Apparatus and method for predicting sugar content on basis of moisture content and specific heat of fruit

Abstract

The present invention relates to a system for predicting sugar content on the basis of the moisture content of a fruit. An apparatus for predicting sugar content on the basis of the moisture content and specific heat of a fruit according to an embodiment of the present invention comprises: a heating unit for applying heating to both surfaces of the fruit; a temperature sensor unit for measuring the surface temperature of the fruit; a moisture prediction unit for collecting data on the temperature change over time of the fruit after the fruit is heated by the heating unit and calculating the specific heat of the fruit on the basis of the collected temperature change data to predict the moisture content; and a sugar content prediction unit for predicting the sugar content of the fruit on the basis of the predicted moisture content.

Description

Device and method for predicting sugar content based on moisture content and specific heat of fruit

[0001] The present invention relates to a system for predicting sugar content based on the moisture content of fruit, and more specifically, to a technology for estimating moisture content by measuring temperature changes on the surface of fruit and predicting sugar content accordingly. By applying heat to both surfaces to monitor temperature changes, sugar content can be accurately predicted through the relationship between moisture and specific heat.

[0002] Recently, fruit quality evaluation technology has focused primarily on non-destructive measurement methods. In the agriculture and food industries, technology capable of accurately measuring internal quality factors such as moisture content, sugar content, and acidity is crucial for supplying high-quality fruits that meet consumer demands. In particular, as sugar content is a key factor determining fruit freshness and taste, there is a growing demand for technologies that can accurately measure and predict it. Accordingly, technologies such as optical analysis, ultrasound, electromagnetic waves, and near-infrared (NIR) spectroscopy, which enable non-destructive and rapid measurements, have advanced; these technologies are used to evaluate internal quality without damaging the fruit's external appearance.

[0003] Existing technologies for predicting and measuring sugar content consist of near-infrared (NIR) spectroscopy, electronic noses, ultrasonic testing, and optical methods. NIR spectroscopy is a non-destructive technique that predicts moisture, sugar content, and acidity by transmitting near-infrared light through fruit and analyzing the reflected light; it is used with high accuracy in large-scale agricultural facilities and research laboratories. Electronic noses predict sugar content and aroma by detecting volatile substances emitted from fruit using chemical sensors, but they suffer from accuracy issues that fluctuate depending on environmental changes. Ultrasonic testing predicts sugar and moisture content by identifying differences in internal density, but it is difficult to guarantee consistent reliability due to distortions in the internal structure. Optical methods evaluate quality by shining lasers or visible light onto the fruit surface and analyzing the reflected light, but accuracy can vary depending on the surface condition.

[0004] Existing technologies have several drawbacks. First, high-precision technologies such as near-infrared spectroscopy require expensive equipment and complex calibration processes, placing a significant financial burden on small-scale farms and distributors. Second, optical methods are sensitive to the surface condition of the fruit, leading to reduced measurement accuracy depending on factors such as dust, moisture, and surface reflectivity. Third, existing technologies fail to adequately account for internal moisture or specific heat characteristics, making it difficult to accurately predict sugar content in fruits with inconsistent moisture levels. Finally, electronic nose and ultrasonic inspection technologies are sensitive to external environmental changes, such as temperature and humidity, making it difficult to obtain reliable data.

[0005] Consequently, existing fruit sugar content prediction technologies have limitations in terms of cost and accuracy, and there is a growing need for simple and precise measurement methods.

[0006] The present invention aims to enable accurate prediction of sugar content based on the moisture content of fruit.

[0007] The present invention aims to enable the prediction of internal moisture and sugar content by evaluating the quality of fruit in a non-destructive manner.

[0008] The present invention aims to provide a highly reliable sugar content measurement system that is not sensitive to the surface condition of the fruit or the external environment.

[0009] The present invention aims to enable the precise evaluation of fruit quality using simple equipment without the need for expensive conventional equipment.

[0010] The present invention aims to provide a technology that can be practically used in agricultural and distribution fields by predicting the sugar content of fruits based on the relationship between moisture and specific heat.

