Growth and yield responses to simulated hail damage in drip-irrigated cotton

The frequent occurrence of hailstorm in Xinjiang affects cotton(Gossypium hirsutum L.)production and causes enormous economic loss.The indeterminate growth habit of cotton allows for varying degrees of recovery and yield when different hail damage levels occur at different stages,which brings inconvenience to agricultural insurance claims and post-damage management.Therefore,this study aimed to elucidate cotton recovery and yield responses to different levels of simulated hail damage at different growth stages.Four levels of hail damage(0,30,60,and 90%)were simulated every 15 d from the five-leaf stage to the boll opening stage in 2018 and 2019,for a total of six times(Ⅰ,Ⅱ,Ⅲ,Ⅳ,Ⅴ,and Ⅵ).The results showed that seed cotton yield decreased as the damage level increased and yield reduction increased when the damage was applied to older plants(for 30,60 and 90% damage levels,yield reduction was 9-17%,22-37% and 48-71%,respectively).One possible reason was that the leaf area index and leaf area duration of plant canopy decreased after hail damage,resulting in a reduction in the accumulation of above-ground biomass.However,when hail damage occurred before bloom,due to the indeterminate growth habit of cotton,the vegetative organs produced a strong compensation ability that promoted the bud development.The compensation ability of vegetative organs decreased when hail damage occurred after bloom and the recovery time was too short to promote new boll maturity.As the first study to understand the recovery of cotton after hail damage,it analyzed the leaf area index,leaf area duration,above-ground biomass accumulation and yield,rather than the yield alone.The findings are of great importance for cotton production as they inform decisions about post-damage management practices,yield forecasts and insurance compensation.

Simulation of Hail and Soil Type Effects on Crop Yield Losses in Kansas,USA

Computer simulation was used for predictive analysis of the effects of weather and soil type on crop yield in the U.S. crop insurance program. The Environmental Policy Integrated Climate （EPIC） model was modified to include hail weather events, which completed the modifications necessary to simulate the four most frequent causes of crop yield loss （hail, excessive wet, excessive cold, and excessive dry） associated with soil type in Kansas, USA. At the region level, per hectare yields were simulated for corn, wheat, soybean, and sorghum. We concluded that it was possible to predict crop yields through computer simulation with greater than 93% accuracy. The hail damage model test indicated EPIC could predict hail-soil-induced yield losses reasonably well （R^2 〉 0.6）. The investigation of soil type influence on dryland sorghum and wheat production indicated that Wymore silty clay loam soil and Kenorna silt loam produced the highest sorghum yields statistically; Kuma silt loam, Roxbury silt loam, Crete silty clay loam, and Woodson silt soils produced the second highest sorghum yields statistically; and Richfiled silt loam, Wells loam, and Canadian sandy loam produced the lowest sorghum yields. By contrast, wheat production showed less sensitivity to soil type variation. The less sensitive response of wheat yields to the soil type could be largely due to the unconsidered small-scale variability of soil features.