Search Results (3)

Early-stage frost damage in citrus fruits is difficult to detect because external symptoms are often weak or absent, hindering intelligent robotic sorting in postharvest scenarios. To address this challenge, this study proposes a robotic multimodal tactile sensing approach inspired by human mechanoreception for frost-damage detection during grasping. A robotic gripper equipped with a $6\times 6$ pressure matrix sensor and a piezoelectric vibration sensor was used to capture complementary tactile cues during standardized fruit handling, enabling the perception of subtle mechanical changes associated with early frost injury. Using 240 Citrus reticulata ‘Hong Mei Ren’ fruits under controlled experimental conditions, a Transformer-based multimodal fusion network was developed to jointly model pressure and vibration sequences for binary classification of normal and frost-damaged fruits. Across repeated stratified random-split experiments, the proposed method achieved a mean classification accuracy of 93.1%. Comparative experiments showed that the fusion model outperformed representative sequence-learning baselines, and ablation analysis confirmed that pressure–vibration fusion was more effective than either single modality alone. Attention-based temporal attribution further revealed that the most informative cues were concentrated in the initial contact and early loading stages, indicating the importance of early transient mechanical responses for frost-damage discrimination. Overall, the proposed approach demonstrates the feasibility of grasp-based robotic frost-damage detection under controlled experimental conditions. Full article

Citrus cultivation represents one of the major economic pillars of the Valencian Community (Spain). Frost events pose a significant threat to these plantations, resulting in substantial economic losses. This study aims to assess the frequency and intensity of frost occurrences in the region from 2004 to 2023, using Meteosat Second Generation satellite imagery. These images provide daily land surface temperature data at 15 min intervals. Frost days were defined as those when temperatures fell below −2.3 °C, the threshold at which orange fruits become susceptible to damage, with different temperature thresholds applied to estimate varying levels of crop damage. Frost duration was also analyzed to classify event intensity and its potential impact on citrus crops. Annual comparisons revealed a decline in both the severity and frequency of frosts, particularly in cases of “moderate” and “intense” damage, supporting forecasts of increased regional aridity and suggesting new opportunities for expanding citrus cultivation to higher altitudes. When compared with farmers’ records, this study’s methodology proves effective in assessing frost impact and offers potential use for winter crop insurance. Validation was conducted using in situ data from the Spanish National Meteorological Agency (AEMET). Full article

Lemon is the most sensitive citrus fruit to cold. Therefore, it is of capital importance to detect and avoid temperatures that could damage the fruit both when it is still in the tree and in its subsequent commercialization. In order to rapidly identify frost damage in this fruit, a system based on the electrochemical impedance spectroscopy technique (EIS) was used. This system consists of a signal generator device associated with a personal computer (PC) to control the system and a double-needle stainless steel electrode. Tests with a set of fruits both natural and subsequently frozen-thawed allowed us to differentiate the behavior of the impedance value depending on whether the sample had been previously frozen or not by means of a single principal components analysis (PCA) and a partial least squares discriminant analysis (PLS-DA). Artificial neural networks (ANNs) were used to generate a prediction model able to identify the damaged fruits just 24 hours after the cold phenomenon occurred, with sufficient robustness and reliability (CCR = 100%). Full article