Pomegranate (Punica granatum L.) is one of the oldest fruits with edible, medicinal and ornamental values. However, there is no report on the mitochondrial genome of pomegranate. In this study, the mitochondrial genome of P. granatum was sequenced, assembled and analyzed in detail, while the chloroplast genome was assembled using the same set of data. The results showed that the P. granatum mitogenome had a multi branched structure, using BGI + Nanopore mixed assembly strategy. The total genome length was 404,807 bp, with the GC content of 46.09%, and there were 37 protein coding genes, 20 tRNA genes and three rRNA genes. In the whole genome, 146 SSRs were identified. Besides, 400 pairs of dispersed repeats were detected, including 179 palindromic, 220 forward and one reverse. In the P. granatum mitochondrial genome, 14 homologous fragments of chloroplast genome were found, accounting for 0.54% of the total length. Phylogenetic analysis showed that among the published mitochondrial genomes of related genera, P. granatum had the closest genetic relationship with Lagerstroemia indica of Lythraceae. The 580 and 432 RNA editing sites were predicted on 37 protein coding genes of mitochondrial genome using BEDTools software and online website PREPACT respectively, but all were from C to U, of which ccmB and nad4 gene were most frequently edited, with 47 sites. This study provides a theoretical basis for understanding the evolution of higher plants, species classification and identification, and will also be useful for further utilization of pomegranate germplasm resources.

Grapevine is one of the most important fruit trees in the world, but it is often threatened by various biotic and abiotic stresses in production, resulting in decreased yield and quality. Grapevine double cropping in one year is a kind of preparatory and artificial control technology, which can not only save the loss of natural disasters, but also plays an important role in staggering the peak to market, thus increasing yield and improving the quality of grape fruit. This perspective provides a concise discussion of the physiological basis, the main determinants, and their impacts on yield and fruit quality of grapevine double cropping. We also highlight the current challenges around this theme and prospect its application in the future.

The ventilation rate of a greenhouse is one of the major factors to consider when assessing its ventilation performance. Compared with plain areas, high-altitude areas have lower air pressure, thinner air, and stronger solar radiation, which in turn affect the magnitude of the local greenhouse ventilation rate. This paper is based on the use of online monitoring and computational fluid dynamics (CFD) techniques for modeling and model validation. The average relative error (ARE), mean absolute error (MAE), root-mean-square error (RMSE), and determination coefficient (R²) of the temperature were 4.88%, 1.396 °C, 1.428 °C, and 0.9982, respectively. The ARE, MAE, RMSE, and R² of the velocity were 9.525%, 0.035 m/s, 0.049 m/s, and 0.9869, respectively. Then, the distributions of the wind pressure, Reynolds number (Re), thermal pressure, air density, air speed, and temperature in greenhouses in high-altitude and plain areas were researched to obtain the relevant factors affecting the ventilation rates of greenhouses in high-altitude areas. In addition, correlation analyses were conducted for five variables affecting the ventilation rate: the inlet velocity, the temperature difference between the inside and outside of the greenhouse, the air density difference between the inside and outside of the greenhouse, total indoor radiation, and the internal heat source of the crop, and the coefficients of their correlations with the greenhouse ventilation rate were 1.0, −0.83, −0.72, −0.72, and 0.68, respectively. A natural ventilation rate model for plateau areas was developed, with the ARE, RMSE, and R² between the sample values and fitted values determined to be 4.55%, 0.543 m³/s, and 0.9997, respectively. The model was validated by predicting the greenhouse ventilation rate in winter (3 January 2022), and the ARE, RMSE, and R² of the sample values and predicted values were 9.726%, 8.435 m³/s, and 0.9901, respectively. This study provides a theoretical basis for further research on greenhouse ventilation characteristics in high-altitude areas.

Insulated plastic greenhouses (IPG) were a new type of facility emerging in production in China. The mechanism of construct parameters on the indoor solar radiation deserves further study. A mathematical model that can well describe the spatial and temporal distribution of solar radiation in the greenhouse was established. Based on this model, the effects of multiple construct parameters, such as insulation blanket shading, height–span ratio, greenhouse azimuth, and geographical latitude, on the indoor solar radiation of IPG were quantitatively specified. The results showed that the spatial and temporal distribution of inside solar radiation was highly variable along the span direction of IPG. And by analyzing the simulation data, it was found that for different heights of greenhouses, the corresponding optimal span is different. Therefore, in the construction of greenhouses, the appropriate height–span ratio should be selected according to the planting demand. And by simulating the inside solar radiation under different greenhouse azimuth angles, it was found that accumulated daily solar radiation in the greenhouse reaches the optimum value when the greenhouse azimuth angle is in the range of 0–20°. This paper can provide theoretical guidance for the design and optimization of structure parameters of IPG in China.

Due to the heavy computation load of closed-loop simulations, optimal control of greenhouse climate is usually simulated in an open-loop form to produce control strategies and profit indicators. Open-loop simulations assume the model, measurements, and predictions to be perfect, resulting in too-idealistic indicators. The method of two-time-scale decomposition reduces the computation load, thus facilitating the online implementation of optimal control algorithms. However, the computation time of nonlinear dynamic programming is seldom considered in closed-loop simulations. This paper develops a two-time-scale decomposed closed-loop optimal control algorithm that involves the computation time. The obtained simulation results are closer to reality since it considers the time delay in the implementation. With this algorithm, optimal control of Venlo greenhouse lettuce cultivation is investigated in Lhasa. Results show that compared with open-loop simulations, the corrections in yield and profit indicators can be up to 2.38 kg m⁻² and 11.01 CNY m⁻², respectively, through closed-loop simulations without considering the computation time. When involving the time delay caused by the computation time, further corrections in yield and profit indicators can be up to 0.1 kg m⁻² and 0.87 CNY m⁻², respectively. These conservative indicators help investors make wiser decisions before cultivation. Moreover, control inputs and greenhouse climate states are within their bounds most of the time during closed-loop simulations. This verifies that the developed algorithm can be implemented in real time.

The wind pressure coefficient is essential for calculating the wind loads on greenhouses. The wind pressure on single-span arched greenhouses built in valleys differs from those in plain regions. To promote our understanding of wind characteristics and ensure the structural safety of greenhouses in valley areas, an analysis of the distribution law of wind pressure on greenhouses is required. Firstly, we carried out a survey on greenhouse distribution and undulate terrain distribution near greenhouses in Tibet and measured the air density in Lhasa, Tibet. Then, employing the validated realizable k-ε turbulence model and the verification of grid independence, the wind pressure on greenhouses with different greenhouse azimuths was investigated. According to the survey results, values, such as the distance between the greenhouse and the mountain in addition to the greenhouse azimuth, were also obtained for calculating the wind pressure on greenhouses placed in valleys. A calculation model considering the relationship between the mountain distance and the wind pressure coefficient is proposed, whose results fit well with the results from computational fluid dynamics. The relative errors between the two different results are within 15%. Research shows that there is a canyon wind effect in the valley area, and its effect on wind pressure should be considered in greenhouse design. This research is valuable for the design of plastic greenhouses built in Tibet or other valley regions.