[0011] A sugar content prediction device based on the moisture content and specific heat of a fruit according to one embodiment may include a heating treatment unit that applies heating to both surfaces of a fruit, a temperature sensor unit that measures the surface temperature of the fruit, a moisture prediction unit that collects temperature change data over time after being heated by the heating treatment unit and calculates the specific heat of the fruit based on the collected temperature change data to predict the moisture content, and a sugar content prediction unit that predicts the sugar content of the fruit based on the predicted moisture content.

[0012] According to one embodiment, the heat treatment unit may include a heating device capable of applying different temperatures to both surfaces of the fruit.

[0013] According to one embodiment, the temperature sensor unit can measure the surface temperature of the fruit at specific time intervals after heating begins.

[0014] The data collection module according to one embodiment can simultaneously collect temperature change data on both surfaces of the fruit.

[0015] The data collection module according to one embodiment can predict the moisture content of the fruit by calculating the slope of the temperature change over time.

[0016] According to one embodiment, the moisture prediction unit calculates the specific heat of the fruit based on the amount of temperature change and can estimate the moisture content based on the correlation between the specific heat and the moisture content.

[0017] The sugar content prediction unit according to one embodiment can predict the sugar content by utilizing the correlation that the sugar content decreases as the moisture content of the fruit increases.

[0018] The heat treatment unit according to one embodiment includes an infrared heater and can apply heat to the surface of the fruit in a non-contact manner.

[0019] The temperature sensor unit according to one embodiment includes an infrared temperature sensor unit and can measure the temperature of the fruit surface in a non-contact manner.

[0020] The data collection module according to one embodiment can estimate moisture content and sugar content in real time by monitoring changes in the surface temperature of the fruit in real time.

[0021] According to one embodiment, the sugar content prediction unit can predict the sugar content by analyzing the difference between the internal moisture content and the surface moisture content of the fruit through the calculation of specific heat based on temperature change.

[0022] A method for predicting sugar content based on the moisture content and specific heat of a fruit according to one embodiment may include the steps of applying heat to both surfaces of a fruit, measuring the temperature of both surfaces of the fruit for a certain period of time after heating, calculating the specific heat based on the measured temperature change to predict the moisture content of the fruit, and predicting the sugar content of the fruit based on the predicted moisture content.

[0023] The step of applying heat to both surfaces of a fruit according to one embodiment includes the step of setting the temperature of the heat applied to both surfaces differently, and the step of predicting the moisture content of the fruit by calculating the specific heat based on the measured temperature change may include the step of predicting the moisture content based on the temperature change data according to the temperature difference.

[0024] The step of predicting the moisture content of a fruit by calculating the specific heat based on the measured temperature change according to one embodiment may include the step of calculating the slope of the temperature change amount to calculate the specific heat, and estimating the moisture content using the correlation between the specific heat and the moisture content.

[0025] The step of predicting the sugar content of a fruit based on the predicted moisture content according to one embodiment may include the step of estimating the moisture content and sugar content of the fruit in real time by processing temperature change data measured for a specific time after heating in real time.

[0026] According to one embodiment, sugar content can be predicted more accurately by measuring the change in specific heat according to the moisture content of the fruit.

[0027] According to one embodiment, the internal quality of the fruit can be evaluated through a non-destructive method, allowing for quality inspection to be performed while preserving freshness and taste.

[0028] According to one embodiment, consistent sugar content prediction is possible because it is not significantly affected by the external environment or the surface condition of the fruit.

[0029] According to one embodiment, the moisture content and sugar content of fruit can be easily measured with simple equipment without a complex calibration process.

[0030] According to one embodiment, through a system based on changes in moisture content and specific heat, it is possible to reduce costs and enable efficient quality control in the agricultural and distribution processes.

[0031] FIG. 1 is a drawing illustrating a sugar content prediction device according to one embodiment.

[0032] FIG. 2 is a diagram illustrating a sugar content prediction experiment according to one embodiment.

[0033] FIG. 3 is a diagram illustrating a sugar content prediction experiment according to another embodiment.

[0034] Figure 4 is a diagram illustrating the results of a sugar content prediction experiment.

