80.03%, and fiber yield increased by 82.17%. Consequently, the bacterial formulation containing these two bacteria demonstrated its potential as a biopesticide in cotton cultivation, effectively controlling pests while also playing a crucial role in enhancing productivity. Overall, the study suggests that using the bioagent formulation consisting of Bacillus subtilis PA1 and Paenibacillus azotofixans PA2 could be an effective and environmentally friendly approach for pest control in cotton farming, leading to increased productivity.

Sustainable adsorption of methylene blue onto biochar-based adsorbents derived from oil palm empty fruit branch: Performance and reusability analysis

This study examines methylene blue (MeB) adsorption by biochar-based adsorbents made from oil palm empty fruit branches. Untreated biochar (BC) and treated activated carbons 1BT and 2BT for one- and two-step KOH treatments were analyzed using FTIR, XRD, SEM-EDX, and BET to determine their physical, chemical properties and adsorption reusability. Adsorption experiments fitted pseudo-second order kinetics which fit experimental data satisfactorily. Langmuir isotherm has the best fitting data, showing monolayer adsorption, moreover three-parameter models like Redlich-Peterson, Sips, and Toth also match well, confirming its trustworthiness. BC, 1BT, and 2BT have maximal adsorption capacities of 796.17–820.12 mg/g, 943.46–969.85 mg/g, and 1123.57–1153.72 mg/g, respectively. In addition, adsorbent reusability demonstrates gradual decreases in adsorption efficiency, and consistently remained high at 46.05 %, 48.99 %, and 48.15 % over five consecutive reuse cycles for BC, 1BT, and 2BT, respectively. These findings have significant implications for the practical application as additive materials in modern landfill liner.

O. Mishchenko’s button accordion school in metaphors and realities of creative and pedagogical process

O. Mishchenko’s button accordion school in metaphors and realities of creative and pedagogical process

IMPACT OF NITROGEN FERTILIZER ON THE PRODUCTIVITY AND QUALITATIVE PARAMETERS OF ANISE (Pimpinella anisum L.)

The present study investigated the effects of nitrogen fertilization on the yield and quality characteristics of Anise (Pimpinella anisum L.). The study was conducted in the ecological conditions of Kahramanmaras from 2019 to 2021. Two different anise populations Izmir (P1) and Konya (P2) and six different nitrogen fertilizer doses (0, 30, 60, 90, 120, 150 kg ha-1) were used in the study. The experiment was set up in triplicate using a split-plot design, with the populations on the main plots and the fertilizer doses on the subplots. Considering the herbal properties of anise grown in different nitrogen dose applications; plant height was 41.71- 42.75 cm, the total number of branches (10.62-12.50 plants-1), fruit branches (4.78-5.29 plants-1) and umbrellas (8.12-9.64 plants-1) were recorded. Considering the yield and quality characteristics; seed yield the range was 350.10- 400.02 kg ha-1, 1000-seed weight 2.78-3.49 g, protein rate 15.3-17.77%, fixed oil rate 15.15-16.34% fixed oil yield 50.51-60.48 kg ha-1, essential oil rate 1.66-2.26%, and essential oil yield 5.80-8.90 L ha-1. The Konya population had higher values in terms of seed yield and quality characteristics. With the exception of plant height, which revealed the total number of branches, fruit branches, umbels, seed yield, thousand seed weight, protein ratio, fixed oil ratio, fixed oil yield, essential oil ratio, and essential oil yield, all of the studied characteristics generally showed improvement with an increase in nitrogen doses. However, a nitrogen treatment of 120 kg ha-1 produced the maximum seed production.