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The aim of this study was to explore the feasibility of quantitatively evaluating a sapphire’s color by analyzing gemstone images. The color characteristics of gemstones through photography and color extraction were accurately captured, and the key color parameters for different color regions of gemstones were extracted. Then, the color of sapphires was simulated by statistical method and function simulation method. The results indicate that the brightness value of the bright area was the highest and the chroma value of the “fire” area was the highest. The chroma (C) of the sapphires was linearly positively correlated with the absolute value of its b value, and the brightness (L) showed a quadratic correlation with its chromaticity parameters (b or C). The function simulation method with an average of b as the main independent variable had a larger standard deviation, which proves that this method has a stronger ability to distinguish the differences in a sapphire’s color. This method can be extended to the color evaluation of other colored gemstones, and it can be used to form a gemstone color evaluation system.

Soil microorganisms are important components of soil ecosystems, and their diversity plays an important role in maintaining their functional stability. Organic fertilizer is an important measure for improving soil fertility in agronomic practice. The effects of organic fertilizer on soil microbial diversity and community structure are different with different degrees of maturation. In this study, uncomposted organic fertilizer (R), high-temperature organic fertilizer (H), cooling organic fertilizer (C), and decomposed organic fertilizer (D) were applied, and the 16S rRNA gene sequences of bacteria in soil were analyzed via high-throughput sequencing technology to understand the effects of organic fertilizer with different degrees of maturation on bacterial diversity and community structure in saline soil. Compared with no fertilization, the uncomposted organic fertilizer, high-temperature organic fertilizer, and decomposed organic fertilizer treatments significantly reduced soil bacterial diversity: the decomposed organic fertilizer treatment significantly reduced soil bacterial richness, the cooling organic fertilizer treatment had no significant effect on soil bacterial diversity and bacterial richness, Proteobacteria representing soil nutrients significantly increased under the cooling organic fertilizer treatment, and the relative abundance of Firmicutes significantly decreased. These four organic fertilizers, with different degrees of maturation, significantly increased the beneficial bacterium Bacillus and nitrile-based degrading bacteria but also significantly increased the potential pathogenicity of the soil, and there was no significant difference between the four treatments. In addition, during a cooling period, the organic fertilizer treatment helped to increase the population of oxidative-stress-tolerant bacteria. The application of organic fertilizer during a cooling period to saline–alkali soil is more helpful in improving its nutrient levels.

The photovoltaic industry is developing rapidly because of its renewable energy and other advantages. However, the installation of this infrastructure may affect soil, vegetation, and carbon dynamics, making it is necessary to carry out vegetation restoration work at a plant’s location in the later stages of its construction. For this reason, three types of artificial vegetation were selected (Pinus sylvestris var. mongolica, Astragalus membra-naceus var. mongholicus and Medicago sativa) as research objects in an ecological photovoltaic power plant in Northern China, to study the changes in soil organic carbon storage (SOCS), carbon:nitrogen ratios (C:N) and C:phosphorus ratios (C:P) at different soil depths and for different vegetation types. Natural vegetation plots undisturbed by the construction of the power plant were used as a control. Seven years after revegetation, we found that the storage and content of soil organic carbon in all three artificial vegetation plots were notably lower compared to the control. Nevertheless, the soil’s organic carbon content for Medicago sativa plots increased was significantly higher by 1.2 g·kg−1 compared to Pinus sylvestris var. mongolica and A. membranaceus var. mongholicus plots, while organic carbon storage increased significantly by 3.55 t·ha and 7.15 t·ha. SOCS, C:N, and C:P concentrations in the 0–20 cm soil layer exhibited a significantly higher value in comparison to those of the 20–40 cm soil layer. As the soil depth increased, all the concentrations declined gradually. Vegetation type and soil depth, as well as their interaction, had a significant impact on soil carbon storage, C:N, and C:P. The study area was restricted by the availability of P. In general, vegetation restoration is a beneficial ecological practice for soil restoration at photovoltaic power stations. It is believed that planting alfalfa can accelerate the improvement of soil carbon with an extension of vegetation recovery time. In order to restore the balance of nutrients for plants, it is necessary to avoid human interference at the later stage, and to supplement phosphorus as soon as possible to minimize phosphorus limitation at the later stage of vegetation growth, which is of great importance to increasing the likelihood of success in reclaiming disturbed land.

This paper focuses on the opportunity to use multiple star trackers to help space situational awareness and space surveillance. Catalogs of space debris around Earth are usually based on ground-based measurements, which rely on data provided by ground-based radar observations and ground-based optical observations. However, space-based observations offer new opportunities because they are independent of the weather and the circadian rhythms to which the ground system is subjected. Consequently, space-based optical observations improve the possibility of space debris detection and cataloging. This work deals with a feasibility study of an innovative strategy, which consists of the use of a star sensor with a dedicated algorithm to run directly on board. This approach minimizes the impact on the original mission of the satellite, and on this basis, it has also the function of space debris monitoring. Therefore, theoretically, every satellite with a star tracker can be used as a space surveillance observer. In this paper, we propose a multi-star space debris detecting and positioning method with constant geocentric observation. Using the multi-star tracker joint positioning method, the angle measurement data of the star tracker is converted into the spatial coordinates of the target. In addition, the Gaussian MMSE difference correction algorithm is used to realize the target positioning of multiple optical observations, and the spatial target position information of the multi-frame images is fused, thus completing the solution of the orbit equation. The simulation results show that the proposed method is sufficient to detect and position space debris. It also demonstrates the necessity and feasibility of cooperative network observation by multiple star trackers.

