Large Plants Research Articles

EFISIENSI PEMANFAATAN PUPUK ANORGANIK MELALUI APLIKASI BOKASHI GAMAL PADA TANAMAN CABAI MERAH BESAR HIBRIDA (Capsicum annuum L.)

The purpose of this study was to determine the efficiency of inorganic fertilizer utilization through the use of bokashi from Gliricidia sepium on large hybrid chili plants and its effects on the physical and chemical properties of the soil as well as plant growth and productivity. This study was conducted in Pakkabba Village, North Galesong District, Takalar Regency, and soil, bokashi, and leaf tissue analysis was carried out at the Soil Laboratory of the Agricultural Assessment and Technology Center (BPTP) Maros. This research was conducted using a Randomized Block Design with 8 treatments: 100% inorganic fertilizer (ZA 650, Urea 250, SP36 500, and KCl 450 kg.ha-1); 90% inorganic fertilizer + Bokashi of Gliricidia sepium 5 t.ha-1; 80% inorganic fertilizer + Bokashi of Gliricidia sepium 10 t.ha-1; 70% inorganic fertilizer + Bokashi of Gliricidia sepium 15 t.ha-1; 60% inorganic fertilizer + Bokashi of Gliricidia sepium 20 t.ha-1; 50% inorganic fertilizer + Bokashi of Gliricidia sepium 25 t.ha-1; Without inorganic fertilizer + Bokashi Gliricidia sepium 30 t.ha-1. The results showed that the application of Gliricidia sepium bokashi did not have a significant effect on the level of soil porosity. The application of Gliricidia sepium bokashi increased the residue of N, P, K soil, C-organic, CEC, and soil pH at the end of the study. Inorganic fertilizer 70% of the recommended dose + 15 t.ha-1 Gliricidia sepium bokashi provided significantly better hybrid large chili productivity compared to other treatments, namely 22.11 t.ha-1. Gliricidia sepium bokashi 30 t.ha-1 without inorganic fertilizer produced chili productivity that was no different from the treatment of 100% inorganic fertilizer. These results indicate that the use of 30 t.ha-1 Gliricidia sepium bokashi can save 100% of inorganic fertilizer (650 kg ZA, 250 kg urea, 500 kg SP-36, and 450 kg KCl) in large chili plantings so that the use of 30 t.ha-1 Gliricidia sepium bokashi without inorganic fertilizer can be an alternative for organic cultivation of hybrid large chili plants.

A model for energy predictions and diagnostics of large-scale photovoltaic systems based on electric data and thermal imaging of the PV fields

The aim of this investigation is the development of robust models for the performance prediction and automatic monitoring of large photovoltaic systems, based on historical and real-time electric and thermal data. This issue is increasingly important due to the worldwide diffusion of large photovoltaic systems and their need to identify and predict failures and malfunctions, in order to promptly assess the convenience of maintenance actions. The present model describes the response to irradiance and temperature conditions of both modules and inverters and also it is able to predict shading conditions able to affect the energy yield. The model has been validated against real electric measurements in 6 large PV plants located in southern Italy and it demonstrated to be able to predict the real time power production within a 4.1 % error. Even more importantly, the model and its comparison with subhourly measurements over several years has demonstrated its effectiveness in detecting downtime conditions caused by inverter or string problems. Simulations and measurements revealed that missed energy production due to electrical grid coupling downtime can exceed 50 % on certain days and that the shading conditions (up to 5 % of the daily energy production) can be easily detected and separated from component problems, thus avoiding false alarms. Finally, the analysis of aerial infrared images allowed to further test the model in failure detection capability, assess the relationship between thermal anomalies and underperformance conditions and in predicting the yearly deterioration rate at the PV plants.

Flexibility assessment and aggregation of alkaline electrolyzers considering dynamic process constraints for energy management of renewable power-to-hydrogen systems