[0035] Figure 5 is a diagram illustrating the temperature change according to density when different temperatures are applied at both T1 (left column) and T3 (midpoint) for the temperatures of T1 (left column), T2 (right column), and T3 (midpoint).

[0036] Figure 6 is a diagram illustrating the temperature change according to density when different temperatures are applied at both T2 (right column) and T3 (midpoint) for the temperatures of T1 (left column), T2 (right column), and T3 (midpoint).

[0037] FIG. 7 is a diagram illustrating a method for predicting sugar content according to one embodiment.

[0038] Specific structural or functional descriptions of embodiments according to the concept of the present invention disclosed herein are provided merely for the purpose of explaining embodiments according to the concept of the present invention, and embodiments according to the concept of the present invention may be implemented in various forms and are not limited to the embodiments described herein.

[0039] Embodiments according to the concept of the present invention may be subject to various modifications and may take various forms; therefore, embodiments are illustrated in the drawings and described in detail in this specification. However, this is not intended to limit the embodiments according to the concept of the present invention to specific disclosed forms, and includes modifications, equivalents, or substitutions that fall within the spirit and scope of the present invention.

[0040] Terms such as "first" or "second" may be used to describe various components, but said components should not be limited by said terms. For the sole purpose of distinguishing one component from another, for example, without departing from the scope of rights according to the concept of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component.

[0041] When it is stated that one component is "connected" or "joined" to another component, it should be understood that while it may be directly connected or joined to that other component, there may also be other components in between. Conversely, when it is stated that one component is "directly connected" or "directly joined" to another component, it should be understood that there are no other components in between. Expressions describing the relationships between components, such as "between," "exactly between," or "directly adjacent to," should be interpreted in the same way.

[0042] The terms used herein are used merely to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0043] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the present invention pertains. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0044]

[0045] Hereinafter, embodiments will be described in detail with reference to the attached drawings. However, the scope of the patent application is not limited or restricted by these embodiments. Identical reference numerals in each drawing indicate identical components.

[0046] FIG. 1 is a drawing illustrating a sugar content prediction device (100) according to one embodiment.

[0047] A sugar content prediction device (100) according to one embodiment may include a heat treatment unit (110), a temperature sensor unit (120), a moisture prediction unit (130), a sugar content prediction unit (140), and a control unit (150).

[0048] First, the heat treatment unit (110) is a device that applies heat to the surface of the fruit, and induces a temperature change by applying heat to both surfaces of the fruit. The heat treatment unit (110) can apply different temperatures, thereby allowing for precise observation of changes in surface temperature. In one embodiment, an infrared heater is used to apply heat to the surface of the fruit in a non-contact manner, which can effectively transfer heat while preventing damage to the fruit.

[0049] The temperature sensor unit (120) measures the surface temperature of the fruit after applying heat in the heat treatment unit (110). The temperature sensor unit (120) monitors the surface temperature of the fruit in real time using a non-contact infrared temperature sensor unit. The temperature sensor unit (120) simultaneously measures temperature changes occurring on both surfaces of the fruit and collects temperature change data by measuring the temperature at regular time intervals. This data is subsequently used as important basic data for moisture prediction.

[0050] The moisture prediction unit (130) calculates the specific heat of the fruit based on temperature change data measured by the temperature sensor unit (120) and predicts the moisture content based on the specific heat value. The moisture prediction unit (130) calculates the correlation between the specific heat and the moisture content according to the amount of temperature change to accurately estimate the moisture content inside the fruit. In particular, it accurately determines the moisture content by using a method that predicts the moisture content by calculating the slope of the temperature change.

[0051] The sugar content prediction unit (140) predicts the sugar content of the fruit based on the moisture content data calculated by the moisture prediction unit (130). The correlation between moisture content and sugar content is based on the principle that the higher the moisture content, the lower the sugar content becomes, and through this, the sugar content based on moisture content can be predicted. The sugar content prediction unit (140) processes the predicted moisture content in real time to immediately predict the sugar content of the fruit.

