The article explores randomness in yearly crop yields using fractal dimensions. By analyzing Hurst exponents, which measure randomness, the researchers found that crop yields exhibit long-term dependence similar to natural processes like river discharges and temperatures. Hurst exponents greater than 0.5 indicate persistent patterns in crop yields, while those less than 0.5 suggest anti-persistent behavior. Removing global trends in yield data is crucial for accurate fractal dimension calculations. The study highlights the importance of understanding the underlying patterns in crop yields for better agricultural management.