In the energy management of renewable power-to-hydrogen (ReP2H) systems, quantifying the flexibility of alkaline electrolyzers (AELs) to respond to fast load-tracking commands and maintain energy balance across various timescales is crucial. However, the flexibility of AELs is subject to electrochemical, and dynamic heat and mass transfer constraints, making them very different, both physically and mathematically, from conventional power system flexibility resources such as energy storage (ES) and electrical vehicles (EVs). Additionally, in large hydrogen plants (HPs), aggregating the flexibility of multiple AELs is necessary. Despite extensive flexibility-related research on power and integrated energy systems, work on the electrolyzers is limited. To address these gaps, this paper presents a flexibility assessment method for AELs. Considering comprehensive nonlinear dynamic process constraints, we establish a flexibility metric based on the maximal/minimal energy an AEL can provide within varying time windows. This metric is additive, facilitating the aggregation of multiple AELs within seconds. By comparing it with the energy demanded by regulatory commands, the feasibility of load-tracking control can be assessed without time-domain simulation. In cases of infeasibility, the cause and required compensation can also be interpreted. Case studies validate the proposed method, and key factors impacting the flexibility of AELs are quantitatively analyzed.

The contribution of traditional-homegardens to bird conservation in human-modified landscapes

AbstractTraditional-homegardens are important for the food security, economy, and culture of rural communities, but also contributing to biodiversity conservation. The objective of this study was to evaluate the role of traditional-homegardens as a refuge for birds, how the birds used them, and which of their attributes were associated with the frequency of bird visits. We compared the percentage of visits among groups of birds by habitat preference. Also, we compared the frequency of visits to different vegetation strata and the use that birds made within traditional-homegardens (forage, perching or nesting). Finally, we analyzed the relationship between the number of visits and some characteristics of the traditional-homegardens (size area, richness of large plants and distance to the nearest forest fragment). Birds visited different vegetation stratum of traditional-homegardens to perch, to forage, and even to nest. In general, we found that larger traditional-homegardens area increased the number of bird visits, while distance to the native forest fragments and the species richness of large plants did not have significant effects. Insectivores and frugivores had a similar pattern to the general; to the granivores, the distance to the forest fragment had a positive effect on the number of visits; to the omnivores, the species richness of large plants had negative effect, to the nectarivores, none of the variables had a significant effect. Overall, this study sheds light on the significance of traditional-homegardens not only for human communities but also for biodiversity conservation by providing valuable habitats for a variety of bird species.

An efficient and generalisable approach for mapping paddy rice fields based on their unique spectra during the transplanting period leveraging the CIE colour space

As one of the most important staple foods globally, rice sustains nearly half of the world's population. Accurate and timely paddy rice mapping is, thus, essential for rice-related policy-making to ensure food security in the context of anthropogenic, environmental and climate changes. However, paddy rice mapping remains a challenging task since it usually has similar spectral characteristics to other land covers. In this research, for the first time, an entirely new approach, called RiceTColour, was proposed for mapping rice fields within the Commission Internationale de l'Eclairage (CIE) colour space based on their unique spectra during the rice transplanting period as observed in remotely sensed imagery. We demonstrate that transplanted rice fields, representing a mixture of soil, water and rice seedlings, consistently exhibit relatively low spectral values in both SWIR and NIR bands across various geographical locations, leading to their unique dark green colours in the false-colour image composed of SWIR, NIR and Red bands. Based upon this, we transformed these three spectral bands into the CIE colour space where paddy rice was found to be readily and completely separated from the other land covers. Straightforward, but specific classification criteria were established within the CIE colour space to differentiate paddy rice from the other land covers. The proposed RiceTColour, thus, represents a new approach for paddy rice identification, that is mapping paddy rice using the CIE colour space based upon the previous underexplored remotely sensed spectra of paddy fields during the transplanting season. The effectiveness of the proposed method was investigated over five rice-planting regions distributed across different geographical regions, characterised by different climates, rice cropping intensities, irrigation schemes and cultural practices. Specifically, the mapping criteria established in a training site (S1) were directly generalised to the other four sites (S2 to S5) for paddy rice mapping. Experimental results demonstrated that the RiceTColour method consistently achieved the most accurate and balanced classifications across all five sites compared with four benchmark comparators: a SAR-based method, an index-based method and two supervised classifier-based methods. In particular, the RiceTColour method performed relatively stable, producing an overall accuracy exceeding 95% in the training site (S1) as well as the four generalised sites (S2 to S5), which is an encouraging result. Such efficient yet stable rice mapping results across various rice-planting regions suggest a very strong generalisation capability of the proposed RiceTColour method. In consideration of the relatively large planting area of paddy rice fields globally, the proposed parameter-free, efficient, and generalisable RiceTColour method, thus, holds great potential for widespread application in various rice-planting areas worldwide.

