Mushroom Houses Research Articles

Microbiomes of Two Pest Fly Species of Pennsylvania Mushroom Houses.

Mushroom cultivation vastly improves the yield of mushrooms under optimized, controlled conditions, but may be susceptible to opportunistic colonization by pest species that can establish themselves, as well as the pathogens and pests they may transmit. Here, we describe our investigation into the bacterial communities of adult Lycoriella ingenua (Diptera: Sciaridae) and Megaselia halterata (Diptera: Phoridae) collected from button mushroom (Agaricus bisporus) production houses in Pennsylvania. We collected adult flies and sequenced the hypervariable v4 region of the bacterial 16S rRNA using the Illumina MiSeq. The most abundant bacterial genus detected in both species was Wolbachia, but phylogenetic analysis revealed that the infections are from different clades. Future studies include the characterization of Wolbachia infections on fly behavior and biology, comparison of microbial diversity of fly species colonizing wild mushrooms, and other microbiota that may contribute to the success of certain pest fly species.

Exploring the Influence of Culture Environment on the Yield of Volvariella volvacea Based on Microbiomics

As one of the most nutritious and delicious mushroom varieties, Volvariella volvacea has always been popular among people around the world. Different from other artificially cultivated mushrooms, Volvariella volvacea is mostly planted on non-sterile substrates. As the cultivation time increases, the yield of mushroom houses continues to decrease. In our experiment, we selected two groups of samples from the old and new mushroom houses, environmental samples and substrate samples. The results showed that the diversity and abundance of microorganisms in the culture environment of the old mushroom room were consistent with that of the new mushroom room, but the proportion of actinomycetes in the former was significantly higher than that of the new mushroom room. The metabolic activity of microorganisms in the old mushroom room was enhanced compared with the new mushroom room. The microbial diversity in the growth substrate was investigated, and it was found that the structure and diversity of the microbial community in the substrate had changed. In conclusion, the interplay between mushrooms, the culture environment, and the host bacterial community may be the cause of the changes in the yield of Volvariella volvacea.

Temperature Prediction of Mushrooms Based on a Data—Physics Hybrid Approach

Temperature has a significant impact on the production of edible mushrooms. The industrial production of edible mushrooms is committed to accurately maintaining the temperature inside the mushroom room within a certain range to achieve quality and efficiency improvement. However, current environmental regulation methods have problems such as lagging regulation and a large range of temperature fluctuations. There is an urgent need to accurately predict the temperature of mushroom houses in the future period to take measures in advance. Therefore, this article proposes a temperature prediction model for mushroom houses using a data–physical hybrid method. Firstly, the Boruta-SHAP algorithm was used to screen out the key influencing factors on the temperature of the mushroom room. Subsequently, the indoor temperature was decomposed using the optimized variational modal decomposition. Then, the gated recurrent unit neural network and attention mechanism were used to predict each modal component, and the mushroom house heat balance equation was incorporated into the model’s loss function. Finally, the predicted values of each component were accumulated to obtain the final result. The results demonstrated that integrating a simplified physical model into the predictive model based on data decomposition led to a 12.50% reduction in the RMSE of the model’s predictions compared to a purely data-driven model. The model proposed in this article exhibited good predictive performance in small datasets, reducing the time required for data collection in modeling.

Energy-Saving Control Method for Factory Mushroom Room Air Conditioning Based on MPC

