Yinfei Qian

Dr. Yinfei Qian

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2020 in Field Crops Research
Verified
Journal Article
Closed access
XGXianjiao Guan
Xianjiao Guan
XCXianmao Chen
Xianmao Chen
CQCaifei Qiu
Caifei Qiu
YQYinfei Qian
Yinfei Qian
JCJin Chen
Jin Chen
CPChunrui Peng
Chunrui Peng

19 October 2024 in Global Change Biology
Verified
Journal Article
Closed access
YUYves Uwiragiye
Yves Uwiragiye
JWJing Wang
Jing Wang
YHYuanyuan Huang
Yuanyuan Huang
LWLiangping Wu
Liangping Wu
JZJiake Zhou
Jiake Zhou
CMChristoph Müller
Christoph Müller

17 July 2024 in Agriculture
Verified
Journal Article
Open access
PDF file
JHJuan Hu
Juan Hu
GXGuan Xian-jiao
Guan Xian-jiao
XLXihuan Liang
Xihuan Liang
BWBinqiang Wang
Binqiang Wang
XCXianmao Chen
Xianmao Chen
JCJin Chen
Jin Chen
Straw returning has gradually been adopted as an effective approach to address the serious degradation of farmland. However, the carbon/nitrogen (C/N) ratio of rice straw is generally too high for microorganisms to decompose the organic materials and release nutrients, which may minimize the benefits of straw returning to the agricultural production system. This study aimed to investigate the effects of straw returning on rice production and propose optimum nitrogen (N) management for early rice production under a straw returning system. The total N fertilizer that was evaluated was 165 kg N ha-1, urea (46% N), applied in different proportions in three stages of rice cultivation: basal, tillering, and panicle. Using no straw returning with the N fertilizer ratio of basal:tillering:panicle = 5:2:3 treatment (T1) as the control, four different N fertilizer ratios of basal:tillering:panicle, including 5:2:3 (T2), 5:2:2 (T3), 5:4:1 (T4), and 5:5:0 (T5) were set under straw returning. The return of straw decreased the available N in the soil at the tillering stage, and impeded root growth and the crop canopy from establishing, which decreased the effective panicles by 10.1% compared with that of T1, limiting the increases in rice grain yield. Increasing the N fertilizer ratio 10–20% (T3 and T4) at the tillering stage effectively increased the content of soil ammonium and nitrate nitrogen, improved the root growth, and increased the root activities by 16.0–40.5% at the tillering stage. As a result, the effective panicle number increased by 5.1–16.2%. Among these, T4 treatment maximized the benefits of straw returning the most. Additionally, increasing the N fertilizer ratio at the tillering stage increased the shoot uptake across the early rice growing season and synchronized crop N uptake with the accumulation of carbon assimilates, which enhanced the crop growth rate and increased the rice yield by 13.5–25.1%. It is concluded that increasing the N fertilizer ratio by 20% at the tillering stage is a promising strategy to increase the availability of N in the phases of high demand for this nutrient.

15 September 2022 in Agronomy
Verified
Journal Article
Open access
PDF file
YQYinfei Qian
Yinfei Qian
XGXianjiao Guan
Xianjiao Guan
CSCaihong Shao
Caihong Shao
CQCaifei Qiu
Caifei Qiu
XCXianmao Chen
Xianmao Chen
CPChunrui Peng
Chunrui Peng
Micro-nano bubble (MNB) irrigation can effectively improve the hypoxia stress caused by conventional irrigation and shows great potential in plant development, yield improvement, and saving of water and fertilizer, and has been recognized as a new and high-efficiency technology in crop planting. However, former research on MNB concentration had no clear segmentation, and other MNB concentrations can achieve better or worse effects. This remains to be further explored in order to explore the optimal concentration of MNBs for the yield and nitrogen absorption and utilization of the double cropping rice. With early rice Ganxin203 and late rice WufengyouT025 as the experimental cultivars, the effects of MNBs on growth, yield, and nitrogen absorption and utilization of the potted double cropping rice were analyzed by setting three concentrations of MNBs (LM, low concentration; MM, middle concentration; HM, high concentration), compared with the ordinary running water (CK). Compared with CK, grain yield of the early rice under the MNB treatment increased by 4.84~10.95% and the late rice increased by 6.10~14.31%. It was found that the higher the concentration of the MNBs, the higher the yield of the rice. This is due to that the MNBs improved the tiller-bearing rate, increased the SPAD and Pn values of the flag leaves in the whole growth period, slowed down the drop of the leaf SPAD and Pn from heading stage to maturity, increased the number of the adventitious roots, improved the α-NA oxidation of the root, and simultaneously promoted the nitrogen accumulation, absorption, and utilization. The HM treatment obtained the best benefits, and the effect of the MNBs on the late rice was better than the early rice.