[0052] The control unit (150) is a central processing unit that controls and adjusts the heat treatment unit (110), the temperature sensor unit (120), the moisture prediction unit (130), and the sugar content prediction unit (140). The control unit (150) processes data collected by each component in real time and calculates specific heat and moisture content by analyzing temperature change data collected from both surfaces of the fruit. Additionally, the control unit (150) ultimately predicts the sugar content based on this data. The control unit (150) performs all measurement and prediction processes in real time to quickly provide the sugar content and moisture content of the fruit.

[0053] In a specific embodiment, different temperatures are applied to both surfaces of the fruit using infrared heaters, and the surface temperature is measured at regular intervals after heating through a temperature sensor. Subsequently, the control unit calculates the specific heat of the fruit based on the collected temperature data, and the moisture prediction unit (130) estimates the moisture content based on this specific heat value. Finally, the sugar content prediction unit (140) predicts the sugar content of the fruit using the moisture content data. This process is non-destructive and processed in real time, allowing for the rapid and accurate prediction of sugar content and moisture content without damaging the fruit.

[0054] FIG. 2 is a drawing (200) illustrating a sugar content prediction experiment according to one embodiment.

[0055] In the sample surface temperature measurement step, the surface temperature of the fruit selected as a sample is measured using an infrared temperature sensor. The infrared temperature sensor accurately measures the temperature of the fruit surface in a non-contact manner, serving as foundational data for observing and analyzing temperature changes during the subsequent heating stage. In this process, the fruit surface temperature can be measured using an infrared thermometer.

[0056] The second step is the heating process, in which the experimenter applies heat to both surfaces of the fruit using a hot air blower. The heating time is 1 minute and 40 seconds per side, and the distance between the sample and the heating tool is adjusted to 4–5 cm. During this process, infrared heating is used to apply heat non-contactually, which allows for the effective transfer of temperature without damaging the fruit. The image in the middle shows the process of applying heat to the fruit using the heating device.

[0057] In the third step, the sugar content of the fruit is measured after heating. The experimenter cuts the fruit into pieces and measures the sugar content using a refractometer. The refractometer analyzes the sugar content of the juice extracted from the fruit to provide an accurate value. This serves as important data for predicting sugar content based on changes in moisture content and specific heat characteristics before and after heating.

[0058] In the fourth step, the weight of the heated fruit is measured. The initial weight of the fruit before drying is accurately measured and used to compare and analyze changes in moisture content after drying. This is an essential process for determining how the fruit's moisture content affects sugar content and specific heat. The weight of the fruit can be measured using an electronic scale.

[0059] The final step is the drying process, in which the fruit is dried in a dryer at a temperature of 100°C for 24 hours. This process removes the moisture content of the fruit, allowing the moisture content to be calculated by comparing it to the weight in the dried state. The moisture content is accurately analyzed through the difference in weight before and after drying.

[0060] Through this experimental procedure, the correlation between changes in fruit surface temperature, moisture content, and sugar content can be clearly analyzed, and fruit quality can be evaluated in a non-destructive manner.

[0061] FIG. 3 is a drawing (300) illustrating a sugar content prediction experiment according to another embodiment.

[0062] Figure 3 is a diagram showing the step-by-step process of another sugar content prediction experiment according to one embodiment. The experiment in Figure 3 explains the process of measuring the moisture content and sugar content of a fruit through various processes.

[0063] In the first step, heat can be applied to three sides of the fruit's surface. This step involves applying heat to specific parts of the fruit to induce a temperature change in those areas, and the heating device used can utilize a non-contact heat source. By observing the temperature change after heating, basic data is obtained to analyze the internal physical characteristics of the fruit.

[0064] The second step is the thermal imaging analysis process. Using a thermal imaging camera, temperature changes in the fruit are visually recorded, and the heat distribution is monitored in real time. This process visually displays the temperature differences of the fruit and allows for the analysis of whether the temperature is evenly distributed or concentrated in specific areas. The thermal imaging frequency is set to 1 Hz, enabling rapid and continuous observation.

