AgriEngineering最新文献

{"title":"Bioactive Compound Extraction of Hemp (Cannabis sativa L.) Leaves through Response Surface Methodology Optimization","authors":"Theodoros G. Chatzimitakos, V. Athanasiadis, Ioannis Makrygiannis, Dimitris Kalompatsios, Eleni Bozinou, S. Lalas","doi":"10.3390/agriengineering6020075","DOIUrl":"https://doi.org/10.3390/agriengineering6020075","url":null,"abstract":"Hemp, commonly known as Cannabis sativa L., is a medicinal plant species of the Cannabaceae family. For the efficient extraction of C. sativa leaves using the conventional stirring process with water as the solvent, three crucial extraction parameters (i.e., extraction duration, liquid–solid ratio, and temperature) were investigated through the response surface methodology (RSM). The concentrations of the extracted bioactive compounds (polyphenols, ascorbic acid, and carotenoids) showed significant variations in the RSM design points, suggesting the importance of finding the optimal extraction conditions in which liquid–solid ratio and extraction temperature were found to have the highest impact. Further analysis was conducted on the optimal extract employing several assays to determine their polyphenol content, total carotenoid content, color evaluation, anti-inflammatory activity, and antioxidant capacity through FRAP, DPPH, and H2O2 assays. Α low extraction time (30 min) at 50 °C and a high liquid–solid ratio (50:1) were required for the highest possible yield of polyphenols. The total polyphenol content was determined to be 9.76 mg gallic acid equivalents/g under optimum conditions, with pelargonin being the most abundant polyphenol (1.51 mg/g) in C. sativa extracts. Ascorbic acid was measured at 282.23 μg/g and total carotenoids at 356.98 μg/g. Correlation analyses revealed that anti-inflammatory activity was negatively correlated with specific polyphenols. As determined by DPPH (27.43 μmol ascorbic acid equivalents (AAE)/g), FRAP (49.79 μmol AAE/g), and H2O2 (230.95 μmol AAE/g) assays, the optimized aqueous extract showed a high antioxidant capacity. Furthermore, it demonstrated considerable anti-inflammatory activity at 17.89%, with the potential to increase to 75.12% under particular extraction conditions. Given the high added-value of the aqueous extracts, the results of this study highlight the potential utility of C. sativa leaves as a source of health-improving antioxidant compounds in the pharmaceutical and food industries.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Furrow Opener and Disc Coulter Configurations on Seeding Performance under Different Residue Cover Densities","authors":"D. Karayel, Eglė Jotautienė, E. Šarauskis","doi":"10.3390/agriengineering6020073","DOIUrl":"https://doi.org/10.3390/agriengineering6020073","url":null,"abstract":"The performance of the no-till seeder is one of the most important factors that affect the success of the no-tillage. Striking the right balance between furrow opener design and residue cover is essential for optimizing seeding conditions and ensuring sustainable agricultural practices that promote both soil conservation and high-yield crop production. This study investigates the impact of residue cover on no-tillage maize seeding after wheat harvest, focusing on plant spacing, seeding depth, mean emergence time, and percent emergence. Trials with hoe-type and double-disc-type furrow openers, accompanied by plain- or ripple-disc-type coulters, were conducted in Antalya, Turkey. The results indicate that residue cover had no significant effect on mean plant spacing, but a higher residue cover increased spacing variation. The seeding depth in hoe-type furrow opener trials remained consistent, while double-disc-type furrow openers showed lower depths with 80% and 90% residue covers. The percentage of plant emergence and mean emergence time decreased as the residue cover increased in double-disc-type furrow opener trials. At 90% residue cover, PE decreased to 60%. The impact of disc coulters on hoe-type furrow openers was limited, but they increased seeding depth and MET in double-disc-type furrow openers. These findings can help optimize residue management for improved efficiency in no-till farming systems.