15 January 2023 in Agronomy
Verified
Journal Article
Open access
PDF file
JLJin Li
Jin Li
Kailou LIUKailou LIU
Kailou LIU
JCJi Chen
Ji Chen
JXJiang Xie
Jiang Xie
Yu JiangYu Jiang
Yu Jiang
JCJin Chen
Jin Chen
Long-term intensive use of mineral fertilizers in double rice-cropping systems has led to soil acidification and soil degradation. Manure fertilization was suggested as an alternative strategy to mitigate soil degradation. However, the effects of long-term mineral and manure fertilization on rice grain yield, yield stability, soil organic carbon (SOC) content, soil total nitrogen (TN) content, and the underlying mechanisms are unclear. Based on a long-term experiment established in 1981 in southern China, we compared four treatments: no fertilizer application (Control); application of nitrogen–phosphorus–potassium (NPK); NPK plus green manure in early rice (M1); and M1 plus farmyard manure in late rice and rice straw return in winter (M2). Our results showed that 37 years of NPK, M1, and M2 significantly increased rice grain yield by 54%, 46%, and 72%, and yield stability by 22%, 17%, and 9%, respectively. M1 and M2 significantly increased SOC content by 39% and 23% compared to Control, respectively, whereas there was no difference between Control and NPK. Regarding soil TN content, it was significantly increased by 8%, 46%, and 20% by NPK, M1, and M2, respectively. In addition, M2 significantly increased bacterial OTU richness by 68%, Chao1 index by 79%, and altered the bacterial community composition. Changes in soil nutrient availability and bacterial Simpson index were positively correlated with the changes in grain yield, while shifts in bacterial community were closely related to yield stability. This study provides pioneer comprehensive assessments of the simultaneous responses of grain yield, yield stability, SOC and TN content, nutrient availability, and bacterial community composition to long-term mineral and manure fertilization in a double rice-cropping system. Altogether, this study spanning nearly four decades provides new perspectives for developing sustainable yet intensive rice cultivation to meet growing global demands.

16 December 2024 in Frontiers in Plant Science
Verified
Journal Article
Open access
PDF file
PSPeihua Shi
Peihua Shi
YWYuan Wang
Yuan Wang
CYCongfei Yin
Congfei Yin
KFKaiqing Fan
Kaiqing Fan
YQYinfei Qian
Yinfei Qian
GCGui Chen
Gui Chen
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. Incremental analysis was performed to quantify saturation effects, revealing that chlorophyll measurements saturated at high nitrogen levels, limiting their reliability. In contrast, Flav and NBI remained sensitive across all nitrogen levels, accurately reflecting nitrogen status. Machine learning models, particularly random forest and extreme gradient boosting, achieved high prediction accuracy for leaf and plant nitrogen concentrations (R2 > 0.82), with SHAP analysis identifying NBI and Flav from the top two leaves as the most influential predictors. By combining Flav and NBI measurements with machine learning, this approach effectively overcomes chlorophyll-based saturation limitations, enabling precise nitrogen estimation across diverse conditions and offering practical solutions for improved nitrogen management in rice cultivation.