Cultivation of Edible Tropical Bolete, Phlebopus spongiosus, in Thailand and Yield Improvement by High-Voltage Pulsed Stimulation

Tropical bolete, Phlebopus spongiosus, is an edible ectomycorrhizal mushroom indigenous to northern Thailand. This mushroom has the ability to produce fruiting bodies without the need for a host plant. In this study, the technological cultivation of P. spongiosus was developed. Cultivation experiments indicated that fungal mycelia could completely colonize the cultivation substrate over a period of 85–90 days following inoculation of liquid inoculum. Primordia were induced under lower temperatures, high humidity and a 12-h photoperiod. Mature fruiting bodies were developed from young fruiting bodies within a period of one week. Consequently, yield improvement of P. spongiosus cultivation was determined by high-voltage pulsed stimulation. The results indicated that the highest degree of primordial formation, number of mature fruiting bodies and total weight values were obtained in cultivation experiments involving a high voltage of 40 kV. The total weight of the mushrooms increased by 1.4 times after applying high-voltage pulses when compared with the control. Additionally, the results revealed that the size of the fruiting body and the proximate composition of the fruiting bodies from high-voltage stimulation treatments were not different from the control. This research provides valuable information concerning successful cultivation techniques and yield improvement by high-voltage pulsed stimulation for the large-scale commercial fruiting body production of P. spongiosus.

Greenhouse localized heating powered by a polygeneration system

Energy consumption in greenhouse heating could reach up to 90% of the total energy requirement depending on the type of greenhouse, environmental control equipment and location of the greenhouse. The use of climate conditioning technologies that exploit renewable energy and the application of passive systems to improve the energy efficiency and the sustainability of the greenhouse sector are recommended. During winter 2020-2021, an experimental test was carried out at the University of Bari in a Mediterranean greenhouse heated by a polygeneration system, composed of a solar system and an air-water heat pump. Three localized heating systems were tested to transfer thermal energy close to plants of Roman lettuce. Heating pipes were placed inside the cultivation substrate in the underground pipe system and on the cultivation substrate in the laid pipe system. The third system consists of metal plates heated by steel tubes and placed in the aerial area of plants. A weather climatic station and a sensor system interfaced with a data logger for continuous data acquisition and storage were used. The plate system was the best for air temperature rising, as it allowed an increase of 3.6% compared to the set-up without any localised heating system. The underground pipe system was the best for the soil heating, as it achieved a temperature increase of 92%. Localized soil heating systems contributed significantly to an earlier harvest by almost 2 weeks.

Genome of Ganoderma Species Provides Insights Into the Evolution, Conifers Substrate Utilization, and Terpene Synthesis for Ganoderma tsugae

Ganoderma tsugae is an endemic medicinal mushroom in Northeast China, providing important source of pharmaceutical product. Comparing with other Ganoderma species, wild G. tsugae can utilize coniferous wood. However, functional genes related to medicinal component synthesis and the genetic mechanism of conifer substrate utilization is still obscure. Here, we assembled a high-quality G. tsugae genome with 18 contigs and 98.5% BUSCO genes and performed the comparative genomics with other Ganoderma species. G. tsugae diverged from their common ancestor of G. lingzhi and G. sinense about 21 million years ago. Genes in G. tsugae-specific and G. tsugae-expanded gene families, such as salh, phea, cyp53a1, and cyp102a, and positively selected genes, such as glpk and amie, were functionally enriched in plant-pathogen interaction, benzoate degradation, and fanconi anemia pathway. Those functional genes might contribute to conifer substrate utilization of G. tsugae. Meanwhile, gene families in the terpene synthesis were identified and genome-wide SNP variants were detected in population. Finally, the study provided valuable genomic resources and offered useful hints for the functional gene mapping and investigation of key gene contributing to conifer cultivation substrate utilization and medicinal component biosynthesis.

