Although low cost red-green-blue-depth (RGB-D) cameras are factory calibrated, to meet the accuracy requirements needed in many industrial applications proper calibration strategies have to be applied. Generally, these strategies do not consider the effect of temperature on the camera measurements. The aim of this paper is to evaluate this effect considering an Orbbec Astra camera. To analyze this camera performance, an experimental study in a thermal chamber has been carried out. From this experiment, it has been seen that produced errors can be modeled as an hyperbolic paraboloid function. To compensate for this error, a two-step method that first computes the error and then corrects it has been proposed. To compute the error two possible strategies are proposed, one based on the infrared distortion map and the other on the depth map. The proposed method has been tested in an experimental scenario with different Orbbec Astra cameras and also in a real environment. In both cases, its good performance has been demonstrated. In addition, the method has been compared with the Kinect v1 achieving similar results. Therefore, the proposed method corrects the error due to temperature, is simple, requires a low computational cost and might be applicable to other similar cameras.

The growing demand for sustainable food systems has increased consumer interest in plant-based burger products. However, burgers currently available on the market differ considerably in their ingredient composition, processing degree and formulation strategies, which may influence consumer perceptions and acceptance. This study investigated consumer evaluation of one conventional beef burger and four plant-based burgers with distinct ingredient profiles. A total of 66 Spanish consumers participated in a multi-method study combining eye-tracking, evaluation of expected liking and ingredients healthiness, and laddering methodology.The results showed that ingredient-related information played a central role in consumer evaluations. Participants displayed different visual attention patterns depending on the evaluation criterion, suggesting that distinct packaging elements were used to assess product healthiness, sustainability, degree of processing, and purchase intention. Ingredients such as olive oil, quinoa, kale, and tofu generally received more favourable evaluations, whereas additives and technological ingredients tended to be viewed less positively. The findings also revealed that perceptions of healthiness and sustainability were not always associated with greater purchase intention.Laddering analysis indicated that consumer preferences were influenced by both ingredient-related perceptions and expected sensory experiences. While ingredient composition contributed to healthiness perception, transparency, and quality of life, product rejection was mainly associated with anticipated negative sensory outcomes. The results highlight that consumer acceptance of burgers is shaped by the interaction between clean-label cues and sensory expectations.These findings contribute to a better understanding of how consumers evaluate conventional and plant-based burgers and provide useful insights for the development and communication of plant-based products.