Comparing canopy-level and weather-station sensor placement effects on anthracnose and Botrytis disease model predictions, for precision timing of fungicide applications in strawberry production

Plasticulture strawberry growers in the Eastern US use lightweight floating row covers to promote floral bud initiation during fall and for frost/freeze protection during spring.
Weather station data which enables predictive disease modeling might not accurately monitor environmental conditions at canopy level.
Increased precision of the two primary model inputs, viz. air temperature (AT) and leaf wetness durations (LWD) could increase the precision of anthracnose (Colletotrichum spp.) fruit rot (AFR) and Botrytis fruit rot (BFR) model predictions, to accurately time fungicide sprays and minimize unnecessary chemical and labor inputs.
Replicate canopy-based sensors were installed at four strawberry farms in Maryland and Virginia during 2019/20 and 2020/21 production seasons.
Five-minute resolution AT and LWD data allowed real-time, model-based disease (AFR and BFR) risk data.
Fungicide application recommendations were based on separate data streams from: 1) canopy-level sensors at 30 cm (CBS); 2) edge-of-field weather station (ATMOS41) at 2 m height, and 3) weekly grower standard (GS) sprays.
Fall-applied row covers significantly increased average canopy AT compared to uncovered canopy and ATMOS41 measurements.
Interior canopy rows had longer LWD than ATMOS41 LWD in 5 of 6 trials.
Predicted AFR and BFR infection risk tended to be lower based on weather station data, resulting in more sprays for the CBS treatment than the ATMOS41 treatment.
Yet, both treatments resulted in fewer (45 and 61%, respectively) sprays than the GS treatment.
While row cover use did not greatly affect predicted AFR or BFR risk during late fall, interior row sensors predicted more infection days than the edge-row or ATMOS41. No significant differences were observed between treatments in marketable yield, presumably due to generally lower than normal disease pressure in both years.
However, the increased sensitivity of disease predictions from canopy-based sensors may benefit cultivars with high disease susceptibility during wet years.

International Symposium on Models for Plant Growth, Environments, Farm Management in Orchards and Protected Cultivation – HorchiModel2023

S.D. Cosseboom, J.D. Lea-Cox, M. Hu

microclimate, row covers, leaf wetness, strawberry, fungal diseases, Colletotrichum

https://doi.org/10.17660/ActaHortic.2025.1425.59