The energy consumption of the mushroom room air conditioning system accounts for 40% of the total energy consumption of the mushroom factory. Efficient and energy-efficient mushroom factories and mushroom houses are the development direction of the industry. Compared with maintenance structure transformation and air conditioning equipment upgrading, energy-saving technology based on regulation methods has the advantages of less investment and fast effectiveness, which has attracted attention. The current methods for regulating air conditioning in edible mushroom factories include simple on/off thermostat control or PID. In the field of energy efficiency in commercial building air conditioning, a large number of studies have shown that compared with traditional control algorithms such as classic on/off or PID control, model predictive control can significantly improve energy efficiency. However, there is little literature mentioning the application of MPC in factory mushroom production rooms. This paper proposes a data-driven MPC and PID combined energy-saving control method for mushroom room air conditioning. This method uses the CNN-GRU-Attention combination neural network as the prediction model, combined with prediction error compensation and dynamic update mechanism of the prediction model dataset, to achieve an accurate prediction of indoor temperature in mushroom houses. Establish an objective function for air conditioning control duration and temperature, use the non-dominated sorting genetic algorithm II (NSGA-II) to solve for the optimal control sequence of the air conditioning in the control time domain, and use the entropy weight method to determine the optimal decision quantity. Integrate rolling optimization, feedback mechanism, and PID to achieve precise and energy-saving control of the mushroom room environment. The experimental results show that compared with the on/off thermostat and PID controller, the designed controller reduces power consumption by 12% and 5%, respectively, and has good application and demonstration value in the field of industrial production of edible mushrooms.

Prediction of Heat and Cold Loads of Factory Mushroom Houses Based on EWT Decomposition

Load forecasting has significant implications on optimizing the operation of air conditioning systems for industrial mushroom houses and energy saving. This research paper presents a novel approach for short-term load forecasting in mushroom houses, which face challenges in accurately modeling cold and heat loads due to the complex interplay of various factors, including climatic conditions, mushroom growth, and equipment operation. The proposed method combines empirical wavelet transform (EWT), hybrid autoregressive integrated moving average (ARIMA), convolutional neural network (CNN), and bi-directional long short-term memory (BiLSTM) with an attention mechanism (CNN-BiLSTM-Attention) to address these challenges. The first step of this method was to select input features via the Boruta algorithm. Then, the EWT method was used to decompose the load data of mushroom houses into four modal components. Subsequently, the Lempel–Ziv method was introduced to classify the modal components into high-frequency and low-frequency classes. CNN-BiLSTM-Attention and ARIMA prediction models were constructed for these two classes, respectively. Finally, the predictions from both classes were combined and reconstructed to obtain the final load forecasting value. The experimental results show that the Boruta algorithm selects key influential feature factors effectively. Compared to the Spearman and Pearson correlation coefficient methods, the mean absolute error (MAE) of the prediction results is reduced by 14.72% and 3.75%, respectively. Compared to the ensemble empirical mode decomposition (EEMD) method, the EWT method can reduce the decomposition reconstruction error by an order of magnitude of 103, effectively improving the accuracy of the prediction model. The proposed model in this paper exhibits significant advantages in prediction performance compared to the single neural network model, with the MAE, root mean square error (RMSE), and mean absolute percentage error (MAPE) of the prediction results reduced by 31.06%, 26.52%, and 39.27%, respectively.

Hani Mushroom House Building Adaptability

The Hani Rice Terraces are a famous World Heritage Site. The mushroom houses in the terraced fields have a unique architectural style and national cultural characteristics. This study focused on four traditional villages with the most obvious characteristics of mushroom houses: Azheke Village, Dayutang Village, Yakou Village, and Dayazi Village. A total of 34 mushroom houses were mapped. The forms of the mushroom houses were classified first, and then, the basic prototype of the building structure of the Hani mushroom houses was extracted for structural modeling. Finally, the structure of the prototype of the mushroom houses under different load conditions was analyzed. The results show that the Hani mushroom house design has a simple structure and good stability, can adapt to the local natural environment, and is the product of the Hani people’s adaptation to the local natural environment.

