Growth, developmental, and physiological responses of two sweetpotato (Ipomoea batatas L. [Lam]) cultivars to early season soil moisture deficit

Abstract

Soil moisture deficit at early season is detrimental for sweetpotato growth and development affecting final yield. This study investigated the effects of different soil moisture regimes on early season growth, developmental, and physiological responses of two sweetpotato cultivars, ‘Beauregard’ and ‘Evangeline’, grown in a greenhouse environment. Five levels of soil moisture treatments, 0.256, 0.216, 0.164, 0.107, and 0.058m3m−3 of VWC, were maintained through sensor-based soil moisture monitoring, and semi-automated programmed irrigation. Midday leaf water potential (LWP), gas exchange, and fluorescence were measured weekly from 30 to 50 days after transplanting (DAT). Growth and development of plants were evaluated through harvesting four plants at 5-day intervals from 14 to 50 DAT. Leaf pigments and cell and chlorophyll stability indices were also determined. Midday LWP of sweetpotato declined linearly with decreasing soil moisture levels. The photosynthetic rate also declined linearly in Beauregard and quadratically in Evangeline with decreasing soil moisture. Both cultivars had a close association between photosynthetic rate and stomatal conductance over the soil moisture treatments, suggesting that stomatal closure is a key limitation for the drop in photosynthesis. Chlorophyll concentration was significantly lower at extreme soil moisture deficit conditions. Significant difference was found in water use efficiency between cultivars and among soil moisture treatments. Rates of vine elongation and leaf formation of Evangeline decreased more rapidly than Beauregard with declining soil moisture levels. Also with decreasing soil moisture, the shoot biomass declined more rapidly than root biomass. The results showed that maintaining soil moisture closer to field capacity (0.256m3m−3 of VWC) during early season is beneficial for early development of both root and shoot system and thus better crop performance. The data and the inferences derived from the functional algorithms developed in this study will be useful for crop modelling, field-level irrigation scheduling, and planting decisions.