Seed vigor is an important index to evaluate seed quality in plant species. How to evaluate seed vigor quickly and accurately has always been a serious problem in the seed research field. As a new physical testing method, multispectral technology has many advantages such as high sensitivity and accuracy, nondestructive and rapid application having advantageous prospects in seed quality evaluation. In this study, the morphological and spectral information of 19 wavelengths (365, 405, 430, 450, 470, 490, 515, 540, 570, 590, 630, 645, 660, 690, 780, 850, 880, 940, 970 nm) of alfalfa seeds with different level of maturity and different harvest periods (years), representing different vigor levels and age of seed, were collected by using multispectral imaging. Five multivariate analysis methods including principal component analysis (PCA), linear discriminant analysis (LDA), support vector machine (SVM), random forest (RF) and normalized canonical discriminant analysis (nCDA) were used to distinguish and predict their vigor. The results showed that LDA model had the best effect, with an average accuracy of 92.9% for seed samples of different maturity and 97.8% for seed samples of different harvest years, and the average sensitivity, specificity and precision of LDA model could reach more than 90%. The average accuracy of nCDA in identifying dead seeds with no vigor reached 93.3%. In identifying the seeds with high vigor and predicting the germination percentage of alfalfa seeds, it could reach 95.7%. In summary, the use of Multispectral Imaging and multivariate analysis in this experiment can accurately evaluate and predict the seed vigor, seed viability and seed germination percentages of alfalfa, providing important technical methods and ideas for rapid non-destructive testing of seed quality.

Rhizosphere microorganisms play a pivotal role in biogeochemical cycles, particularly in relation to carbon (C) and nitrogen (N) cycles. However, the impact of stand age on the composition of rhizosphere microbial communities and the abundance involved in C and N cycling remains largely unexplored in restoration ecosystems dominated by shrubs of temperate deserts. This study focuses on revealing changes in microbial composition and functional genes in the rhizosphere soil of Caragana korshinskii after revegetation, as well as their response mechanisms to changes in environmental factors. The alpha diversity of bacteria tended to increase with stand age, whereas that of fungi decreased. The abundance of denitrification; dissimilatory nitrate reduction to ammonium, nitrification, and ammonium assimilation; and C fixation-related gene levels increased with stand age, whereas those related to the degradation of starch, pectin, hemicellulose, cellulose, and aromatics decreased. The parameters MBC, MBN, and TC were the key factors affecting the bacterial community, whereas the fungal community was regulated by TN, EC, pH, and MBC. Stand age indirectly regulated C and N cycling functions of genes through altered soil properties and microbial community structures. This study presents a novel approach to accurately evaluate the C and N cycling dynamics within ecosystems at various stages of restoration.

Gravel mulching is a widely employed strategy for water conservation in arid agricultural regions, with potential implications for soil carbon (C) sequestration and greenhouse gas emissions. However, soil respiration and CO₂-C emissions remain uncertain owing to less consideration of the influence of precipitation patterns and planting age. In this study, we investigated the soil respiration rate (R_soil) and cumulative CO₂-C emission (C_cum), both measured over a period of 72 h, along with soil properties and enzyme activities under different precipitation conditions based on gravel mulching with different planting ages. We analyzed the effects of planting ages on R_soil and C_cum and revealed the underlying mechanisms driving changes in environmental factors on R_soil and C_cum. The results demonstrated that the R_soil reached the maximum value at about 1 h, 0.5 h, and 0.25 h after rewetting in 1, 10, and 20 years of gravel mulching under the condition with 1 mm, 5 mm, and 10 mm of precipitation, respectively, whereas the R_soil exhibited its maximum at about 8 h after soil rewetting under precipitation of 30 mm. The C_cum induced by precipitation pulses tends to decrease with increasing years of gravel mulching. The C_cum was 0.0061 t ha⁻¹ in the 20-year gravel-mulched soil, representing a 53.79% reduction compared to the 1-year gravel-mulched soil. Soil organic matter (SOM), planting ages, and alkaline phosphatase (ALP) were the primary factors influencing the R_soil and C_cum in 0–20 cm, while SOM, planting ages, and soil porosity (AirP) were the key factors affecting the R_soil and C_cum in 20–40 cm. The R_soil and C_cum in the 0–20 cm soil were regulated by soil enzyme activities, while those of 20–40 cm soil were controlled by soil properties. This indicates that the decrease in R_soil and C_cum is caused by soil degradation, characterized by a decrease in SOM and ALP. This study offers a novel insight into the long-term environmental impact of gravel mulching measures in arid areas, which is helpful in providing a theoretical basis for dryland agricultural management. It is imperative to consider the duration of gravel mulching when predicting the potential for C sequestration in arid agricultural areas.

Expansion of photovoltaic infrastructure in arid regions raises concerns about soil microhabitat degradation. Very few studies have systematically compared these recovery alternatives in reshaping the soil fungal communities during early recovery. This study investigated short-term effects (less that two-year recovery) of PV infrastructure and restoration (natural/artificial) on soil fungal diversity and enzymatic activities in Ningxia desert steppe. A total of 243 soil samples were analyzed to assess fungal diversity, composition, enzyme activities, and co-occurrence networks. The restoration method significantly affected soil fungal α-diversity and β-diversity in the experimental solar park. Specifically, at each recovery site, soil depth showed significant effect on fungal α-diversity. However, on a fine scale, artificial restoration significantly increased fungal species richness across soil depths. Ascomycota dominated across different sites, followed by Basidiomycota and Mucoromycota. Shared core genera Fusarium, Mortierella, and Geminibasidium were determined in both recovery sites. Sucrase/phenol oxidase (natural) and catalase/sucrase (artificial) were identified as key fungal drivers according to Random Forest models. Co-occurrence analysis suggested neither artificial restoration nor natural restoration has attained the level of natural habitats. Networks of artificial subsoil and natural topsoil were closest to natural habitat. These results emphasize the impact of restoration and PV shading on fungal communities via spatial heterogeneity and enzyme dynamics during initial recovery stage, providing insights for semi-arid ecosystem management under PV development.