Keragaan Agribisnis Usaha Jamur Tiram Putih di Kelurahan Anduonohu Kecamatan Poasia Kota Kendari (Studi Kasus di Usaha Tiga Putra Farm)

Oyster mushroom is a type of wood mushroom that Indonesia commonly consumes. It has a fruiting body that grows in bloom to form a shallow funnel shell (oyster). This study aimed to determine the agribusiness performance of the White Oyster Mushroom (Pleurotus ostreatus) in Anduonohu ​​Village, Poasia District, Kendari City. Case study on Tiga Putra Farm Business. This research was conducted in September 2021. The object of this research was the Tiga Putra Fram Timber Mushroom business. The method used in this study is Qualitative Descriptive Analysis. The type of data in this study used primary data, namely direct interviews, and secondary data, namely library literature. The variables used in this study are 1. The informant's identity includes age, education level, business experience, and some family dependents, 2. Agribusiness performance from this study is in the form of support in the agribusiness subsystem, which includes production facilities (seeds, fertilizers, tools /machinery, and mushroom house), cultivation and farming subsystem (planting, maintenance, processing), and marketing subsystem (distribution). The results of this study are the agribusiness performance of the white oyster mushroom (Pleurotus ostreatus), namely the procurement and provision of production facilities, including the procurement of mushroom houses, seeds, tools, and machines. Cultivation and farming include oyster mushroom production, maintenance, and harvest. Oyster mushroom product marketing is done online and offline by online method, namely posting oyster mushroom products on several social media platforms such as Facebook, WhatsApp, and Instagram. Thus the range of product marketing can be more comprehensive. Offline marketing to resellers of oyster mushrooms that will be resold, such as the Ummushabri Kendari and Hypermart.

Optimization of Space in the Oyster Mushroom Industry with the Activity Relationship Chart Method

Layout is a technique of arranging facilities to be better than before which aims to minimize all costs and maximize profits. The purpose of this research is to optimize space in XYZ which produces oyster mushrooms. The optimization of space in this study uses the Activity Relationship Chart (ARC) method approach. ARC is a method that identifies the relationship of importance between one facility to another or one activity to another, whether it is important to bring it closer or it should be kept away. The results showed that the layout of the facilities in the XYZ home industry can still be optimized, including adding raw material warehouses, toilets, prayer rooms, ablution places, and the use of vacant land as oyster mushroom houses.

Productivity and Flexibility Improvement of Straw Mushroom House

This study aims to improve the productivity and flexibility of the mushroom house to increase the production of straw mushrooms. Determining the design of technical specifications and material requirements of the mushroom house is a process that is quite important in determining the success or failure of increasing straw mushroom production. QFD (Quality Function Deployment) is used to obtain the best design based on the needs of the mushroom farmers. The needs of the mushroom farmers are then translated through QFD into technical specifications. MCDM (Multi Criteria Decision Making) is used to determine the material for the frame and blanket of the mushroom house according to the technical specifications of the QFD. CRITIC (Criteria Importance Through Intercriteria Correlation) is one of the methods of MCDM that performs an objective weighting of the criteria. A mushroom house was built based on the technical and material specifications obtained from QFD and CRITIC. Tests were carried out by comparing the productivity and flexibility between traditional mushroom houses and designed mushroom houses. The peroductivity of the mushroom house includes cleanliness, stability in temperature and humidity, the rate of growth of straw mushrooms in media. Flexibility includes the ability to assembled and disassembled, easily mobilize from one place to another.

Affecting Biotik and Abiotic Components Cultivation of Oyster Mushroom (Pleurotus ostreatus) in Kualanamu, North Sumatera

Oyster mushroom (Pleoratus ostreatus) is one of the mushroom species cultivated by residents of Pasar VI Kualanamu Village, Beringin District, Deli Serdang Regency, North Sumatra Province. Residents gain knowledge of oyster mushroom cultivation through the training provided. Therefore, researchers are interested in conducting research in Pasar VI Kualanamu Village. The purpose of this study is to determine the biotic and abiotic components that can affect the growth of oyster mushrooms and what efforts need to be made so that they can cultivate oyster mushrooms and increase their production. The research carried out is a type of field research that is descriptive qualitative, namely research that describes existing phenomena by finding patterns of interactive relationships, discovering new theories, describing complex realities and gaining understanding of meaning. In this study, the researcher was involved as a participant observer to further explore the research process carried out. From the results of the study it can be concluded that the biotic and abiotic components that can affect the growth of oyster mushrooms (Pleurotus ostreatus) are kumbung building materials (mushroom houses), pests in kumbung (mushroom houses), sunlight, water, sterilization of materials (wood powder & bran), soil temperature and humidity, planting and harvesting media