This paper describes the multilayer voting algorithm, a novel autonomous star identification method for spacecraft attitude determination. The proposed algorithm includes two processes: an initial match process and a verification process. In the initial match process, a triangle voting scheme is used to acquire candidates of the detected stars, in which the triangle unit is adopted as the basic voting unit. During the identification process, feature extraction is implemented, and each triangle unit is described by its singular values. Then the singular values are used to search for candidates of the imaged triangle units, which further improve the efficiency and robustness of the algorithm. After the initial match step, a verification method is applied to eliminate incorrect candidates from the initial results and then outputting the final match results of the imaged stars. Experiments show that our algorithm has more robustness to position noise, magnitude noise, and false stars than the other three algorithms, the identification speed of our algorithm is largely faster than the geometric voting algorithm and optimized grid algorithm. However, it takes more memory, and SVD also seems faster.

The overexploitation of groundwater and the excessive application of nitrogen (N) fertilizer under the intensive double cropping system are responsible for the groundwater level decline and potential contamination in the North China Plain (NCP). Alternative cropping systems have the potential to alleviate current groundwater and N problems in the region, while there are limited studies simultaneously focusing on the impact of a change of cropping systems on crop yields, groundwater consumption, and N leaching. In this study, Field observed experiments of double-cropping system (i.e., winter wheat–summer maize) and mono-cropping system (early sowing maize) were used to calibrate and validate the Root Zone Water Quality Model (RZWQM2). Then, the validated RZWQM2 model was used to evaluate the long-term crop growth and environmental impact under the local winter wheat–summer maize rotation system with practical irrigation (WW-SM_pi) and auto-irrigation (WW-SM_ai), and three alternative cropping systems (single early maize, SEM; winter wheat–summer maize and single early maize, WW-SM-SEM; winter wheat-summer maize and double single early maize, WW-SM-2SEM). The net consumption of groundwater and N leaching under WW-SM_pi were 226.9 mm yr−1 and 79.7 kg ha−1 yr−1, respectively. Under the local rotation system, auto-irrigation could increase crop yields and N leaching. Compared with the WW-SM_ai, the alternative cropping systems, WW-SM-SEM, WW-SM-2SEM, and SEM, significantly decreased the net consumption of groundwater by 49.3%, 63.0%, and 97.8%, respectively (147.5–292.9 mm), and N leaching by 53.5%, 67.5%, and 89.6%, respectively (50.0–83.7 kg ha−1). However, the yields of the three alternative cropping systems were reduced by less than 30% (12.2%, 20.1%, and 29.7%, respectively). The simulated results indicated that appropriately decreasing the planting frequency of winter wheat is an effective approach to reduce groundwater overexploitation and N contamination with a relatively limited reduction in grain yields. The results could provide a scientific basis for cropping system adjustment in guaranteeing sustainable regional water and grain policy.

Yan73, a teinturier (dyer) grape variety in China, is one of the few Vitis vinifera cultivars with red-coloured berry flesh. To examine the tissue-specific expression of genes associated with berry colour in Yan73, we analysed the differential accumulation of anthocyanins in the skin and flesh tissues of two red-skinned grape varieties with either red (Yan73) or white flesh (Muscat Hamburg) based on HPLC-MS analysis, as well as the differential expression of 18 anthocyanin biosynthesis genes in both varieties by quantitative RT-PCR. The results revealed that the transcripts of GST, OMT, AM3, CHS3, UFGT, MYBA1, F3′5′H, F3H1 and LDOX were barely detectable in the white flesh of Muscat Hamburg. In particular, GST, OMT, AM3, CHS3 and F3H1 showed approximately 50-fold downregulation in the white flesh of Muscat Hamburg compared to the red flesh of Yan73. A correlation analysis between the accumulation of different types of anthocyanins and gene expression indicated that the cumulative expression of GST, F3′5′H, LDOX and MYBA1 was more closely associated with the acylated anthocyanins and the 3′5′-OH anthocyanins, while OMT and AM3 were more closely associated with the total anthocyanins and methoxylated anthocyanins. Therefore, the transcripts of OMT, AM3, GST, F3′5′H, LDOX and MYBA1 explained most of the variation in the amount and composition of anthocyanins in skin and flesh of Yan73. The data suggest that the specific localization of anthocyanins in the flesh tissue of Yan73 is most likely due to the tissue-specific expression of OMT, AM3, GST, F3′5′H, LDOX and MYBA1 in the flesh.