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140995258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cultivation of Spirulina maxima in a Medium Supplemented with Leachate for the Production of Biocompounds: Phycocyanin, Carbohydrates, and Biochar","authors":"Wallyson Ribeiro dos Santos, Matheus Lopes da Silva, G. Tagliaferro, A. L. G. Ferreira, Daniela Helena Pelegrine Guimarães","doi":"10.3390/agriengineering6020074","DOIUrl":"https://doi.org/10.3390/agriengineering6020074","url":null,"abstract":"Cyanobacteria are microorganisms that grow rapidly in an aquatic medium, showing the capacity of accumulations of biocompounds subsequently converted into value-added biocompounds. The cyanobacterium Spirulina maxima can produce pigments besides accumulating significant amounts of carbohydrates and proteins. An alternative to reducing biomass production costs at an industrial scale is the use of landfill leachate in the growing medium, as well as the mitigation of this pollutant. The objective of this work was to cultivate Spirulina maxima in a medium supplemented with leachate, using the design of experiments to evaluate the effects of leachate concentration (% v/v), light source, and light intensity in an airlift photobioreactor, analyzing them as a response to the productivity of biomass, phycocyanin, carbohydrates, and biochar. The highest values of productivity (mg L−1d−1) were 97.44 ± 3.20, 12.82 ± 0.38, 6.19 ± 1.54, and 34.79 ± 3.62 for biomass, carbohydrates, phycocyanin, and biochar, respectively, adjusted for experiment 2 with the factors of leachate concentration (5.0% v/v), light source (tubular LED), and luminosity (54 µmol m−2 s−1), respectively. The use of leachate as a substitute for macronutrients in Zarrouk’s medium for the cultivation of Spirulina maxima is a viable alternative in the production of biocompounds as long as it is used at an appropriate level.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nighttime Harvesting of OrBot (Orchard RoBot)","authors":"Jakob Waltman, Ethan Buchanan, D. Bulanon","doi":"10.3390/agriengineering6020072","DOIUrl":"https://doi.org/10.3390/agriengineering6020072","url":null,"abstract":"The Robotics Vision Lab of Northwest Nazarene University has developed the Orchard Robot (OrBot), which was designed for harvesting fruits. OrBot is composed of a machine vision system to locate fruits on the tree, a robotic manipulator to approach the target fruit, and a gripper to remove the target fruit. Field trials conducted at commercial orchards for apples and peaches during the harvesting season of 2021 yielded a harvesting success rate of about 85% and had an average harvesting cycle time of 12 s. Building upon this success, the goal of this study is to evaluate the performance of OrBot during nighttime harvesting. The idea is to have OrBot harvest at night, and then human pickers continue the harvesting operation during the day. This human and robot collaboration will leverage the labor shortage issue with a relatively slower robot working at night. The specific objectives are to determine the artificial lighting parameters suitable for nighttime harvesting and to evaluate the harvesting viability of OrBot during the night. LED lighting was selected as the source for artificial illumination with a color temperature of 5600 K and 10% intensity. This combination resulted in images with the lowest noise. OrBot was tested in a commercial orchard using twenty Pink Lady apple trees. Results showed an increased success rate during the night, with OrBot gaining 94% compared to 88% during the daytime operations.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140998171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying Paraconsistent Annotated Logic Eτ for Optimizing Broiler Housing Conditions","authors":"Angel Antonio Gonzalez Martinez, I. de Alencar Nääs, Thayla Morandi Ridolfi de Carvalho-Curi, J. Abe","doi":"10.3390/agriengineering6020071","DOIUrl":"https://doi.org/10.3390/agriengineering6020071","url":null,"abstract":"Broilers are particularly sensitive to heat stress, which can impair growth, and lower conversion efficiency and survival rates. Under a climate change scenario, maintaining optimal thermal conditions within broiler houses becomes more complex and energy-intensive. Climate change can worsen air quality issues inside broiler houses by increasing the concentration of harmful gases, and proper mechanical ventilation systems are essential for diluting and removing these gases. The present study aimed to develop and validate a model for the ideal broiler housing strategy by applying the Paraconsistent Annotated Evidential Logic Eτ. A database from four broiler houses in a commercial farm, rearing 157,700 birds from the 1st to the 42nd day of growth, was used in the research. All environmental data were recorded weekly inside the houses, and on day 42, flock mortality, overall feed-to-gain ratio, and body weight were calculated and registered. The Cohen’s Kappa statistics for each environmental parameter classification compared to the paraconsistent classification. Results indicated that temperature shows good agreement, relative humidity shows slight agreement, air velocity presents a good agreement, CO2 concentration has a slight agreement, and NH3 concentration is classified by slight agreement. The environmental and productivity variables as a function of the broiler age using the extreme True paraconsistent state indicate the model validation. The paraconsistent analysis presented the ideal scenario for broilers’ growth, maintaining the environmental variables level within a particular threshold and providing greater profit to broiler farmers.