Pengembangan Monitoring Suhu dan Kelembaban Berbasis Internet of Things serta Sistem Automatic Sprinkling pada Rumah Jamur

White oyster mushroom is one type of wood fungus that has native habitat in temperate regions with temperatures ranging from 22-28oC and humidity ranging from 60-80% RH. This mushroom cultivation can be done by storing planting media in a mushroom house (kumbung) by monitoring and maintaining the condition of temperature and humidity. At present the monitoring and maintenance of temperature and humidity is done by manually watering methods by estimating the conditions of the kumbung temperature and humidity. This causes the temperature and humidity conditions only to be estimated manually so that mushroom productivity is not maximal. This study aims to facilitate the mushroom farmers in watering and monitoring the condition of the kumbung. This system consists of sensors placed inside the cage and will detect the temperature and humidity conditions of the cage, temperature and humidity data will then be processed by the controller to enable automatic watering. watering is done with the help of a pump that is equipped with a nozzle to create a mist of water. Based on the results of observations that have been made can be obtained that the system is able to streamline time by watering automatically when the mushroom house conditions are not in accordance with the setpoint. This system is also capable of producing mushroom house conditions that can reduce temperatures to the range of 22-28o C and increase humidity to the range of 60-80% RH in less than 600 seconds. Information on monitoring the temperature and humidity of mushroom houses has been based on internet of things, which is showing the temperature and humidity conditions of mushroom houses through the website according to the data sent by the controller.

Oyster mushroom house conditions classification using K-Nearest Neighbor

Internet of Things devices that were implemented to support condition monitoring and control systems in mushroom houses get a lot of temperature and humidity data from mushroom houses. The large number of temperature and humidity data can be used as the variables or indicators that affect mushroom production. Temperature and humidity data can be classified based on the production of mushrooms produced in one house or mushroom houses. This study aims to determine the classification of temperature and humidity data in mushroom houses based on mushroom production. The method used is a data mining approach based on the K-Nearest Neighbor. This research begins with determining the variables from training data or training data, taking testing data, then the testing data is reprocessed based on the K-Nearest Neighbor method with training data. Finally, evaluation of the method used was carried out by calculating the accuracy value. As a result, the accuracy of the K- Nearest Neighbor method was about 89%. These results are expected to be used to forecast the yield of mushroom production for future research. The forecast can be seen from the pattern of temperature and humidity data that is formed based on a certain period of time.

Automated Controlled Environment Mushroom House

Mushroom can be served as flavoursome food, but most importantly, it can be served as nutritional and medicinal value food. Therefore, a mushroom is an essential commodity under the Malaysia National Agro-Food Policy. Currently, mushroom cultivation is being done in the conventional method, not in a proper and hygienic condition. Therefore controlled environment mushroom house (CEMH) has been developed by transforming a greenhouse into a controlled environment mushroom house integrated with the internet of things (IoT) system. This CEMH micro-climate is automatically controlled by the combination of data parameters provided by various types of sensors. The integration of the IoT system has further enhanced this system to overcome extreme weather changes and override the control anytime and anywhere. The computation and monitoring process can be done either locally or remotely. The current system is set up for Grey Oyster mushroom (Pleurotus pulmonaris) cultivation to identify the best isolate to be proposed for mass production. The interconnection of sensors, mechanical and electronic systems is to optimize the growth condition. The developed system manages to control the temperature consistently and relative humidity (% RH) in the range of 18oC to 27oC and % RH not lower than 70%, respectively. For this condition, this system can produce at least 30% more yield than ordinary mushroom houses. Moreover, the contamination rate is successfully kept below 2% and is considered very low compared to ordinary entrepreneur mushroom houses, usually more than 10%. This system can provide the research facility for the high nutritional and medicinal value mushrooms.

Analysis of the Role of Bradysia impatiens (Diptera: Sciaridae) as a Vector Transmitting Peanut Stunt Virus on the Model Plant Nicotiana benthamiana.

