Unraveling the core microbial succession during the moromi fermentation of cantonese soy sauce: An amplicon sequencing approach - Hongbiao Tang; Mouyong Zou; Xingui Zhu; Ge Tan; Liqiong Guo; Junfang Lin (Food Research International, 2026)

Experimental and theoretical study on the in-situ thermal tensile strength and gasification kinetics of iron coke: Dual-activation mechanism of iron-catalyzed gasification - Jie Wang; Wei Wang; Xuheng Chen; Junfang Bao; Ruilin Lin; Runsheng Xu (Fuel, 2025)

The effects of oil type on the properties of oil-water interfaces and W1/O/W2 double emulsions stabilized by Pleurotus geesteranus protein particles - Tinghui Pei; Bo Lin; Juntong Li; Qianwang Zheng; Zhiwei Ye; Liqiong Guo; Junfang Lin; Yuan Zou (Food Hydrocolloids, 2025)

Anti-obesity effects of the high molecular weight Cordyceps militaris polysaccharide CMP40 in high-fat diet mice - Yingyin Wu; Yifeng Zhang; Shishi Huang; Weifan Xie; Genan Huang; Yuan Zou; Zhiwei Ye; Tao Wei; Junfang Lin; Qianwang Zheng (Food Bioscience, 2024)

Fabrication and characterization of W1/O/W2 double emulsions stabilized with Pleurotus geesteranus protein particles via one-step emulsification - Manhong Jin; Chuwen Li; Menghuan Ma; Qianwang Zheng; Liqiong Guo; Junfang Lin; Zhiwei Ye; Yuan Zou (Food Hydrocolloids, 2024)

Radiometric assessment of OLCI, VIIRS, and MODIS using fiducial reference measurements along the Atlantic Meridional Transect - Silvia Pardo; Gavin H. Tilstone; Robert J.W. Brewin; Giorgio Dall'Olmo; Junfang Lin; Francesco Nencioli; Hayley Evers-King; Tânia G.D. Casal; Craig J. Donlon (Remote Sensing of Environment, 2023)

A review on recent advances in LED-based non-thermal technique for food safety: current applications and future trends - Xinpeng Yu; Peng Zheng; Yuan Zou; Zhiwei Ye; Tao Wei; Junfang Lin; Liqiong Guo; Hyun-Gyun Yuk; Qianwang Zheng (Critical Reviews in Food Science and Nutrition, 2023)

Distribution, Source Identification, and Output flux of Barium in Surface Waters in the Sanjiangyuan Region and Qilian Mountain Region of Tibetan Plateau - Zuxiu Yao; Guangyi Sun; Li Lin; Wei Zhang; Junfang Zhang; Lingjian Gao; Lihai Shang (Bulletin of Environmental Contamination and Toxicology, 2023)

Development and optimization of LED systems for surface fungal decontamination of fresh produce - Xinpeng Yu; Weihong Deng; Ziqian Zhang; Yuan Zou; Tao Wei; Junfang Lin; Liqiong Guo; Hyun-Gyun Yuk; Zhiwei Ye; Qianwang Zheng (Postharvest Biology and Technology, 2023)

Evaluating historic and modern optical techniques for monitoring phytoplankton biomass in the Atlantic Ocean - Robert J. W. Brewin; Jaime Pitarch; Giorgio Dall’Olmo; Hendrik J. van der Woerd; Junfang Lin; Xuerong Sun; Gavin H. Tilstone (Frontiers in Marine Science, 2023)
Traditional measurements of the Secchi depth ( z SD ) and Forel-Ule colour were collected alongside modern radiometric measurements of ocean clarity and colour, and in-situ measurements of chlorophyll-a concentration (Chl-a), on four Atlantic Meridional Transect (AMT) cruises. These data were used to evaluate historic and modern optical techniques for monitoring Chl-a, and to evaluate remote-sensing algorithms. Historic and modern optical measurements were broadly consistent with current understanding, with Secchi depth inversely related to Forel-Ule colour and to beam and diffuse attenuation, positively related to the ratio of blue to green remote-sensing reflectance and euphotic depth. The relationship between Secchi depth and Forel-Ule on AMT was found to be in closer agreement to historical relationships when using data of the Forel-Ule colour of infinite depth, rather than the Forel-Ule colour of the water above the Secchi disk at half z SD . Over the range of 0.03-2.95 mg m -3 , Chl-a was tightly correlated with these optical variables, with the ratio of blue to green remote-sensing reflectance explaining the highest amount of variance in Chl-a (89%), closely followed by the Secchi depth (85%) and Forel-Ule colour (71-81%, depending on the scale used). Existing algorithms that predict Chl-a from these variables were evaluated, and found to perform well, albeit with some systematic differences. Remote sensing algorithms of Secchi depth were in good agreement with in-situ data over the range of values collected (8.5 - 51.8 m, r 2 >0.77, unbiased root mean square differences around 4.5 m), but with a slight positive bias (2.0 - 5.4 m). Remote sensing algorithms of Forel-Ule agreed well with Forel-Ule colour data of infinite water ( r 2 >0.68, mean differences <1). We investigated the impact of environmental conditions and found wind speed to impact the estimation of z SD , and propose a path forward to include the effect of wind in current Secchi depth theory. We discuss the benefits and challenges of collecting measurements of the Secchi depth and Forel-Ule colour and propose future directions for research. Our dataset is made publicly available to support the research community working on the topic.