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":"27 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141010660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Convolutional Neural Networks, XGBoost, and Hybrid CNN-XGBoost for Precise Red Tilapia (Oreochromis niloticus Linn.) Weight Estimation in River Cage Culture with Aerial Imagery","authors":"W. Taparhudee, Roongparit Jongjaraunsuk, S. Nimitkul, Pimlapat Suwannasing, Wisit Mathurossuwan","doi":"10.3390/agriengineering6020070","DOIUrl":"https://doi.org/10.3390/agriengineering6020070","url":null,"abstract":"Accurate feeding management in aquaculture relies on assessing the average weight of aquatic animals during their growth stages. The traditional method involves using a labor-intensive approach and may impact the well-being of fish. The current research focuses on a unique way of estimating red tilapia’s weight in cage culture via a river, which employs unmanned aerial vehicle (UAV) and deep learning techniques. The described approach includes taking pictures by means of a UAV and then applying deep learning and machine learning algorithms to them, such as convolutional neural networks (CNNs), extreme gradient boosting (XGBoost), and a Hybrid CNN-XGBoost model. The results showed that the CNN model achieved its accuracy peak after 60 epochs, showing accuracy, precision, recall, and F1 score values of 0.748 ± 0.019, 0.750 ± 0.019, 0.740 ± 0.014, and 0.740 ± 0.019, respectively. The XGBoost reached its accuracy peak with 45 n_estimators, recording values of approximately 0.560 ± 0.000 for accuracy and 0.550 ± 0.000 for precision, recall, and F1. Regarding the Hybrid CNN-XGBoost model, it demonstrated its prediction accuracy using both 45 epochs and n_estimators. The accuracy value was around 0.760 ± 0.019, precision was 0.762 ± 0.019, recall was 0.754 ± 0.019, and F1 was 0.752 ± 0.019. The Hybrid CNN-XGBoost model demonstrated the highest accuracy compared to using standalone CNN and XGBoost models and could reduce the time required for weight estimation by around 11.81% compared to using the standalone CNN. Although the testing results may be lower than those from previous laboratory studies, this discrepancy is attributed to the real-world testing conditions in aquaculture settings, which involve uncontrollable factors. To enhance accuracy, we recommend increasing the sample size of images and extending the data collection period to cover one year. This approach allows for a comprehensive understanding of the seasonal effects on evaluation outcomes.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141019879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sugarcane Water Productivity for Bioethanol, Sugar and Biomass under Deficit Irrigation","authors":"F. S. Barbosa, Rubens Duarte Coelho, T. H. Barros, J. V. Lizcano, E. F. Fraga Júnior, L. C. Santos, D.P.V. Leal, N. L. Ribeiro, J. Costa","doi":"10.3390/agriengineering6020064","DOIUrl":"https://doi.org/10.3390/agriengineering6020064","url":null,"abstract":"Knowledge of how certain crops respond to water stress is one of the prerequisites for choosing the best variety and best management practices to maximize crop water productivity (WPc). The selection of a more efficient protocol for managing irrigation depths throughout the cultivation cycle and in the maturation process at the end of the growth period for each sugarcane variety can maximize bioethanol productivity and WPc for bioethanol, sugar and biomass, in addition to the total energy captured by the sugarcane canopy in the form of dry biomass. This study aimed to evaluate the effect of four irrigation depths and four water deficit intensities on the maturation phase for eight sugarcane varieties under drip irrigation, analyzing the responses related to WPc for bioethanol, sugar and biomass. These experiments were conducted at the University of São Paulo. The plots were positioned in three randomized blocks, and the treatments were distributed in a factorial scheme (4 × 8 × 4). The treatments involved eight commercial varieties of sugarcane and included four water