[0065] In the third step, sampling can be performed by dividing the fruit into uniform sizes. The fruit is evenly divided to prepare the pieces to be used in the experiment, which are then utilized for accurate weight measurement and drying experiments in subsequent stages. The sampling process is a crucial step that ensures the experiment is conducted under identical conditions for all pieces.

[0066] In the fourth step, the sampled fruit slices can be divided into two for use in the experiment. This process allows for finer division of the slices, enabling experiments on various parts of the fruit. It increases the precision of the experiment and obtains data from various parts.

[0067] The fifth step is the process of measuring the sugar content of the sampled fruit pieces. The experimenter can measure the sugar content of each fruit piece using a refractometer. A refractometer is a device that measures sugar content by analyzing the liquid extracted from the fruit, and the data obtained from this process can be analyzed by comparing it with changes in moisture content after drying.

[0068] In the sixth step, the weight of the sampled fruit pieces is measured. This process records the weight of the fruit before drying and provides important data for estimating moisture content by comparing it with the weight change after drying.

[0069] The seventh step involves arranging the fruit pieces in the dryer for drying. It is important to prepare the pieces so that they are evenly distributed, and to arrange them carefully to prevent them from overlapping or being pressed against each other during drying. This ensures a uniform result after drying.

[0070] The eighth step is the drying process, during which the fruit can be dried at 100°C for 24 hours. During this process, the moisture inside the fruit evaporates, resulting in a dried state. After 24 hours, the fruit is completely dried, and the moisture content can be calculated based on the difference in weight before and after drying.

[0071] The final step is measuring the weight of the fruit pieces after drying. The weight of the dried fruit is measured again to compare the difference before and after drying. This allows for the calculation of the fruit's moisture content, and based on the results, the correlation between the fruit's sugar content and moisture content is analyzed.

[0072] This experimental procedure precisely measures the moisture content of fruits and analyzes the relationship between moisture content and sugar content, providing important data for predicting sugar content.

[0073] Figure 4 is a diagram illustrating the results of a sugar content prediction experiment.

[0074] Figure 4 is a diagram visually illustrating the results of a fruit sugar content prediction experiment, consisting of a graph and a data table explaining the correlation between Brix values ​​(indicators of sugar content) and temperature changes. This diagram explains how temperature changes vary depending on the sugar content of the fruit and shows the temperature change patterns according to the sugar content (Brix values) of each experimental sample.

[0075] The graph in Figure 4 shows the temperature change trends of samples with different Brix values ​​over time. The three main Brix values ​​used in the graph are 18.1, 15.2, and 12.3, with each line representing the temperature change of the fruit sample corresponding to that Brix value. Brix 18.1 represents the sample with the highest sugar content, and the temperature change is relatively gradual. This indicates that fruits with higher sugar content have lower moisture content and consequently lower specific heat, resulting in rapid temperature changes. Brix 15.2 represents a sample with medium sugar content, and the temperature change pattern falls between that of Brix 18.1 and Brix 12.3. This sample possesses moderate specific heat and moisture content, causing the temperature change to proceed at a moderate rate. Brix 12.3 represents the sample with the lowest sugar content, and the temperature change is the slowest. As moisture content increases, the specific heat increases, the temperature change proceeds more slowly, and the slope is characterized by the gentlest slope.

[0076] According to Figure 4, for Brix 18.1, the temperature changes rapidly over time, showing that the temperature change occurs quickly in samples with low specific heat. For Brix 15.2, the temperature change proceeds at a moderate level, and the slope of the temperature change is moderate. For Brix 12.3, the temperature change is the slowest, and it can be seen that the temperature change occurs more slowly in samples with higher specific heat.

[0077] An important result that can be observed in Figure 4 is that as sugar content increases (i.e., the higher the Brix value), the moisture content decreases, and consequently, the specific heat decreases, leading to rapid temperature changes. Conversely, as sugar content decreases (i.e., the higher the moisture content), the specific heat increases, resulting in slower temperature changes. Based on this pattern and the correlation between temperature change and specific heat, a methodology is presented to predict the sugar content of fruit.

[0078] Figure 5 is a diagram illustrating the temperature change according to density when different temperatures are applied at both T1 (left column) and T3 (midpoint) for the temperatures of T1 (left column), T2 (right column), and T3 (midpoint).