Carbon emission trading, carbon efficiency, and the Porter hypothesis: Plant-level evidence from China

Focusing on large thermal power plants in China, we examine the causal effect of carbon emission trading scheme (CETS) on their carbon emission efficiency. Using the staggered installation of CETS pilots as a natural experiment, we show that carbon emission trading significantly improves power plants’ carbon efficiency. Specifically, the CETS leads to a 6.9 % increase in carbon efficiency. The carbon efficiency growth effects are stronger for plants that are not state-owned, large in scale, or plants located in regions with high level of marketization. Moreover, the improvement in carbon efficiency mainly comes from the reduction in carbon emission, not the improvement in power generation level. The mechanism analysis indicates that the implementation of CETS increases the number of granted patents by as much as 23 %, which provides supporting evidence for the Porter hypothesis.

Improving biogas production with application of trimetallic nanoparticle using response surface methods

The potential of trimetallic nanoparticles (TMNPs) to enhance biogas production through microbe-to-microbe interactions and boost biogas yield is evident. This present study employed the central composite design (CCD) of response surface methods (RSM) to determine the optimal conditions of iron-cobalt-zinc TMNPs influenced anaerobic digestion for higher biogas yield. The impact of initial pH (6.6–7.4), TMNPs concentration (0–30 mg L−1), temperature (25-45 °C), and hydraulic retention time (HRT) (0-4 days) were modelled for improved biogas production. The results indicated that the linear model terms of pH and TMNPs concentration, and quadratic model terms of temperature and HRT, significantly affect the biogas production. Linear model terms of TMNPs, temperature, pH, and HRT have significant interactive effects and the numerical analysis identified the best conditions for the evaluated parameters. Ideal anaerobic process settings generated a maximum cumulative biogas production of 3700 mL−1POME than blank (2000 mL−1), corresponding to an 85 % yield. Optimizing the initial pH, TMNPs concentration, temperature, and HRT can significantly improve biogas yield and could be helpful for developing more efficient AD processes at large volume and commercial biogas plants. Promoting TMNPs as catalysts positively improves an AD process towards sustainable biogas production.

Techno-economic assessment of the Dethridge waterwheel under sluice gates in a novel design for pico hydropower generation

The world is increasingly shifting toward low-head hydropower as a sustainable form of renewable energy in response to the negative socioeconomic impacts of large hydroelectric plants. In this context, the article presents a novel design involving retrofitting the gates of existing dam structures with Dethridge waterwheel technology. This innovative solution installs the wheel under the gate to harvest the untapped potential energy resulting from the head difference at these already-existing facilities while simultaneously reducing the need for costly civil work and preventing new installations in freshwater systems. The El-Reah El-Tawfiqy barrage in Egypt served as the model case study for evaluating the implementation of the proposed design. According to the results, the plant's levelized cost is 29 USD/MWh, less expensive than traditional hydropower projects and achieves grid parity. With an estimated 140 MWh of electricity produced annually, the project is expected to cut around 1460 tons of CO2 equivalent over its 25-year lifespan. This study includes several novelties, including modifying hydraulic structure gates for pico power generation. Additionally, a thorough numerical analysis was performed to estimate the output power instead of relying on theoretical approaches for the economic viability study. These results can guide policymakers and stakeholders in implementing affordable and sustainable renewable energy solutions.

Deep Edge-Based Fault Detection for Solar Panels.

Solar panels may suffer from faults, which could yield high temperature and significantly degrade their power generation. To detect faults of solar panels in large photovoltaic plants, drones with infrared cameras have been implemented. Drones may capture a huge number of infrared images. It is not realistic to manually analyze such a huge number of infrared images. To solve this problem, we develop a Deep Edge-Based Fault Detection (DEBFD) method, which applies convolutional neural networks (CNNs) for edge detection and object detection according to the captured infrared images. Particularly, a machine learning-based contour filter is designed to eliminate incorrect background contours. Then faults of solar panels are detected. Based on these fault detection results, solar panels can be classified into two classes, i.e., normal and faulty ones (i.e., macro ones). We collected 2060 images in multiple scenes and achieved a high macro F1 score. Our method achieved a frame rate of 28 fps over infrared images of solar panels on an NVIDIA GeForce RTX 2080 Ti GPU.

A Real-Time Intelligent Valve Monitoring Approach through Cameras Based on Computer Vision Methods.