replacement levels and four water deficits of increasing intensity in the final phase of the crop season. It was found that for each variety of sugarcane, there was an optimal combination of irrigation management strategies throughout the cycle and during the maturation process. The RB966928 variety resulted in the best industrial bioethanol yield (68.7 L·Mg−1), WPc for bioethanol (0.97 L·m−3) and WPc for sugar (1.71 kg·m−3). The energy of the aerial parts partitioned as sugar had a direct positive correlation with the availability of water in the soil for all varieties. The RB931011 variety showed the greatest potential for converting water into shoots with an energy of 1.58 GJ·ha−1·mm−1, while the NCo376 variety had the lowest potential at 1.32 GJ·ha−1·mm−1. The productivity of first-generation bioethanol had the highest values per unit of planted area for the greatest water volumes applied and transpired by each variety; this justifies keeping soil moisture at field capacity until harvesting time only for WR100 water replacement level with a maximum ethanol potential of 13.27 m3·ha−1.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":"12 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140671205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergetic Use of Sentinel-1 and Sentinel-2 Data for Wheat-Crop Height Monitoring Using Machine Learning","authors":"Lwandile Nduku, C. Munghemezulu, Zinhle Mashaba-Munghemezulu, Phathutshedzo Eugene Ratshiedana, Sipho Sibanda, J. Chirima","doi":"10.3390/agriengineering6020063","DOIUrl":"https://doi.org/10.3390/agriengineering6020063","url":null,"abstract":"Monitoring crop height during different growth stages provides farmers with valuable information important for managing and improving expected yields. The use of synthetic aperture radar Sentinel-1 (S-1) and Optical Sentinel-2 (S-2) satellites provides useful datasets that can assist in monitoring crop development. However, studies exploring synergetic use of SAR S-1 and optical S-2 satellite data for monitoring crop biophysical parameters are limited. We utilized a time-series of monthly S-1 satellite data independently and then used S-1 and S-2 satellite data synergistically to model wheat-crop height in this study. The polarization backscatter bands, S-1 polarization indices, and S-2 spectral indices were computed from the datasets. Optimized Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), Decision Tree Regression (DTR), and Neural Network Regression (NNR) machine-learning algorithms were applied. The findings show that RFR (R2 = 0.56, RMSE = 21.01 cm) and SVM (R2 = 0.58, RMSE = 20.41 cm) produce a low modeling accuracy for crop height estimation with S-1 SAR data. The S-1 and S-2 satellite data fusion experiment had an improvement in accuracy with the RFR (R2 = 0.93 and RMSE = 8.53 cm) model outperforming the SVM (R2 = 0.91 and RMSE = 9.20 cm) and other models. Normalized polarization (Pol) and the radar vegetation index (RVI_S1) were important predictor variables for crop height retrieval compared to other variables with S-1 and S-2 data fusion as input features. The SAR ratio index (SAR RI 2) had a strong positive and significant correlation (r = 0.94; p < 0.05) with crop height amongst the predictor variables. The spatial distribution maps generated in this study show the viability of data fusion to produce accurate crop height variability maps with machine-learning algorithms. These results demonstrate that both RFR and SVM can be used to quantify crop height during the growing stages. Furthermore, findings show that data fusion improves model performance significantly. The framework from this study can be used as a tool to retrieve other wheat biophysical variables and support decision making for different crops.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":"12 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140673996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Throughput Phenotyping: Application in Maize Breeding","authors":"E. L. Resende, A. T. Bruzi, Everton da Silva Cardoso, Vinícius Quintão Carneiro, Vitório Antônio Pereira de Souza, Paulo Henrique Frois Correa Barros, Raphael Rodrigues Pereira","doi":"10.3390/agriengineering6020062","DOIUrl":"https://doi.org/10.3390/agriengineering6020062","url":null,"abstract":"In breeding programs, the demand for high-throughput phenotyping is substantial as it serves as a crucial tool for enhancing technological sophistication and efficiency. This advanced approach to phenotyping enables the rapid and precise measurement of complex traits. Therefore, the objective of this study was to estimate the correlation between vegetation