Assessment of fish trophic ecology in natural environments is imperative to understand biological and ecological requirements, supporting the management and conservation of populations and environments. There are several methods available to assess fish diets, generically divided in noninvasive approaches, such as underwater observations, and invasive approaches, such as analyses of lipid biomarkers, stable isotopes and stomach contents. Each one has application assumptions and conditions that must be aligned with study objectives and methodological criteria, assuring results robustness and allowing comparability among different studies. This review addresses the advantages and limitations of these methods, highlighting those applied for stomach analysis (SA). This work presents complete updated review concerning qualitative and quantitative methods applied to SA: sixty equations were reviewed comprising four formulae to value stomachs per se and, for stomach content analysis, eight single indices, fifteen composite indices and thirty-three equations related to modeling approaches. The review presents different potentialities associated to these methods, standardizes distinct names applied to a same method, and provides clarifications on confusion sources due to the use of same names in distinct methods, a source of scientific mistakes detected in the specialized literature.

Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.