Fresh fruit bruising caused by mechanical impact is the most problematic effect of mechanical postharvest processing of tomatoes. The conventional postharvest process of tomato fruit (Solanum lycopersicum L.) handling was surveyed from harvest to shipping preparation at a farm in Toechon in the Republic of Korea. Acceleration sensors located on the harvest boxes and fruit skin showed that the most severe impact forces (>10 g) occurred while fruit was moved in and out of the harvest box. Next, multivariate analysis was used to evaluate nondestructively the susceptibility of tomatoes to bruising by developing five estimation models incorporating quality factors and the presence of bruising resulting from peak contact forces. Linear regression models, artificial neural network (ANN) regression models, and a logistic regression model were built; the primary dependent variables were the rates of weight loss and firmness loss, and impact-induced bruising. The impact force was controlled by using a pendulum, which produced four levels of impact force on tomato fruit. Increasing the relative humidity (RH) and firmness, and decreasing the temperature and degree of weight loss decreased tomato fruit bruise damage. In addition, the proposed drop–impact measurement technique, with multivariate analysis, can be used to evaluate tomato quality nondestructively.

As environmental pollution and the global population increase, and the COVID-19 pandemic becomes more severe, demands for indoor farming, especially home food gardening, have also increased. However, most research thus far has focused on large-scale food production, with very few studies having been conducted at the household scale. Also, the devices cultivating household crops with control systems in a continuous way, which minimize fluctuations of environmental conditions, have been rarely developed. Therefore, this study aimed to design a household cultivation system for sweet basil that is automatically and continuously controlled by fuzzy logic with a Raspberry Pi4. Three inputs (temperature, humidity, and growth stage) and seven outputs (fan, humidifier, heater 1, heater 2, LED red, green, and blue) were used with six rules, ensuring that three lights operated independently upon three growth stages. Simulation and actual operation were carried out, resulting in an appropriately controlled system that operated with few defects. In the case of an operation of the input variable, temperature and humidity were maintained at an average of 21.24 °C and 75.58%, respectively, and the LED operation for the growth stage was confirmed to be flawless. For verification of the designed fuzzy system, a comparison between the simulation and actual operation was performed to examine differences and identify problems. To this end, Pearson’s correlation coefficients were used, and the direction of correction of the fuzzy logic system was proposed. Through these results, the feasibility of a home cultivation system using fuzzy logic was demonstrated, and it is expected that further studies applying it will be conducted in the future.

Beyond the use of 2D images, the analysis of 3D images is also necessary for analyzing the phenomics of crop plants. In this study, we configured a system and implemented an algorithm for the 3D image reconstruction of red pepper plant (Capsicum annuum L.), as well as its automatic analysis. A Kinect v2 with a depth sensor and a high-resolution RGB camera were used to obtain more accurate reconstructed 3D images. The reconstructed 3D images were compared with conventional reconstructed images, and the data of the reconstructed images were analyzed with respect to their directly measured features and accuracy, such as leaf number, width, and plant height. Several algorithms for image extraction and segmentation were applied for automatic analysis. The results showed that the proposed method showed an error of about 5 mm or less when reconstructing and analyzing 3D images, and was suitable for phenotypic analysis. The images and analysis algorithms obtained by the 3D reconstruction method are expected to be applied to various image processing studies.

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