Conventional fertilization in the greenhouses of North China used excessive amounts of chemical and organic fertilizer, resulting in soil degradation and severe agricultural non-point source pollution. A nine-year study was conducted on a loamy clay soil in Shijiazhuang, Hebei province, to investigate the effects of reduced-fertilizer input regimes on soil property, bacterial diversity, nitrogen (N) cycling and their interactions. There were four treatments, including high organic + chemical fertilizer application rate and three reduced-fertilizer treatments with swine manure, maize straw or no substitution of 50% chemical N. Treatments with reduced-fertilizer input prevented soil salinization and acidification as in local conventional fertilization after being treated for nine years. In comparison to chemical fertilizer only, swine manure or maize straw substitution maintained higher nutrient availability and soil organic C contents. Fertilizer input reduction significantly increased bacterial richness and shifted bacterial community after nine years, with decisive factors of EC, Olsen P and C/N ratio of applied fertilizer. Soil chemical characteristics (EC, pH and nutrients), aggregation and C/N ratio of applied fertilizer selected certain bacterial groups, as well as N-cycling functions. Reduced-fertilizer input decreased the potential nitrification and denitrification functioning of bacterial community, but only in organic substitution treatments. The results of this study suggested that fertilizer input reduction combined with organic C input has potential in reducing non-point source pollution and increasing N-use efficiency in greenhouse vegetable production in North China.

In response to significant shifts in dietary and lifestyle preferences, the global demand for fruits has increased dramatically, especially for apples, which are consumed worldwide. Growing apple orchards of more productive and higher quality with limited land resources is the way forward. Precise planting age identification and yield prediction are indispensable for the apple market in terms of sustainable supply, price regulation, and planting management. The planting age of apple trees significantly determines productivity, quality, and yield. Therefore, we integrated the time-series spectral endmember and logistic growth model (LGM) to accurately identify the planting age of apple orchard, and we conducted planting age-driven yield prediction using a neural network model. Firstly, we fitted the time-series spectral endmember of green photosynthetic vegetation (GV) with the LGM. By using the four-points method, the environmental carrying capacity (ECC) in the LGM was available, which serves as a crucial parameter to determine the planting age. Secondly, we combined annual planting age with historical apple yield to train the back propagation (BP) neural network model and obtained the predicted apple yields for 12 counties. The results show that the LGM method can accurately estimate the orchard planting age, with Mean Absolute Error (MAE) being 1.76 and the Root Mean Square Error (RMSE) being 2.24. The strong correlation between orchard planting age and apple yield was proved. The results of planting age-driven yield prediction have high accuracy, with the MAE up to 2.95% and the RMSE up to 3.71%. This study provides a novel method to accurately estimate apple orchard planting age and yields, which can support policy formulation and orchard planning in the future.

Soil restoration is a crucial approach to improving plant productivity in orchards with soil degradation, yield reduction, and fruit quality declination in China. A self-invented root-zone ecological restoration practice (RERP) with soil conditioner, or organic fertilizer, was employed in a degraded peach orchard in Beijing in 2020 to investigate the consequent impacts on soil bacterial composition and functionality at soil depths of 0–20 cm and 20–40 cm. Bacterial diversity was sensitive to RERP, especially in subsurface soil. RERP with soil conditioner significantly increased bacterial diversity, and affected abundances of certain genera, such as a significantly increased amount of Bacillus in surface soil and Blastococcus, Microvirga, Nocardioides, and Sphingomonas in subsurface soil. It also significantly affected abundances of bacterial functions related to metabolism in subsurface soil, particularly those with low abundance such as decreased transcription abundance and increased amino acid metabolism abundance. Soil bacterial functions were observably affected by bacterial diversity and composition, particularly in the deep soil layer. RERP affected bacterial functionality via responses of soil bacteria and bacteria-mediated alterations to the changed soil property. Correlation analysis between soil properties, bacterial taxonomy, and bacterial functions revealed that RERP affected bacterial functionality by altering the soil microenvironment with ample nutrients and water supply in root zone. Consequently, shifted bacterial functionality could have a potential in orchard ecosystem services in view of fruit yield and quality. Taken together, RERP had notably positive impacts on soil bacterial diversity and functions, and a prospect of increased plant productivity in the degrade orchard ecosystem.