Phytopathogens are the main disease agents that promote attack of cocoa plantations in all tropical countries. The similarity of the symptoms caused by different phytopathogens makes the reliable identification of the diverse species a challenge. Correct identification is important in the monitoring and management of these pests. Here we show that matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) in combination with multivariate data analysis is able to rapidly and reliably differentiate cocoa phytopathogens, namely Moniliophthora perniciosa, Phytophthora palmivora, P. capsici, P. citrophthora, P. heveae, Ceratocystis cacaofunesta, C. paradoxa, and C. fimbriata. MALDI-MS reveals unique peptide/protein and lipid profiles which differentiate these phytopathogens at the level of genus, species, and single strain coming from different hosts or cocoa tissues collected in several plantations/places. This fast methodology based on molecular biomarkers is also shown to be sufficiently reproducible and selective and therefore seems to offer a suitable tool to guide the correct application of sanitary defense approaches for infected cocoa plantations. International trading of cocoa plants and products could also be efficiently monitored by MALDI-MS. It could, for instance, prevent the entry of new phytopathogens into a country, e.g., as in the case of Moniliophthora roreri fungus that is present in all cocoa plantations of countries bordering Brazil, but that has not yet attacked Brazilian plantations. Graphical Abstract Secure identification of phytopathogens attacking cocoa plantations has been demonstrated via typical chemical profiles provided by mass spectrometric screening.
Keywords: Ceratocystis spp; Matrix-assisted laser desorption ionization–time-of-flight; Moniliophthora perniciosa; Phytopathogen; Phytophthora spp; Theobroma cacao.