[0079] This diagram explains the temperature change according to density based on data obtained through experiments.

[0080] The X-axis represents the temperature difference between T1 (left column) and T3 (midpoint). This difference is a value measured based on the difference in heat applied to both surfaces of the fruit, signifying the temperature gap between the left and midpoints. A higher value on the X-axis indicates a greater temperature difference between the two points, serving as an important indicator for observing how the heated heat spreads into the interior of the fruit.

[0081] The Y-axis represents the slope of the temperature change. The slope signifies the rate of temperature change over time due to the temperature difference, illustrating how heat diffuses into the fruit. A higher Y-axis value indicates a faster rate of temperature change, while a lower value indicates a slower rate of temperature change. The slope value depends on density and specific heat; as density increases, the rate of heat transfer slows down, resulting in a smaller slope value.

[0082] The data marked with dots in the diagram represents the actual measured slope values ​​according to the temperature difference between T1 and T3. Each dot represents an individual data point obtained from the experiment, visualizing the distribution of slopes according to the temperature difference. The line in the diagram is a regression line based on this data, expressing the correlation between the slope and the temperature difference as a linear equation. The equation of the regression line is expressed as y = 0.01x + 3.18, which means that while the slope increases as the temperature difference increases, the change is relatively insignificant. Since the slope remains almost constant, it can be seen that as density increases, the heat transfer rate slows down, resulting in minimal temperature changes.

[0083] Figure 5 is a diagram visually illustrating the temperature change pattern according to density. It can be seen that as the temperature difference between T1 and T3 increases, the slope of the temperature change increases, but the magnitude of the change is not large. This means that as the density and specific heat of the fruit increase, the rate of heat transfer slows down, so the temperature change is not large even if there is a temperature difference between the two points. In other words, it can be concluded that as the density increases, heat transfer occurs slowly, resulting in a gradual change in the internal temperature of the fruit.

[0084] Figure 6 is a diagram illustrating the temperature change according to density when different temperatures are applied at both T2 (right column) and T3 (midpoint) for the temperatures of T1 (left column), T2 (right column), and T3 (midpoint).

[0085] Figure 6 is a diagram showing the change in slope according to the temperature difference between T2 (right column) and T3 (midpoint), showing experimental results analyzing the temperature change pattern according to density. This diagram visually illustrates how the temperature change varies depending on density and specific heat when different temperatures are applied at two points.

[0086] The X-axis represents the temperature difference between T2 (right column) and T3 (midpoint). T2 represents the temperature applied from the right heat source, and T3 represents the temperature measured at the midpoint; this value quantifies the temperature difference between these two points. A larger temperature difference indicates that less heat is lost while the heat applied from the source is transferred to the midpoint. As the X-axis value increases, the temperature difference between T2 and T3 becomes more significant.

[0087] The Y-axis represents the slope of the temperature change, indicating the amount of temperature change over time due to the temperature difference. The slope explains how quickly heat diffuses into the interior of an object; a larger slope value indicates a more rapid change in temperature. The slope varies depending on density and specific heat; as density increases, the slope becomes smaller, and heat transfer occurs more slowly.

[0088] The data marked with dots in the diagram represent slope values ​​measured according to the temperature difference between T2 and T3. These are individual data points collected from the experiment, visually illustrating the slope distribution based on the temperature difference obtained under each experimental condition. Additionally, the regression line plotted based on the data points indicates the correlation between the temperature difference and the slope. The equation of the regression line is y = 0.01x + 3.10, which shows that the slope increases slightly as the temperature difference increases, but the change is minimal. This regression line suggests that as density increases, the heat transfer rate slows down, and the slope remains constant.

[0089] Figure 6 shows that heat tends to be transferred more rapidly as the temperature difference between T2 (right column) and T3 (midpoint) increases. However, according to the experimental results, the change in the slope is relatively small as the temperature difference increases. This demonstrates that the rate of heat transfer varies significantly depending on the density and specific heat of the fruit, and that as density increases, heat transfer slows down and the slope of the temperature change becomes gentler. Therefore, this experiment analyzes the effects of density and specific heat on heat transfer and provides a pattern of temperature change according to the internal characteristics of the fruit.