Abnormal valve positions can lead to fluctuations in the process industry, potentially triggering serious accidents. For processes that frequently require operational switching, such as green chemical processes based on renewable energy or biotechnological fermentation processes, this issue becomes even more severe. Despite this risk, many plants still rely on manual inspections to check valve status. The widespread use of cameras in large plants now makes it feasible to monitor valve positions through computer vision technology. This paper proposes a novel real-time valve monitoring approach based on computer vision to detect abnormalities in valve positions. Utilizing an improved network architecture based on YOLO V8, the method performs valve detection and feature recognition. To address the challenge of small, relatively fixed-position valves in the images, a coord attention module is introduced, embedding position information into the feature channels and enhancing the accuracy of valve rotation feature extraction. The valve position is then calculated using a rotation algorithm with the valve's center point and bounding box coordinates, triggering an alarm for valves that exceed a pre-set threshold. The accuracy and generalization ability of the proposed approach are evaluated through experiments on three different types of valves in two industrial scenarios. The results demonstrate that the method meets the accuracy and robustness standards required for real-time valve monitoring in industrial applications.

Forgotten project of a private agricultural plantation in the Khanate of Khiva, Uzbekistan

ABSTRACT This article re-evaluates a failed large irrigation enterprise and agricultural plantation in the Khanate of Khiva, an Imperial Russian protectorate in contemporary Uzbekistan, during the 1910s. Co-initiated by Russian entrepreneurs and the Khivan government, this project has been considered one of several lucrative, speculative ventures by Russian capitalists exploiting imperial privileges. This article demonstrates that the entrepreneurs involved in the dacha Lawzan enterprise possessed adequate capital and technology for this large-scale project. However, the project was hampered by legal restrictions put in place by the imperial government and by lingering conflict with nomads in the Khanate and ultimately failed. The case of dacha Lawzan exemplifies government–entrepreneur tension in the colonial territories of Imperial Russia, which impeded the economic development projects initiated by local governments to attract private capital to irrigation and cotton cultivation.

Design and Experiment of Planting Mechanism of Automatic Transplanter for Densely Planted Vegetables

The planting mechanism of existing transplanters cannot meet the agronomic requirements of planting densely planted vegetables with multiple rows, small plant spacing, and small row spacing. In order to solve this current problem, an eight-row duckbill planting mechanism driven by a motor and a cylinder was designed. According to the agronomic guidance and mechanism design requirements for transplanting densely planted vegetable seedlings, this paper analyzes the working principle of the planting mechanism, establishes its kinematic theoretical model, and determines the structural parameters of the driving device and opening and closing device in the planting mechanism. Aimed at the problem of large planting resistance when eight-row planting end effectors of the planting mechanism are planting at the same time, based on the existing research, three duckbill planting end effectors with double incisions, four incisions, and conical structures were selected, and the planting process was simulated using an EDEM 2022-RecurDyn 2024 coupling simulation. The single-factor analysis method and the interactive factor Box–Behnken response surface analysis method were used. It is concluded that the duckbill end effector with double incisions has the smallest planting resistance, and the rationality of the mechanism design is preliminarily verified. A planting resistance measurement platform was built based on the STM32 platform and HX711 module, and a planting resistance test of the duckbill planting end effector was carried out to verify the correctness of the planting mechanism simulation results. The planting mechanism performance test was carried out, and the test results showed that the planting qualification rate of the prototype reached 96.62%, the planting spacing variation coefficient was only 3.55%, and the planting efficiency reached about 7135 plants/h, which met the agronomic requirements of small plant spacing and small row spacing for densely planted vegetables and verified the feasibility and practicality of the planting mechanism.

ABOUT SOME PROBLEMS OF THE ELECTRIC ENERGY SECTOR OF GEORGIA

In the article - "About some problems of the electric energy sector of Georgia" - the issue of the country's electricity production potential and how it is used is discussed. The article mentions that out of all the energy resources, Georgia has the most electrical energy resources. These are hydropower (water resources), wind and solar resources. A retrospective analysis of both total and individual production and consumption of electricity in the period 1990-2023 concluded that a 47.5% increase in individual consumption was caused by the catastrophic population decrease in Georgia during the same period. The article also mentions that the average consumption of electricity in Georgia is half of the corresponding indicator of Germany, the USA - Mesa-Med, and Norway - one-sixth. The electricity balance of Georgia is negative. A significant part of electricity is imported from Russia and Azerbaijan. Among the problems faced by the electrical energy system, the article discusses the possibility of causing danger by depending on external sources of electricity, giving preference to the construction of large hydroelectric power plants (the construction of which destroys wild nature) and less attention to the study of the issue of regional production and consumption of electricity. The article provides conceptual solutions to each of these problems. Keywords: electric energy; hydropower; wind and solar energy; large and small hydropower plants; Electrical energy balance.