Early Warning of Harmful Algal Bloom Risk Using Satellite Ocean Color and Lagrangian Particle Trajectories - Junfang Lin; Peter I. Miller; Bror F. Jönsson; Michael Bedington (Frontiers in Marine Science, 2021)
Combining Lagrangian trajectories and satellite observations provides a novel basis for monitoring changes in water properties with high temporal and spatial resolution. In this study, a prediction scheme was developed for synthesizing satellite observations and Lagrangian model data for better interpretation of harmful algal bloom (HAB) risk. The algorithm can not only predict variations in chlorophyll-a concentration but also changes in spectral properties of the water, which are important for discrimination of different algal species from satellite ocean color. The prediction scheme was applied to regions along the coast of England to verify its applicability. It was shown that the Lagrangian methodology can significantly improve the coverage of satellite products, and the unique animations are effective for interpretation of the development of HABs. A comparison between chlorophyll-a predictions and satellite observations further demonstrated the effectiveness of this approach: r 2 = 0.81 and a low mean absolute percentage error of 36.9%. Although uncertainties from modeling and the methodology affect the accuracy of predictions, this approach offers a powerful tool for monitoring the marine ecosystem and for supporting the aquaculture industry with improved early warning of potential HABs.

Sensitivity of a Satellite Algorithm for Harmful Algal Bloom Discrimination to the Use of Laboratory Bio-optical Data for Training - Victor Martinez-Vicente; Andrey Kurekin; Carolina Sá; Vanda Brotas; Ana Amorim; Vera Veloso; Junfang Lin; Peter I. Miller (Frontiers in Marine Science, 2020)
Early detection of dense harmful algal blooms (HABs) is possible using ocean colour remote sensing. Some algorithms require a training dataset, usually constructed from satellite images with a priori knowledge of the existence of the bloom. This approach can be limited if there is a lack of in situ observations, coincident with satellite images. A laboratory experiment collected biological and bio-optical data from a culture of Karenia mikimotoi , a harmful phytoplankton dinoflagellate. These data showed characteristic signals in chlorophyll-specific absorption and backscattering coefficients. The bio-optical data from the culture and a bio-optical model were used to construct a training dataset for an existing statistical classifier. MERIS imagery over the European continental shelf were processed with the classifier using different training datasets. The differences in positive rates of detection of K. mikimotoi between using an algorithm trained with purely manually selected areas on satellite images and using laboratory data as training was overall <1%. The difference was higher, <15%, when using modeled optical data rather than laboratory data, with potential for improvement if local average chlorophyll concentrations are used. Using a laboratory-derived training dataset improved the ability of the algorithm to distinguish high turbidity from high chlorophyll concentrations. However, additional in situ observations of non-harmful high chlorophyll blooms in the area would improve testing of the ability to distinguish harmful from non-harmful high chlorophyll blooms. This approach can be expanded to use additional wavelengths, different satellite sensors and different phytoplankton genera.

A novel technology: microfluidic devices for microbubble ultrasound contrast agent generation - Hangyu Lin; Junfang Chen; Chuanpin Chen (Medical & Biological Engineering & Computing, 2016)

Phosphocreatine protects endothelial cells from oxidized low-density lipoprotein-induced apoptosis by modulating the PI3K/Akt/eNOS pathway - Anil Ahsan; Guozhu Han; Junfang Pan; Shumin Liu; Arshad Ahmed Padhiar; Peng Chu; Zhengwu Sun; Zonghui Zhang; Bin Sun; Jingjun Wu; Aisha Irshad; Yuan Lin; et al. (Apoptosis, 2015)

Gender differences in affective sharing and self–other distinction during empathic neural responses to others’ sadness - Pinchao Luo; Junfang Wang; Yan Jin; Shanshan Huang; Mengshu Xie; Lin Deng; Juncong Fang; Xiaochun Zheng; Xiaoying Chen; Yue Li; Yijie Jiang; Xifu Zheng (Brain Imaging and Behavior, 2015)

Production of antibacterial peptide from bee venom via a new strategy for heterologous expression - Chunsheng Hou; Liqiong Guo; Junfang Lin; Linfeng You; Wuhua Wu (Molecular Biology Reports, 2014)