[0090] The series of experiments conducted in this invention focuses on presenting a methodology for predicting the sugar content of fruit by analyzing the effects of an object's density and specific heat on heat transfer and temperature change. In the experiments, different temperatures were applied to both ends of a 0.2m long object to observe temperature changes and slopes. In each experiment, a section where the temperature change slope remained within 5% was identified, and through this, the correlation between heat transfer and temperature change was analyzed.

[0091] First, temperature changes based on density acted as a significant variable in the experiment. As a result of measuring the temperatures at T1 (left column), T2 (right column), and T3 (midpoint), the temperature gradients between T3 and T1 and between T3 and T2 were found to be identical. This implies that the heat applied from both sides spreads evenly according to the density of the object. The higher the density of the object, the slower the rate of heat transfer, and the more gradual the temperature change occurs. Furthermore, as density increases, the difference in the rate of temperature change decreases, and the temperature gradient remains constant. In other words, for a high-density object, heat transfer occurs slowly even if there is a large temperature difference between the left and right sides, resulting in a constant temperature gradient.

[0092] In addition, the effect of an object's specific heat on temperature change was confirmed in the experiment. Objects with high moisture content have a high specific heat; this means that while they absorb more thermal energy, the rate of temperature change is slower. When moisture content is high, the temperature change is small, resulting in a lower slope, which implies lower sugar content. Conversely, when moisture content is low, the specific heat is small, leading to rapid heat transfer and a larger temperature change, resulting in a higher slope. This relationship clearly demonstrates the correlation between moisture content and sugar content.

[0093] In addition, the heat transfer mechanism according to changes in T3 (midpoint temperature) was analyzed. As the value of T3 increases, heat spreads more rapidly, yet the slopes measured on the left and right sides remained constant. This implies that while the value of T3 affects the heat transfer rate, it does not alter the physical characteristics of heat transfer itself. Even if the value of T3 changes, the heat transfer mechanism remains unchanged, and only the time required for heat transfer to reach equilibrium varies.

[0094] In conclusion, density and specific heat significantly influence the rate of heat transfer and the pattern of temperature change. When density or specific heat is high, the rate of heat transfer slows down, and temperature changes occur gradually. Fruits with high water content have a high specific heat, resulting in slow temperature changes and consequently lower sugar content. Conversely, fruits with low water content have a low specific heat, leading to rapid temperature changes and higher sugar content. Based on these experimental results, sugar content can be predicted by analyzing the specific heat and density of fruits.

[0095] FIG. 7 is a diagram illustrating a method for predicting sugar content according to one embodiment.

[0096] The step of applying heat to both sides of the fruit's surface is the first step inducing a temperature change. During this process, heat is transferred into the interior of the fruit. When applying heat, different temperatures can be set for each side of the fruit, and the heat transfer rate and specific heat are analyzed. Non-contact heating methods, such as infrared heat sources, can be used, and it is important to apply heat without damaging the fruit.

[0097] In the step of measuring the temperature change of the fruit over time, temperature fluctuations occurring on both surfaces of the fruit are measured for a certain period after heating. Non-contact sensors, such as infrared temperature sensors, are used to measure temperature changes, and the amount of temperature change resulting from the heat applied from both sides is collected. Based on this data, basic information necessary to estimate the specific heat and moisture content of the fruit is obtained. The temperature data measured over a certain period is subsequently used to calculate moisture content and specific heat.

[0098] In the step of estimating the moisture content of fruit based on measured temperature changes, the slope of the measured temperature change is calculated to determine the specific heat of the fruit, and the moisture content is estimated based on this. The internal moisture content of the fruit can be predicted by analyzing the correlation between specific heat and moisture content. Analyzing the slope based on the temperature difference is important; a smaller slope indicates a higher specific heat, which means a higher moisture content.

