Because pasture meat has a higher market value than meat produced in traditional systems, numerous authentication methods have been developed to distinguish it from meat produced in conventional systems. In temperate European settings and breeds, visual reflectance spectroscopy has proved to be successful. The goal of this study was to use reflectance spectroscopy to certify lamb meat from grassland-based systems in North Africa. This study studied the influence of the feeding system (FS) (P vs. S) and breed (Barbarine, BB; Queue Fine de l'Ouest, QFO; and Noire de Thibar, NT) on the weight and colour of perirenal, subcutaneous, and caudal fat in North African lambs. There were a total of 18 P and 18 S lambs utilised in this experiment. Each breed was represented by six P and six S lambs. The colour and reflectance spectra of different fat tissues were evaluated. The FS had a significant impact on the weights of all fat tissues and all colour parameters of perirenal and subcutaneous fat (P0.01), as well as the redness and yellowness of caudal fat (P0.01) (P0.05; P0.01). In all adipose tissues, S lambs showed more lightness and less redness and yellowness than P lambs. The breed had an effect on the weight, lightness, and redness of perirenal fat, as well as the weight and redness of subcutaneous fat, with a significant interaction with FS for subcutaneous fat data. At wavelengths between 450 and 510 nm (method 1, M1) or between 400 and 700 nm (method 2, M2), the reflectance spectra of perirenal, subcutaneous, and caudal fat was measured. Six P and six S lambs were used to symbolise each breed. Different fat tissues' colour and reflectance spectra were analysed. The FS had a significant effect on the weights of all fat tissues and all perirenal and subcutaneous fat colour parameters (P0.01), as well as the redness and yellowness of caudal fat (P0.01) (P0.05; P0.01). S lambs had more lightness and less redness and yellowness in all adipose tissues than P lambs. The weight, lightness, and redness of perirenal fat, as well as the weight and redness of subcutaneous fat, were all affected by the breed, with a significant interaction with the FS for subcutaneous fat data. Between 450 and 510 nm (method 1, M1) between 400 and 700 nm (method 2, M2). The reflectance spectra of perirenal, subcutaneous, and caudal fat were measured (method 2, M2). The current study uses the vegetation index method, or NDVI, to assess the current state of the Segara Anakan mangrove. The mangrove Segara Anakan has a significant economic value and is important to coastal fishing. However, the status of the Segara Anakan mangrove is severely deteriorating as a result of multiple land uses that are more concerned with economic goals than with mangrove protection, resulting in mangrove land criticality. Mangrove density is one measure of mangrove land's critical level. The goal of this study was to determine the density of mangrove cover in Segara Anakan. The approach utilised was the Normalized Difference Vegetation Index (NDVI), which was based on the interpretation of a satellite picture acquired by Landsat 8 on April 4, 2016, and was categorised using the Guidelines of the United Nations Environment Programme. In 2005, the Forestry Department completed an inventory and identification of critical mangrove land. According to the results of data processing of Landsat 8 images, mangrove crown density in Segara Anakan is categorised into three classes based on NDVI: dense (4,792.11 ha), medium (762.11 ha), and sparse (571.95 ha), with a total area of mangrove of 6,126.28 hectare. Through education and counselling on the mangrove ecosystem and aquatic environment, social capital must be strengthened in order to enhance knowledge of the limits of capacity of mangrove ecosystems and estuary waters.
Author(S) Details
. Ismail
Marine and Fisheries Polytechnic of Sorong, Ministry of Marine Affair and Fisheries, 98411 Sorong City, Indonesia.
. Sulistiono
Department of Aquatic Resources Management, Faculty of Fisheries and Marine Sciences, Bogor Agriculture University, 16680 Bogor, Indonesia.
Sigid Hariyadi
Department of Aquatic Resources Management, Faculty of Fisheries and Marine Sciences, Bogor Agriculture University, 16680 Bogor, Indonesia.
Hawis Madduppa
Department of Marine Science and Technology, Faculty of Fisheries and Marine Sciences, 16680 Bogor, Bogor Agriculture University, Indonesia.
View Book:- https://stm.bookpi.org/RAAVS-V6/article/view/6987
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