Institut für Agrartechnik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/19

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Investigating crude sesame oil sedimentation and its monitoring using Laser Backscattering Imaging (LBI)
(2023) Wu, Zhangkai; Romuli, Sebastian; Intani, Kiatkamjon; Müller, Joachim
Sesame oil is a food and energy resource that is not used enough. Sedimentation of crude oil after pressing can remove particles and happens regardless of the producer’s intention. However, sedimentation of crude plant oil and its sensing technology are rarely studied. This research studied crude sesame oil sedimentation and monitored it with low-cost laser backscattering imaging (LBI). In the discontinuous measurement, a 30-day sedimentation was conducted with oil samples sent to the lab LBI system for image capture. A scattering spot and an increasing Tyndall effect along the light path were seen. In the continuous measurement, an LBI system was mounted on a sedimentation tank for 30 days. The sedimentation curve, scattering images, and oil properties were checked. The sedimentation speed was about −7 mm/h, then less than −2 mm/h. The image features correlated well with the sedimentation interface height (R2 = 0.97) when the height was above −100 mm. The oil-particle-related properties (ash content, phosphorus content, carbon residue, and total contamination) dropped by at least 87%, water content decreased by 90%, and the oxidation-related properties (oxidation stability, γ-tocotrienol, δ-tocopherol, γ-tocopherol, and acid value) changed less significantly. The crude sesame oil sedimentation had two stages: diluted and hindered sedimentation. This research can help improve sedimentation tank and LBI system design and prevent unwanted sedimentation.
Modeling and spatiotemporal mapping of water quality through remote sensing techniques: A case study of the Hassan Addakhil dam
(2021) El Ouali, Anas; El Hafyani, Mohammed; Roubil, Allal; Lahrach, Abderrahim; Essahlaoui, Ali; Hamid, Fatima Ezzahra; Muzirafuti, Anselme; Paraforos, Dimitrios S.; Lanza, Stefania; Randazzo, Giovanni
With its high water potential, the Ziz basin is one of the most important basins in Morocco. This paper aims to develop a methodology for spatiotemporal monitoring of the water quality of the Hassan Addakhil dam using remote sensing techniques combined with a modeling approach. Firstly, several models were established for the different water quality parameters (nitrate, dissolved oxygen and chlorophyll a) by combining field and satellite data. In a second step, the calibration and validation of the selected models were performed based on the following statistical parameters: compliance index R2, the root mean square error and p-value. Finally, the satellite data were used to carry out spatiotemporal monitoring of the water quality. The field results show excellent quality for most of the samples. In terms of the modeling approach, the selected models for the three parameters (nitrate, dissolved oxygen and chlorophyll a) have shown a good correlation between the measured and estimated values with compliance index values of 0.62, 0.56 and 0.58 and root mean square error values of 0.16 mg/L, 0.65 mg/L and 0.07 µg/L for nitrate, dissolved oxygen and chlorophyll a, respectively. After the calibration, the validation and the selection of the models, the spatiotemporal variation of water quality was determined thanks to the multitemporal satellite data. The results show that this approach is an effective and valid methodology for the modeling and spatiotemporal mapping of water quality in the reservoir of the Hassan Addakhil dam. It can also provide valuable support for decision-makers in water quality monitoring as it can be applied to other regions with similar conditions.

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