[0099] In the step of predicting fruit sugar content based on estimated moisture content, sugar levels are predicted from moisture data based on the correlation that sugar levels decrease as moisture content increases. This process can be handled in real time, allowing for real-time prediction of fruit sugar levels by immediately analyzing temperature change data. This enables non-destructive evaluation of fruit sugar content.

[0100] The sugar content prediction method according to one embodiment can systematically explain the sugar content prediction process based on the moisture content and specific heat characteristics of the fruit. The series of processes involving heating, measuring temperature changes, calculating specific heat and predicting moisture content, and finally predicting sugar content can evaluate the quality of the fruit non-destructively and efficiently.

[0101]

[0102] The device described above may be implemented as a hardware component, a software component, and / or a combination of a hardware component and a software component. For example, the device and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0103] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0104] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0105] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0106] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

1. In a device for predicting the moisture content and sugar content of a fruit, A heat treatment unit that applies heat to both surfaces of the fruit; A temperature sensor unit that measures the surface temperature of the fruit; A moisture prediction unit that collects temperature change data over time after being heated by the heat treatment unit and calculates the specific heat of the fruit based on the collected temperature change data to predict the moisture content; and A sugar content prediction unit that predicts the sugar content of a fruit based on the above-mentioned predicted moisture content A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by including 2. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized in that the above-mentioned heat treatment unit includes a heating device capable of applying different temperatures to both surfaces of the fruit.

3. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by the above-mentioned temperature sensor unit measuring the surface temperature of the fruit at specific time intervals after heating begins.

4. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by the above data collection module simultaneously collecting temperature change data on both surfaces of the fruit.

5. In Paragraph 4, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by the above moisture prediction unit calculating the slope of the temperature change over time to predict the moisture content of the fruit.

6. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized in that the above moisture prediction unit calculates the specific heat of the fruit according to the amount of temperature change and estimates the moisture content based on the correlation between the specific heat and the moisture content.

7. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by the above-mentioned sugar content prediction unit predicting sugar content using a correlation in which the sugar content decreases as the moisture content of the fruit increases.

8. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized in that the above-mentioned heat treatment unit includes an infrared heater and applies heat to the surface of the fruit in a non-contact manner.

9. In Paragraph 8, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized in that the above-mentioned temperature sensor unit includes an infrared temperature sensor unit and measures the temperature of the fruit surface in a non-contact manner.

10. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized by the above moisture prediction unit monitoring changes in the surface temperature of the fruit in real time to estimate the moisture content and sugar content in real time.

11. In Paragraph 1, A sugar content prediction device based on the moisture content and specific heat of a fruit, characterized in that the above-mentioned sugar content prediction unit predicts the sugar content by analyzing the difference between the internal moisture content and the surface moisture content of the fruit through the calculation of specific heat according to temperature change.

12. In a method for predicting the moisture content and sugar content of fruits, Step of applying heat to both surfaces of the fruit; A step of measuring the temperature of both surfaces of the fruit for a certain period of time after heating; A step of predicting the moisture content of the fruit by calculating the specific heat based on the measured temperature change; and Step of predicting the sugar content of fruit based on predicted moisture content A method for predicting sugar content based on the moisture content and specific heat of a fruit, characterized by including 13. In Paragraph 12, The step of applying heat to both surfaces of the fruit Step of setting different temperatures for the heat applied to both surfaces Includes, The step of predicting the moisture content of the fruit by calculating the specific heat based on the measured temperature change is, A step of predicting moisture content based on temperature change data according to the temperature difference. A method for predicting sugar content based on the moisture content and specific heat of a fruit, characterized by including 14. In Paragraph 12, The step of predicting the moisture content of the fruit by calculating the specific heat based on the measured temperature change is, A step of calculating specific heat by calculating the slope of the temperature change and estimating moisture content using the correlation between specific heat and moisture content. A method for predicting sugar content based on the moisture content and specific heat of a fruit, characterized by including 15. In Paragraph 12, The step of predicting the sugar content of the fruit based on the predicted moisture content is, A step of estimating the moisture content and sugar content of fruit in real time by processing temperature change data measured over a specific period after heating in real time. A method for predicting sugar content based on the moisture content and specific heat of a fruit, characterized by including

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