indices (VIs) and grain yield and to identify the optimal timing for accurately estimating yield. Furthermore, this study aims to employ photographic quantification to measure the characteristics of corn ears and establish their correlation with corn grain yield. Ten corn hybrids were evaluated in a Complete Randomized Block (CRB) design with three replications across three locations. Vegetation and green leaf area indices were estimated throughout the growing cycle using an unmanned aerial vehicle (UAV) and were subsequently correlated with grain yield. The experiments consistently exhibited high levels of experimental quality across different locations, characterized by both high accuracy and low coefficients of variation. The experimental quality was consistently significant across all sites, with accuracy ranging from 79.07% to 95.94%. UAV flights conducted at the beginning of the crop cycle revealed a positive correlation between grain yield and the evaluated vegetation indices. However, a positive correlation with yield was observed at the V5 vegetative growth stage in Lavras and Ijaci, as well as at the V8 stage in Nazareno. In terms of corn ear phenotyping, the regression coefficients for ear width, length, and total number of grains (TNG) were 0.92, 0.88, and 0.62, respectively, demonstrating a strong association with manual measurements. The use of imaging for ear phenotyping is promising as a method for measuring corn components. It also enables the identification of the optimal timing to accurately estimate corn grain yield, leading to advancements in the agricultural imaging sector by streamlining the process of estimating corn production.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modern Floating Greenhouses: Planting Gray Oyster Mushrooms with Advanced Management Technology Including Mobile Phone Algorithms and Arduino Remote Control","authors":"Grianggai Samseemoung, Phongsuk Ampha, Niti Witthayawiroj, Supakit Sayasoonthorn, Theerapat Juey","doi":"10.3390/agriengineering6020061","DOIUrl":"https://doi.org/10.3390/agriengineering6020061","url":null,"abstract":"A floating greenhouse for growing oyster mushrooms can be operated remotely via a mobile phone. This innovative system can enhance mushroom production and quality while saving time. By using the Android OS operating system on a mobile phone (Internet Mobile Device with Android OS, MGT Model: T10), users can adjust the humidity and temperature within the greenhouse. This approach is particularly beneficial for older adults. Create a smart floating greenhouse that can be controlled remotely to cultivate oyster mushrooms. It would help to enhance the quality of the mushrooms, reduce the time required for cultivation, and increase the yield per planting area. We carefully examined the specifications and proceeded to create a greenhouse that could float. In addition, we have developed a unit that could control temperature and humidity, a solar cell unit, and a rack for growing mushrooms. Our greenhouses were operated remotely. To determine the best conditions for growing plants in a floating greenhouse, we conducted a test to measure temperature and humidity. We then compared our findings to those of a traditional greenhouse test and determined the optimal parameters for floating greenhouse growth. These parameters include growth time, temperature, humidity, and weight. A mushroom nursery that can be controlled remotely and floats on water consists of four main components: a structure to regulate temperature and humidity, solar cells, and mushroom racks. Research shows that mushrooms grown under this automated control system grow better than those grown through traditional methods. The harvest period is shorter, and the yield is higher than the typical yield of 1.81–1.22. When considering the construction and use of remote-controlled floating mushroom nurseries, the daily weight of mushrooms accounted for 20.22%. The company’s investment return rates were found to be 3.47 years, or 580.21 h per year, which is higher than the yield of traditional methods. This mobile phone remote control system, created by Arduino, is tailor-made for cutting-edge floating greenhouses that grow grey oyster mushrooms. It can be operated with ease via mobile devices and is especially user-friendly for elderly individuals. This system enables farmers to produce a high volume of quality breeds. Furthermore, those with fish ponds can utilize the system to increase their profits.","PeriodicalId":505370,"journal":{"name":"AgriEngineering","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140683020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}