Autoregression Prediction Model for Grape Anthracnose

Grapevine (Vitis vinifera L.) is an economically important fruit crop, but its production is severely affected by anthracnose caused by Colletotrichum gloeosporioides, commonly known as bird’s eye spot. The present investigation was conducted at the Horticultural Farm, University of Agricultural Sciences, Raichur, during the Kharif seasons of 2024 and 2025 to study disease progression and to develop a prediction model for grape anthracnose in the susceptible cultivar Thompson Seedless. Disease severity was recorded at weekly intervals using a 0-4 rating scale and expressed as Per cent Disease Index (PDI). Simultaneously, weekly weather data were collected from the Main Agricultural Research Station, Raichur. Anthracnose appeared during the 27th and 24th standard meteorological weeks in 2024 and 2025, respectively, and gradually increased to 100 per cent severity by the end of the season. Observed PDI ranged from 8.50 to 100.00 per cent in 2024 and from 7.13 to 100.00 per cent in 2025. A first-order autoregressive model was developed to predict disease progression, which showed close agreement between observed and predicted PDI values, particularly during the mid-season period. The developed models exhibited high autocorrelation coefficients (R = 0.953 in 2024 and R = 0.891 in 2025), indicating a strong temporal relationship in disease development. The study demonstrates that an autoregressive approach can effectively describe the progression pattern of grape anthracnose under field conditions.