Bradysia species, commonly known as fungus gnats, are ubiquitous in greenhouses, nurseries of horticultural plants, and commercial mushroom houses, causing significant economic losses. Moreover, the insects from the Bradysia genus have a well-documented role in plant pathogenic fungi transmission. Here, a study on the potential of Bradysia impatiens to acquire and transmit the peanut stunt virus (PSV) from plant to plant was undertaken. Four-day-old larvae of B. impatiens were exposed to PSV-P strain by feeding on virus-infected leaves of Nicotiana benthamiana and then transferred to healthy plants in laboratory conditions. Using the reverse transcription-polymerase chain reaction (RT-PCR), real-time PCR (RT-qPCR), and digital droplet PCR (RT-ddPCR), the PSV RNAs in the larva, pupa, and imago of B. impatiens were detected and quantified. The presence of PSV genomic RNA strands as well as viral coat protein in N. benthamiana, on which the viruliferous larvae were feeding, was also confirmed at the molecular level, even though the characteristic symptoms of PSV infection were not observed. The results have shown that larvae of B. impatiens could acquire the virus and transmit it to healthy plants. Moreover, it has been proven that PSV might persist in the insect body transstadially. Although the molecular mechanisms of virion acquisition and retention during insect development need further studies, this is the first report on B. impatiens playing a potential role in plant virus transmission.

Sistem Kontrol Otomatis Berbasis IoT dan Sel Surya Untuk Budidaya Jamur Tiram di Desa Selorejo, Jombang

Lila Yuwana*1, Susilo Indrawati2, Sudarsono3, Niniet Indah Arvitrida4, Iim Fatimah5, Diky Anggoro61,2,3,5,6Departemen Fisika, Institut Teknologi Sepuluh Nopember4Departemen Teknik dan Sistem Industri, Institut Teknologi Sepuluh Nopember*e-mail: lila@physics.its.ac.id1, susilo_i@physics.its.ac.id2 , sudars29@gmail.com3, arvietrida@gmail.com4, iim.fatimah.its@gmail.com5, anggorodiky@gmail.com6 Received: 31 Mei 2021/ Accepted: 16 Juni 2021 Abstract Pleurotus ostreatus cultivation has been developed using wood sawdust as a planting medium in Selorejo Village, Mojowarno District, Jombang Regency, East Java. Previous research, sawdust can function very well as a growing medium for oyster mushrooms, which is indicated by the abundance of yields. In addition, the use of sawdust can also overcome the problem of abundant waste from the furniture industries in Selorejo Village. In this community service that will be carried out, it aims to create an internet-based or IoT (Internet of Things) and solar cell-based control system as a resource for the entire system. The IoT system designed and built in abdimas is used to see the development of ostreatus mushrooms in the mushroom house through a webcam that is integrated with the system. Furthermore, through this IoT, humidity and temperature settings can be done anywhere through the android application and internet browser. The power system that uses solar cells in this service is taking into account the limited electrical power in the mushroom house in Selorejo Village, Mojowarno Jombang. All systems that are designed and will be built in this service are portable, in other words, they can be easily moved around. With this service, it is hoped that Micro, Small and Medium Enterprises (MSMEs) in ostreatus cultivation can increase the efficiency of the ostreatus mushroom growing process because monitoring the process of growing ostreatus mushrooms can be done anywhere and anytime, through an integrated IoT system. In addition, it is hoped that other MSMEs can adopt the automation system for controlling humidity and temperature for ostreatus mushroom cultivation based on IoT and solar cells. Key words: IoT (Internet of Things), solar cells, mushroom houses, ostreatus mushrooms, sensors and monitoring

