A method for recognizing grain, comprising: obtaining first image data having grain to be recognized; inputting the first image data into a first recognition model to obtain a first recognition result, wherein the first recognition result identifies a type of the grain to be recognized; and obtaining a confidence level that the grain to be recognized belongs to the type of grain in the first recognition result, characterized by : in response to determining that the confidence level that the grain to be recognized belongs to the type of grain meets a first preset condition, inputting the first image data into a second recognition model associated with the identified type of grain to obtain a second recognition result, wherein the second recognition result identifies a variety of the grain to be recognized; obtaining a confidence level that the grain to be recognized belongs to a variety of the grain type in the second recognition result; in response to determining that the confidence level meets a second preset condition, outputting the variety of the grain to be recognized as a recognition result; and in response to determining that the confidence level does not meet the second preset condition, outputting the type of the grain to be recognized as the recognition result. obtaining first image data having grain to be recognized; inputting the first image data into a first recognition model to obtain a first recognition result, wherein the first recognition result identifies a type of the grain to be recognized; and obtaining a confidence level that the grain to be recognized belongs to the type of grain in the first recognition result, characterized by : in response to determining that the confidence level that the grain to be recognized belongs to the type of grain meets a first preset condition, inputting the first image data into a second recognition model associated with the identified type of grain to obtain a second recognition result, wherein the second recognition result identifies a variety of the grain to be recognized; obtaining a confidence level that the grain to be recognized belongs to a variety of the grain type in the second recognition result; in response to determining that the confidence level meets a second preset condition, outputting the variety of the grain to be recognized as a recognition result; and in response to determining that the confidence level does not meet the second preset condition, outputting the type of the grain to be recognized as the recognition result. in response to determining that the confidence level that the grain to be recognized belongs to the type of grain meets a first preset condition, inputting the first image data into a second recognition model associated with the identified type of grain to obtain a second recognition result, wherein the second recognition result identifies a variety of the grain to be recognized; obtaining a confidence level that the grain to be recognized belongs to a variety of the grain type in the second recognition result; in response to determining that the confidence level meets a second preset condition, outputting the variety of the grain to be recognized as a recognition result; and in response to determining that the confidence level does not meet the second preset condition, outputting the type of the grain to be recognized as the recognition result. <EOS>