A phylogenomic approach to disentangling the evolution of the large and diverse daisy tribe Anthemideae (Asteraceae)

AbstractThe daisy tribe Anthemideae Cass. is one of the largest and most diverse tribes within Asteraceae. We analyzed a data set including 61 out of 111 Anthemideae genera, and all but four of the 19 currently recognized subtribes (Inulantherinae, Lapidophorinae, Lonadinae, and Vogtiinae) using a targeted high‐throughput sequencing approach, the first focused on the tribe. We followed different phylogenomic approaches, using nuclear and plastid data, as well as additional analytical methods to estimate divergence times and diversification rates, to unravel the evolutionary history and classification of this tribe. Our results reinforce the phylogenetic backbone of the Anthemideae advanced in previous studies and further reveal the possible occurrence of ancient hybridization events, plastid capture, and/or incomplete lineage sorting (ILS), suggesting that complex evolutionary processes have played an important role in the evolution of this tribe. The results also support the merging of subtribe Physmasperminae into Athanasiinae and subtribe Matricariinae into Anthemidinae and clarify previously unresolved relationships. Furthermore, the study provides additional insights into the biogeographic patterns within the tribe by identifying three main groups: the Southern African Grade, the Asian Clade, and the circum‐Mediterranean Clade. These groups partially coincide with previously identified ones. Overall, this research provides a more detailed understanding of the Anthemideae tribe and improves its classification. The study also emphasizes the importance of phylogenomic approaches for deciphering the evolutionary dynamics of large and diverse plant lineages.

Prediksi Jumlah Produksi Kelapa Sawit di Indonesia Menggunakan Algoritma Backpropagation

Indonesia is a country that has advantages in the agricultural sector which has the largest plantation and agricultural areas in ASEAN, one of which is oil palm plantations. Indonesia is one of the largest crude palm oil (CPO) business players in the world. More and more palm oil mills and oil palm land are being converted to oil palm cultivation, because oil palm plantations are more beneficial for farmers and palm oil processors. Palm oil plantations are still trying in several ways to maintain stable market demand, one of which is by increasing palm oil production, because palm oil is the main source of other product derivatives. Palm oil production fluctuates every month, but the ups and downs are caused by many factors, namely climate, rainfall, soil fertility, selling prices, and others. Reduced production has a direct impact on the income of farmers and workers in the sector, which in turn can cause economic instability. Actions are needed to ensure the continuity of this industry, one of which is by making predictions. One prediction technique is the Backpropagation artificial neural network. The prediction model can provide very accurate estimates of palm oil production at the provincial level. By analyzing historical data, this research can identify patterns that can help predict future palm oil production. The urgency lies in the strategic role of palm oil in the Indonesian economy.

From A Supervisor To A Plantation Owner

The looming financial crisis threatened to transform Mr. Rostam's thriving agribusiness into a sinking ship, casting a shadow of uncertainty over his entrepreneurial dreams. The once-promising future now appeared murky and fraught with challenges, leaving him to navigate the business desperately to keep his venture afloat. It is a test of resilience, innovation, and unwavering determination as he grapples with the harsh realities of an uncertain market. With limited resources, he coped with more of the challenges of a struggling business. The road ahead seemed daunting, with uncertainty lurking at every turn. Mr. Rostam pondered over the situation, feeling the weight of responsibility on his shoulders; he muttered, "The business has reached the critical point, and failure was not an option”. Mr. Rostam has to look for the right opportunity and decide about taking the next big leap of faith to start his next agriculture business venture. Terengganu Agrotech Development Corporation Sdn. Bhd. (TADC) looking for proposals to develop a large palm oil plantation farm in Terengganu state. Mr. Rostam has to develop the right plan with a partner that can invest in the proposed corporate farming project.

PEMBERIAN PUPUK HAYATI BIONEENSIS DAN MEDIA ORGANIK TERHADAP PERTUMBUHAN DAN PRODUKSI CABAI MERAH BESAR (Capsicum annuum L.)