RESPONS VARIETAS DAN MUSIM TANAM TERHADAP PERTUMBUHAN, HASIL DAN KUALITAS JAMUR TIRAM

Oyster mushroom was a prospective vegetable commodity and has high economical value. The aim of this research was to find out oyster mushroom varieties that could be adapted in Bogor – West Java, and produced high yield and quality when cultivated both in the dry and rainy seasons. A Randomized Block Design with 4 replications were set up in mushroom houses during the dry and the rainy seasons. Treatments comprised of 6 varieties of oyster mushrooms, viz: varieties No. 1; 30; 37; 38; 46 (origin from IVEGRI’s collection) and No. 85 (origin from Bogor as control variety). The result showed that varieties and planting seasons has significantly effect on growth of oyster mushroom. However varieties has no significantly effect on yield of mushroom which was in average 55-91 ton/1000 m2 of mushrooms house area. Fresh yield of mushroom planted in dry season (91.3 ton) was significantly higher than those in wet season (61.7 ton). Varieties has significantly effect of mushroom quality, meanwhile seasons gave a same good quality with delicious/ ranking <3, storage resistance up to 2 days at room temperature and water content >90 %. Keywords: Planting season, Pleurotus ostreatus, growth, yield, quality

Rumah jamur solusi peningkatan ekonomi masyarakat Desa Seko Lubuk Tigo Kecamatan Lirik Riau

The objective of this service is to increase the economy of community at Seko Lubuk Tigo village of Lirik sub-district, and to meet the needs of the mushroom market by making mushroom houses. The method of this program was conducted in the form of counseling, accompaniment, and the demonstration of making mushroom house by involving the students of Riau University who are in carrying out a Student Study Service (KKN). The respons of community were very positive, and have high spirit in applying the technology of making Mushroom House. The community were very enthusiastic to make mushroom house as a new job opportunity. The output of this program is to make the oyster mushroom production house and the pocket book for mushroom production. It is expected that by conducting this program, the community can disseminate the technology which is accepted to be applied to other communities.

Fate of weed seeds in spent mushroom compost following commercial mushroom production

AbstractCommercial mushroom producers grow several varieties of mushrooms on compost. Upon completion of the growing cycle, the spent mushroom compost is often sold as a soil amendment for both agricultural and homeowner use. Mushroom compost ingredients often come from fields infested with weeds, and in turn compost may spread unwanted weed seed. We conducted studies to assess the viability of weed seed following specific stages of the commercial mushroom production process. Weed seed was more likely to survive if the entire production process was not completed. However, no viable hairy vetch, Italian ryegrass, ivyleaf morningglory, Palmer amaranth, or velvetleaf remained at the end of the study. Although the seeds of most species were eliminated earlier in the composting process, ivyleaf morningglory required the complete process to eliminate 100% of the seed. These results indicate that spent mushroom compost is free of many weed species upon removal from mushroom houses and is unlikely to spread weed seed.

Pest incidence in white button mushroom in Haryana

To know the status of pest incidence in mushroom, survey was conducted during 2014-15 to 2017-18 in major mushroom growing districts of Haryana state viz. Hisar, Sirsa, Fatehabad, Jind, Rohtak, Panipat, Sonepat, Karnal, Kurukshetra and Yamunanagar. The mean of the four years data indicated that the mushroom flies’ incidence was higher in districts Karnal, Sonepat, Panipat and Rohtak compared to the other districts of state surveyed and among mushroom flies, the infestation of sciarid fly was higher as compared to the phorid fly. During the study, no incidence any insect pest or mite was observed in district Sirsa. It was concluded that the mushroom houses having cleanliness recorded lower incidence of insect pests compared to the others where sanitation practices were not followed properly.

Tyrophagus neiswanderi (Acari: Acaridae) as a Pest of Greenhouse Spinach in Antalya, Turkey

Tyrophagus neiswanderi (Johnston & Bruce 1965) generally lives in stored products as saprophyte and on dead bodies of arthropods living in the soil, organic fertilizers, mushroom houses, greenhouses, algae and plant scraps. In this study, however, it was observed in roots and shoots of spinach (Spinacia oleracea L.) plants originated from greenhouse commercial crop in 2016-2017, in cultivated areas around Antalya, Turkey. This is the first record of T. neiswanderi occurring in spinach plants under greenhouse conditions in Antalya, Turkey.