Browsing by Author "Qi Y"

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    Alfalfa adapts to soil nutrient surplus and deficiency by adjusting the stoichiometric characteristics of main organs and nutrient reabsorption
    (BioMed Central Ltd, 2025-12-01) Sun Y; Hui J; Yang K; Wei K; Wang X; Cartmill AD; López IF; Qi Y; Ma C; Zhang Q
    Accurate nutrient diagnosis is essential for simulating alfalfa (Medicago sativa L.) yield and optimizing resource-use efficiency under diverse soil nutrient conditions. However, limited knowledge exists about how fertilization impacts soil–plant nutrient stoichiometric constraints, especially in nutrient-deficient gray desert soils. This study conducted a field experiment with four nitrogen (N) application rates: 0, 60, 120, and 180 kg N∙ha−1 and four phosphorus (P) application rates: 0, 50, 100, and 150 kg P2O5∙ha−1. We assessed changes in the nutrient limitation characteristics of alfalfa and identified its primary driving factors, focusing on soil nutrient perspectives, nutrient distribution in main organs (leaves, shoots, and roots) and nutrient resorption. The results demonstrated that fertilization increased N and P concentrations in various alfalfa organs while reducing carbon (C) content. A strong synergy was observed in nutrient concentrations across the different alfalfa organs. With increasing application of single-nutrient fertilizers, the C:N and C:P ratios in alfalfa organs decreased, while the N:P ratio stabilized under conditions of sufficient or co-limiting soil N and P. Alfalfa N:P ratios under different fertilization treatments were 4.89–5.46 in roots, 6.19–8.45 in stems, and 9.10–15.16 in leaves. The C:N and C:P ratios were significantly negatively correlated with alfalfa yield, but the relationship between the N:P ratio and yield was not statistically significant. Soil nutrient status positively influenced N and P concentrations in leaves, stems, and roots, however, their effect on stoichiometric ratios was primarily mediated through indirect effects on corresponding organ-level nutrients. Moreover, soil nutrients directly or indirectly explained 98% of the variation in nutrient resorption in leaves. In conclusion, fertilization indirectly affects the stoichiometric characteristics of alfalfa organs via soil nutrients. Adjusting fertilizer nutrient ratios can mitigate nutrient limitations in both soil and alfalfa, providing valuable insights for fertilizer formulation, timing of fertilizer application, and fertilization application strategies. Highlights 1.Fertilization alters the C-N-P stoichiometry of the soil–plant system. 2.The stoichiometric characteristics and ratios of different organs exhibit a certain degree of synergy. 3.Stoichiometric ratios can represent nutrient limitation to a certain extent. 4.Soil nutrient changes affect the stoichiometric characteristics and ratios of alfalfa.
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    Can the use of digital technology improve the cow milk productivity in large dairy herds? Evidence from China's Shandong Province
    (Frontiers Media S.A., 2022-12-02) Qi Y; Han J; Shadbolt NM; Zhang Q; Naseer MAUR
    Introduction: Improving milk productivity is essential for ensuring sustainable food production. However, the increasing difficulty of supervision and management, which is associated with farm size, is one of the major factors causing the inverse relationship between size and productivity. Digital technology, which has grown in popularity in recent years, can effectively substitute for manual labor and significantly improve farmers' monitoring and management capacities, potentially addressing the inverse relationship. Methods: Based on data from a survey of farms in Shandong Province in 2020, this paper employs a two-stage least squares regression model to estimate the impact of herd size on dairy cow productivity and investigate how the adoption of digital technology has altered the impact of herd size on dairy cow productivity. Results: According to the findings, there is a significant and negative impact of herd size on milk productivity for China's dairy farms. By accurately monitoring and identifying the time of estrus, coupled with timely insemination, digital technology can mitigate the negative impact of herd size on milk productivity per cow. Discussion: To increase dairy cow productivity in China, the government should promote both small-scale dairy farming and focus on enhancing management capacities of farm operators, as well as large-scale dairy farms and increase the adoption of digital technologies.
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    Evaluation of the accuracy of the IDvet serological test for Mycoplasma bovis infection in cattle using latent class analysis of paired serum ELISA and quantitative real-time PCR on tonsillar swabs sampled at slaughter
    (Public Library of Science (PLoS), 2023-05-11) Marquetoux N; Vignes M; Burroughs A; Sumner E; Sawford K; Jones G; Qi Y
    Mycoplasma bovis (Mbovis) was first detected in cattle in New Zealand (NZ) in July 2017. To prevent further spread, NZ launched a world-first National Eradication Programme in May 2018. Existing diagnostic tests for Mbovis have been applied in countries where Mbovis is endemic, for detecting infection following outbreaks of clinical disease. Diagnostic test evaluation (DTE) under NZ conditions was thus required to inform the Programme. We used Bayesian Latent Class Analysis on paired serum ELISA (ID Screen Mycoplasma bovis Indirect from IDvet) and tonsillar swabs (qPCR) for DTE in the absence of a gold standard. Tested samples were collected at slaughter between June 2018 and November 2019, from infected herds depopulated by the Programme. A first set of models evaluated the detection of active infection, i.e. the presence of Mbovis in the host. At a modified serology positivity threshold of SP%> = 90, estimates of animal-level ELISA sensitivity was 72.8% (95% credible interval 68.5%-77.4%), respectively 97.7% (95% credible interval 97.3%-98.1%) for specificity, while the qPCR sensitivity was 45.2% (95% credible interval 41.0%-49.8%), respectively 99.6% (95% credible interval 99.4%-99.8%) for specificity. In a second set of models, prior information about ELISA specificity was obtained from the National Beef Cattle Surveillance Programme, a population theoretically free-or very low prevalence-of Mbovis. These analyses aimed to evaluate the accuracy of the ELISA test targeting prior exposure to Mbovis, rather than active infection. The specificity of the ELISA for detecting exposure to Mbovis was 99.9% (95% credible interval 99.7%-100.0%), hence near perfect at the threshold SP%=90. This specificity estimate, considerably higher than in the first set of models, was equivalent to the manufacturer's estimate. The corresponding ELISA sensitivity estimate was 66.0% (95% credible interval 62.7%-70.7%). These results confirm that the IDvet ELISA test is an appropriate tool for determining exposure and infection status of herds, both to delimit and confirm the absence of Mbovis.