Crop cultivation prediction system and prediction methods

Abstract

This invention relates to a crop cultivation prediction system for predicting the number of days needed for crop cultivation. The system includes: a weather unit acquiring weather parameters for the crop's cultivation area; an image unit acquiring real-time images of the crop's appearance; and an analysis unit connected to both the weather and image units. The weather parameters are accumulated daily to form judgment parameters, and the real-time appearance images are compared with a crop growth database to determine the crop's growth stage corresponding to the image. Based on the judgment parameters and growth stage, the analysis unit calculates the number of days needed for crop cultivation. This invention also provides a crop cultivation prediction method. Thus, the crop cultivation prediction system and method utilize judgment parameters and growth stage to achieve the goal of predicting the number of days needed for crop cultivation.

Claims

1. A crop cultivation prediction system for predicting the number of cultivation days for at least one crop, the crop cultivation prediction system comprising: a weather unit for acquiring weather parameters of a cultivation area of ​​the crop; an image unit for acquiring real-time images of the crop's appearance; and an analysis unit connected to the weather unit and the image unit, accumulating the weather parameters daily to form a judgment parameter, comparing the real-time appearance image with a growth database of the crop to determine a growth stage of the crop corresponding to the real-time appearance image; and, using the judgment parameter and the growth stage, the analysis unit calculates the number of cultivation days for the crop; wherein the judgment parameter includes multiple cumulative temperature values ​​of the cultivation area; and the growth stage of the crop includes real-time appearance images of the crop acquired on multiple trait occurrence days.

2. The crop cultivation forecasting system as described in claim 1, wherein the weather parameter includes a temperature value, a humidity value, a day sunshine duration value, a day sunshine intensity value, an ultraviolet radiation intensity value, or a combination thereof; the temperature value includes an hourly temperature, a daily maximum temperature, a daily minimum temperature, a predicted temperature, or a combination thereof.

3. The crop cultivation prediction system as described in claim 1, wherein the growth database contains the cumulative temperature values ​​and the occurrence dates of the traits, and the cumulative temperature values ​​and the occurrence dates of the traits together constitute a growth trend line of the crop, the growth trend line being a predicted number of days required for the crop to grow from the actual occurrence date of a first trait to the expected occurrence date of a second trait based on the cumulative temperature values.

4. The crop cultivation prediction system as described in claim 1, wherein the analysis unit includes multiple growth models. Based on the accumulated temperature values ​​and the occurrence dates of the traits, one of the growth models is trained and calculated to enable the analysis unit to obtain a predicted number of days required for the crop from the actual occurrence date of a first trait to the expected occurrence date of a second trait. Each growth model obtains its corresponding predicted number of days, and the predicted number of days is compared with the actual number of days for the crop to obtain the optimal growth model that is closest to the actual number of days. The optimal growth model is then optimized by an algorithm and fed back to the analysis unit.

5. A method for predicting crop cultivation, comprising: providing a weather parameter, obtaining the weather parameter of a cultivation area of ​​a crop through a weather unit; providing a date of occurrence of a real-time appearance image, recording the date of occurrence of the real-time appearance image of the crop through an image unit; and providing a number of cultivation days for the crop, accumulating the weather parameter daily to form a judgment parameter through an analysis unit signal connected to the weather unit and the image unit, comparing the date of occurrence of the real-time appearance image with a growth database of the crop to obtain a growth stage of the crop corresponding to the date of occurrence of the real-time appearance image; and calculating the number of cultivation days for the crop using the judgment parameter and the growth stage; wherein the judgment parameter includes multiple cumulative temperature values ​​of the cultivation area; and the growth stage of the crop includes obtaining real-time appearance images of the crop on multiple trait occurrence days.

6. The crop cultivation forecasting method as described in claim 5, wherein the weather parameter includes an hourly temperature, a daily maximum temperature, a daily minimum temperature, a forecast temperature, or a combination thereof.

7. The crop cultivation prediction method as described in claim 5, wherein the growth database contains the cumulative temperature values ​​and the occurrence dates of the traits, and the cumulative temperature values ​​and the occurrence dates of the traits together constitute a growth trend line of the crop, the growth trend line being a predicted number of days required for the crop to grow from the actual occurrence date of a first trait to the expected occurrence date of a second trait based on the cumulative temperature values.

8. The crop cultivation prediction method as described in claim 5, wherein the analysis unit includes multiple growth models, and one of the growth models is trained and calculated based on the cumulative temperature values ​​and the occurrence dates of the traits, so that the analysis unit obtains a predicted number of days required for the crop to grow from the actual occurrence date of a first trait to the expected occurrence date of a second trait.

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