You are looking at 1 - 2 of 2 items for
- Author or Editor: K. Raja Reddy x
Temperature affects reproductive potential, aesthetic, and commercial value of ornamental peppers (Capsicum annuum L.). Limited information is available on cultivar tolerance to temperature stress. An experiment was conducted using pollen and physiological parameters to assess high and low temperature tolerance in ornamental peppers. In vitro pollen germination (PG) and pollen tube length (PTL) of 12 morphologically diverse ornamental pepper cultivars were measured at a range of temperatures, 10 to 45 °C with 5 °C increments. Cell membrane thermostability (CMT), chlorophyll stability index (CSI), canopy temperature depression (CTD), and pollen viability (PV) were measured during flowering. From the modified bilinear temperature–PG and PTL response functions, cardinal temperatures (Tmin, Topt, and Tmax) for PG and PTL and maximum PG (PGmax) and PTL (PTLmax) were estimated. Cultivars varied significantly for PG, PTL, cardinal temperatures for PG and PTL, and all three physiological parameters. Cumulative temperature response index (CTRI) of each cultivar, calculated as the sum of 12 individual temperature responses derived from PV, PGmax, PTLmax, Tmin, Topt, and Tmax for PG and PTL, CMT, CTD, and CSI were used to distinguish differences among the cultivars and classify for high (heat) and low (cold) temperature tolerance. Based on CTRI–heat, cultivars were classified as heat-sensitive (‘Black Pearl’, ‘Red Missile’, and ‘Salsa Yellow’), intermediate (‘Calico’, ‘Purple Flash’, ‘Sangria’, and ‘Variegata’), and heat-tolerant (‘Chilly Chili’, ‘Medusa’, ‘Thai Hot’, ‘Explosive Ember’, and ‘Treasures Red’). Similarly, cultivars were classified for cold tolerance as cold-sensitive, moderately cold-sensitive, moderately cold-tolerant, and cold-tolerant based on CTRI–cold. ‘Red Missile’ and ‘Salsa Yellow’ were classified as cold-tolerant. Cultivar screening using pollen parameters will be ideal for reproductive temperature tolerance, whereas physiological parameters will be suitable for screening vegetative temperature tolerance. The identified heat- and cold-tolerant cultivars are potential candidates in breeding programs to develop new ornamental and vegetable pepper genotypes for high and low temperature tolerance.
Sweetpotato [Ipomoea batatas (L.) Lam.] storage root formation is a complex developmental process. Little quantitative information is available on storage root initiation in response to a wide range of soil moisture levels. This study aimed to quantify the effects of different levels of soil moisture on sweetpotato storage root initiation and to develop functional relationships for crop modeling. Five levels of soil moisture, 0.256, 0.216, 0.164, 0.107, and 0.058 m3·m−3 soil, were maintained using sensor-based soil moisture monitoring and semiautomated programmed irrigation. Two commercial sweetpotato cultivars, Beauregard and Evangeline, were grown in pots under greenhouse conditions and treatments were imposed from transplanting to 50 days. Identification of storage roots was based on anatomical, using cross-sections of adventitious roots, and visual features harvested at 5-day intervals from 14 to 50 days after transplanting (DAT). Recorded time-series storage root numbers exhibited sigmoidal responses at all soil moisture levels in both cultivars. Time to 50% storage root initiation and maximum storage root numbers were estimated from those curves. Rate of storage root development was determined as a reciprocal of time to 50% storage root formation data. Time to 50% storage root initiation declined quadratically from 0.05 to 0.15 m3·m−3 soil moisture and increased slightly at the higher soil moisture levels in both the cultivars. Cultivars differed in time to 50% storage root initiation and the storage root developmental rate. Soil moisture optima for storage root initiation were 0.168 and 0.199 m3·m−3 soil, equivalent to 63% and 75% field capacity for cultivars Beauregard and Evangeline, respectively. The data and the inferences derived from the functional algorithms developed in this study could be used to advise growers to schedule irrigation more precisely, make planting decisions based on available soil moisture, and to develop sweetpotato crop models for field applications.