Fatty Acids and Stable Isotope Ratios in Shiitake Mushrooms (Lentinula edodes) Indicate the Origin of the Cultivation Substrate Used: A Preliminary Case Study in Korea

Shiitake mushroom (Lentinula edodes) is commonly consumed worldwide and is cultivated in many farms in Korea using Chinese substrates owing to a lack of knowledge on how to prepare sawdust-based substrate blocks (bag cultivation). Consequently, issues related to the origin of the Korean or Chinese substrate used in shiitake mushrooms produced using bag cultivation have been reported. Here, we investigated differences in fatty acids (FAs) and stable isotope ratios (SIRs) in shiitake mushrooms cultivated using Korean and Chinese substrates under similar conditions (strain, temperature, humidity, etc.) and depending on the harvesting cycle. The total FA level decreased significantly by 5.49 mg∙g−1 as the harvesting cycle increased (p < 0.0001); however, no differences were found in FAs between shiitake mushrooms cultivated using Korean and Chinese substrates. Linoleic acid was the most abundant FA, accounting for 77–81% of the total FAs during four harvesting cycles. Moreover, the SIRs differed significantly between the Korean and Chinese substrates, and the harvesting cycles resulted in smaller maximum differences in SIR values compared to those of the cultivation substrate origins. Our findings contribute to the identification of the geographical origin of shiitake mushrooms and may have potential applications in international shiitake-mushroom markets.

Comparative Metabolomic Analysis of Dendrobium officinale under Different Cultivation Substrates

Dendrobium officinale, a precious herbal medicine, has been used for a long time in Chinese history. The metabolites of D. officinale, regarded as its effective components to fight diseases, are significantly affected by cultivation substrates. In this study, ultra-performance liquid chromatography mass spectrometry (UPLC-MS/MS) was conducted to analyze D. officinale stems cultured in three different substrates: pine bark (PB), coconut coir (CC), and a pine bark: coconut coir 1:1 mix (PC). A total of 529 metabolites were identified. Multivariate statistical analysis methods were employed to analyze the difference in the content of metabolites extracted from different groups. By the criteria of variable importance in projection (VIP) value ≥1 and absolute log2 (fold change) ≥1, there were a total of 68, 51, and 57 metabolites, with significant differences in content across groups being filtrated out between PB and PC, PB and CC, and PC and CC, respectively. The comparisons among the three groups revealed that flavonoids were the metabolites that fluctuated most. The results suggested the D. officinale stems from the PB group possessed a higher flavonoid content. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that the significantly regulated metabolites were mainly connected with flavonoid biosynthesis. A comprehensive profile of the metabolic differentiation of D. officinale planted in different substrates was provided, which supports the selection of an optimum cultivation substrate for a higher biomass yield of D. officinale.

Cultivation Substrate Composition Influences Morphology, Volatilome and Essential Oil of Lavandula Angustifolia Mill.

Aromatic plants are commonly produced for ornamental, cosmetic and medicinal purposes. Their morphological traits and the amounts and compositions of the volatile substances and essential oils (EOs) produced can be influenced by several factors, including the cultivation technique. In the present study, the influence of substrate composition on Lavandula angustifolia Mill. production was evaluated. In particular, substrates containing mixes of peat (P), green compost (C) and/or demolition aggregates (A) were tested in the following ratios: 70%:30% v/v, P:C; 70%:30% v/v, P:A; and 40%:30%:30% v/v, P:C:A. The P:C mixture allowed to obtain the best results in terms of survival rate, compactness of the plant and flower production. The P:C:A led to higher yields and better quality of EOs, with higher amounts of linalool, an important compound for medicinal uses. The volatiles and the blooming trend were not affected by the different cultivation substrates. Therefore, substrate composition in pot lavender cultivation can be regulated depending on the final use of the plant, successfully using locally sourced material in addition to peat.

A Phenotype-Based Approach for the Substrate Water Status Forecast of Greenhouse Netted Muskmelon

Cultivation substrate water status is of great importance to the production of netted muskmelon (Cucumis melo L. var. reticulatus Naud.). A prediction model for the substrate water status would be beneficial in irrigation schedule guidance. In this study, the machine learning random forest model was used to forecast plant substrate water status given the phenotypic traits throughout the muskmelon growing season. Here, two varieties of netted muskmelon, “Wanglu” and “Arus”, were planted in a greenhouse under four substrate water treatments and their phenotypic traits were measured by taking the images within the visible and near-infrared spectrums, respectively. Results showed that a simplified model outperformed the original model in forecasting speed, while it only uses the top five most significant contribution traits. The forecast accuracy reached up to 77.60%, 94.37%, and 90.01% for seedling, vine elongation, and fruit growth stages, respectively. Combining the imaging phenotypic traits and machine learning technique would provide a robust forecast of water status around the plant root zones.