This research was conducted from June 2022 to September 2022 at the Green House, Faculty of Agriculture, Universitas Muslim Indonesia. This study aims to determine the application of biofertilizer bioneensis and planting media to the growth and production of large red chili (Capsicum annuum L.), to determine the interaction between biofertilizer bioneensis and organic media on the growth and production of large red chili (Capsicum annuum L.). This study used a factorial randomized block design (RAK) with 2 (two) factors, namely the first factor, namely: Bio-fertilizer bioneensis with 3 levels. The second factor is: planting media with 3 levels. There were 9 treatment combinations, each treatment was repeated 3 times to obtain 27 experimental units. Observational data were analyzed using the analysis of variance (ANOVA) and continued with the Honest Significant Difference Test (BNJ). The parameters observed were plant height, number of branches, flowering age, number of fruit, fruit weight and fruit production. The results showed that the use of biofertilizer bioneensis alone had no significant effect on all observation parameters. productive branches, number of fruit, fruit weight, and amount of production The interaction of the application of biofertilizer bioneensis and organic media on large red chili plants did not significantly affect all observation parameters.

The Future of Microreactors: Technological Advantages, Economic Challenges, and Innovative Licensing Solutions with Blockchain

This study details the unique advantages and challenges associated with microreactors. Microreactors offer rapid installation and flexible application capabilities, meeting energy needs in remote and inaccessible areas. Unlike large nuclear power plants, they can be set up and start generating energy within a few days, resulting in significant time and cost savings. Their small size and modular design reduce capital and operational costs while enhancing economic competitiveness. However, some technical and regulatory challenges persist for the widespread adoption of microreactors. Licensing processes designed for large nuclear power plants may delay the widespread adoption of microreactors. Blockchain technology can play a crucial role in overcoming these challenges by providing transparency and reliability in the licensing processes. The operational settings of microreactors should be carefully considered, and regulatory authorities must be effectively designated. Collaboration and coordination are vital in this process. Consequently, the flexibility and innovative solutions offered by microreactors highlight the importance of future research to examine the optimal conditions for their use.

Occurrence and analysis of microplastics in municipal wastewater, Poland

Microplastics are a growing environmental threat and wastewater treatment plants have been identified as significant conduits for these pollutants. This study addresses microplastic loading in the influent of a large urban wastewater treatment plant, presenting a detailed analysis of their prevalence and characteristics. Our findings reveal a concentration of 4.09 microplastic particles per litre in the tributary. We performed a detailed statistical comparison of the microplastic particles, categorising them by shape, size, colour, and polymer type. Using Fourier transform total reflectance infrared spectroscopy, we identified 13 different polymer types, with polyethylene terephthalate, rubber, and polyethylene predominating. The analysis showed that textile fibres, mainly from clothing, are the most prevalent form of microplastic in wastewater, followed by fragments from the breakdown of larger plastic objects and films. This research highlights the critical need for strategic interventions to mitigate microplastic pollution at municipal sources.

Aerobic Composting of Organic Waste, Alternative and an Efficient Solid Waste Management Solution

The process of composting which involves the treatment of organic wastes to obtain a stable clean product, has become an increasingly desirable choice, at any scale from home to large waste treatment plants. Composting serves as an alternative to landfilling for managing biodegradable waste while also increasing or preserving soil organic matter, decreasing solid waste, and reducing disposal costs. The compost product improves the condition of the soil, reduces erosion, and helps reduce plant diseases without having adverse impacts on the environment. This study aims to manufacture high-quality compost as a solid waste management method by converting organic waste into a useful resource for the community in a financially and ecologically sustainable manner. We investigated the potential of aerobic composting by controlling the operation process parameters, including monitoring the pH value, temperature, electrical conductivity (EC), carbon-to-nitrogen ratio (C/N), and moisture content during the composting. We studied the physiochemical and biological changes of composting using a 60-liter bioreactor. The composting process determined an average pH value between 6.9 and 7.8, and it revealed a decrease in TOC from 26.18 to 22.19. Additionally, compost process monitoring indicated a maximum temperature rise of 69 °C over the first three days, and then a decrease after 20 days of air temperature. Total nitrogen in the NH4+/NO3-ratio nitrification decreased to less than 1.4, and the compost in the C/N ratio decreased from 20.75 to 10.035 and setting quality criteria by comparing the final product quality produced through the in-vessel composting.