Optimal fertilization is an important measure for managing cultivated grasslands, and a necessary means for maintaining the nutrient balance, yield, and quality of grassland ecosystems. This study aimed to explore the effects of organic fertilizers on the production performance and nutritional quality of cultivated grasslands in karst areas. Two types of monocultured cultivated grasslands (i.e., and ) were employed as the research objects, and a randomized block design was adopted to investigate the effects of five fertilization gradients on the forage height, coverage, yield, and nutritional quality of the cultivated grasslands. According to the results, the plant height, coverage, and yield of first presented an increasing trend, then decreased with increasing fertilization gradient, with a peak at 20-30 t/hm fertilization gradient. The height, coverage, and yield of increased gradually with increase in fertilization gradient, and peaked at 40 t/hm. Meanwhile, the crude protein (CP) and ether extract (EE) contents of both grassland types displayed first presented an increasing trend, then decreased with increasing fertilization gradient, and peaked at 10-30 t/hm fertilization gradient. The neutral detergent fiber (NDF) and acidic detergent fiber (ADF) contents of presented "N-shaped" and "M-shaped" change trends with increasing fertilization gradient, while those of showed "V-shaped" and "M-shaped" change trends, reaching minimum values under fertilization gradients of 30 and 20 t/hm, respectively. Year, fertilization, and year × fertilization (Y×F) significantly affected the plant heights, coverages, dry/fresh weight ratios, and yields of and . The contribution of coverage to the subordinate function of was greatest at a fertilization gradient of 20 t/hm. Meanwhile, the subordinate function values of the height and coverage of increased gradually with increasing fertilization gradient, but the difference in the subordinate function value of height was only 0.09%-0.18% under the fertilization gradient of 20-40 t/hm. Evaluation of forage nutrition revealed 10-30 t/hm and 20-30 t/hm as the optimal organic fertilizer application rates for and , respectively.
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http://dx.doi.org/10.3389/fpls.2023.1228621 | DOI Listing |
Sci Data
January 2025
University of Antwerp - imec - IDLab, Department of Mathematics, Antwerp, 2000, Belgium.
As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fill existing data gaps by employing two machine learning models, eXtreme Gradient Boosting and HistGradientBoosting algorithms to produce precise country-level predictions of nitrogen (N), phosphorus pentoxide (PO), and potassium oxide (KO) application rates. Subsequently, we created a comprehensive dataset of 5-arcmin resolution maps depicting the application rates of each fertilizer for 13 major crop groups from 1961 to 2019.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated the stochasticity of soil microbes and multitrophic networks through amplicon sequencing, assessed soil community functions related to carbon (C), N, phosphorus (P), and sulfur (S) cycling, and characterized the dominant bacterial life history strategies via metagenomics along a gradient of increasing pesticide diversity under two N addition levels.
View Article and Find Full Text PDFJ Environ Qual
January 2025
Department of Earth and Ocean Sciences, University of North Carolina Wilmington, Wilmington, North Carolina, USA.
Eastern North Carolina has been subjected to widespread water quality degradation for decades, notably throughout the Cape Fear River Watershed, owing largely to the magnitude of concentrated animal feeding operations (CAFOs) in the region. Long-term nutrient monitoring data from numerous locations throughout southeastern North Carolina have shown significantly elevated organic nitrogen (Org-N) concentrations starting around the year 2000-a concerning development, as labile Org-N can stimulate algal blooms and subsequent bacterial production, thus enhancing eutrophication in freshwater systems. By measuring the stable isotope signatures (δC, δN) of particulate organic matter sampled from a range of southeastern North Carolina waters, the predominant sources to the observed Org-N loadings were elucidated.
View Article and Find Full Text PDFSci Rep
December 2024
Reproductive Medicine Department, Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Currently applicable models for predicting live birth outcomes in patients who received assisted reproductive technology (ART) have methodological or study design limitations that greatly obstruct their dissemination and application. Models suitable for Chinese couples have not yet been identified. We conducted a retrospective study by using a database includes a total of 11,938 couples who underwent in vitro fertilization (IVF) treatment between January 2015 and December 2022 in a medical institution of southwest China Yunnan province.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Institute of Biotechnology, Jiaxing Academy of Agricultural Science, Jiaxing, China.
Nitrogen is essential for rice growth and yield formation, but traditional methods for assessing nitrogen status are often labor-intensive and unreliable at high nitrogen levels due to saturation effects. This study evaluates the effectiveness of flavonoid content (Flav) and the Nitrogen Balance Index (NBI), measured using a Dualex sensor and combined with machine learning models, for precise nitrogen status estimation in rice. Field experiments involving 15 rice varieties under varying nitrogen application levels collected Dualex measurements of chlorophyll (Chl), Flav, and NBI from the top five leaves at key growth stages.
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