The potential of near infrared spectroscopy (NIRS) to measure the chemical composition of aquaculture solid waste
|Author(s)||Lopes Galasso Helena1, 2, 3, Callier Myriam1, Bastianelli Denis4, Blancheton Jean-Paul1, Aliaume Catherine2|
|Affiliation(s)||1 : Univ Montpellier, CNRS, IFREMER, Ifremer,UMR MARBEC,IRD, Chemin Maguelone, F-34250 Palavas Les Flots, France.
2 : Univ Montpellier, CNRS, IFREMER, UMR MARBEC,IRD, Pl Eugene Bataillon, F-34095 Montpellier, France.
3 : Minist Educ Brazil, CAPES Fdn, BR-70040020 Brasilia, DF, Brazil.
4 : CIRAD, UMR SELMET, Syst Elevage Mediterraneens & Tropicaux, F-34398 Montpellier, France.
|Source||Aquaculture (0044-8486) (Elsevier Science Bv), 2017-07 , Vol. 476 , P. 134-140|
|WOS© Times Cited||8|
|Keyword(s)||Near infrared spectroscopy, Fish farm waste, Faeces, Dicentrarchus labrax, Chemical composition|
In aquaculture, it is extremely important to determine the composition of fish farm waste to evaluate its potential impacts and to improve its reuse. Near-infra red spectroscopy (NIRS), an alternative to standard chemical analytical techniques, is a quick non-invasive method to assess physical and chemical composition, reducing the cost of routine analysis. We developed NIRS calibration models for organic matter (OM), total organic carbon (TOC), total organic nitrogen (TON), the carbon/nitrogen ratio (C/N), total phosphorus (TP) and the lipid content of marine fish particulate waste. To obtain a wide range of compositions of fish waste, decomposition time, feed loss, and inter-specific variations were taken into account. The NIRS calibration models were built using three sub-datasets: in Scenario 1) the calibration was species-specific, including only seabass waste (SeabassWaste), in Scenario 2), the calibration included data from two other species (MultiSpeciesWaste) and in Scenario 3), the general calibration included all data as well as simulation of extreme feed loss (up to 50%) (Faeces&Feed). All calibrations performed using either dried or wet samples gave equations with high coefficients of determination (R2) and reasonably low standard error of cross validation (SECV) values for all parameters tested, except for TP due the high proportion of mineral P.