The dynamic predator–prey relations in the food web are vital for understanding the function and structure of ecosystems. Dietary estimation is a research hotspot of quantitative ecology, providing key insights into predator–prey relationships. One of the most promising approaches is quantitative fatty acid signature analysis (QFASA), which is the first generation of statistical tools to estimate the quantitative trophic predator–prey relationships by comparing the fatty acid (FA) signatures among predators and their prey. QFASA has been continuously widely applied, refined and extended since its introduction. This article reviewed the research progress of QFASA from development and application. QFASA reflects the long-term diet of predator, and provides the quantitative dietary composition of predator, but it is sensitive to the metabolism of predator. The calibration coefficients (CCs) and the FA subset are two crucial parameters to explain the metabolism of predators, but the incorrect construction or improper use of CCs and the FA subset may cause bias in dietary estimation. Further study and refinement of the QFASA approach is needed to identify recommendations for which CCs and subsets of FA work best for different taxa and systems.

In the process of pond culture, the usage of an aeration device can increase dissolved oxygen density and form a decent circulation which facilitates the collection of sludge. Acoustic Doppler Velocimeter (ADV) has been widely used to monitor the flow velocity, however, factors such as bubbles and suspended particles can affect the correlation coefficient and signal-to-noise ratio of ADV, which leads to the existence of outliers in velocity data. This study constructs the three-dimensional rousseeuw phase-space (3DRPS) method by optimizing the phase space threshold method and robust estimation method through two-step filtering and three-dimensional simultaneous measurement, where the outliers close to the real value can be detected more accurately and the iterative process can be reduced more effectively. The results show that the detection rate of the optimized 3DRPS method is approximately 99%. It is a promising method that effectively improves the accuracy of outlier detection and greatly reduces the phenomenon of over processing.