|Henry, Christopher - University Of Arkansas|
|Zhao, Haijun - Former ARS Employee|
|Lorence, Argelia - Arkansas State University|
Submitted to: Rice Technical Working Group Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/19/2018
Publication Date: 10/16/2018
Citation: Rohila, J.S., Henry, C.G., Zhao, H., Lorence, A., McClung, A.M. 2018. Agronomic, physiological and biochemical evaluations of rice under a water-deficit irrigation system. Rice Technical Working Group Meeting Proceedings. February 19-22, 2018, San Diego, California. 2018 Electronic Publication.
Technical Abstract: The sustainability of conventional flood irrigation management in rice is a concern worldwide considering the uncertain patterns of precipitation and depletion of aquifers used for irrigation. This same concern is shared in USA rice producing areas and, thus, development of rice varieties that can tolerate water-deficit irrigation (such as alternate-wetting-and-drying, AWD) practices without a penalty on grain yield and quality is highly desired. A multi-year study was conducted to evaluate rice cultivars and germplasm under precise deficit irrigation regimes using a subsurface drip irrigation system. The goal of this investigation was to identify cultivars that possess water-deficit stress tolerance with minimum yield penalty and to understand the biochemical and physiological nature of selected germplasm. Field trials were conducted using a randomized complete block design at DBNRRC/UofA research farm (N 34.46286°, W 91.39944°) for three years (2014-2016). A total of 15 rice cultivars representing a diverse genotypic range (indica, japonica, long grain, and medium grain) were evaluated in a replicated trial using four soil moisture regimes: Treatment 1: fully saturated (field capacity, FC), Treatment 2: 30% deficit, Treatment 3: 70% deficit, and Treatment 4: just above the wilting point. Two-row plots were drill planted each year (May-June) in such a way that the buried drip tape was between the two rows in the plot. To prevent water exchange between the treatments, 4 buffer rows of rice (cv. RoyJ) were planted between the irrigation treatments. Fertilizer and herbicide was applied according to local rice agronomic practices. Plots were thinned to a uniform plant stand and two-four seedlings were selected in the middle of the row and tagged for season-long defined measurements. Plots were fully irrigated until the V5 stage when irrigation treatments were initiated. To target certain soil moisture levels for each treatment, the irrigation valves were automatically controlled based on Acclima water moisture sensors, which were placed in rhizosphere of each treatment at 20 cm depth. Throughout the season actual soil moisture was monitored on each plot through a portable soil moisture sensor. On average, the total amount of irrigation applied in the most saturated treatment was 68.98 ha-cm compared to 36.34 ha-cm in the greatest water deficit treatment. Overall water-deficit stress treatments reduced plant height (91 cm to 79 cm), delayed heading dates (89 days to 93 days), and reduced grain yield per plant (26.5 g to 14.4 g) compared to the FC treatment. Regression analyses of the data support the developing hypothesis that the yield under water-deficit environment could be governed by thousand kernel weight trait. The cultivars were ranked for yield per se, and for yield stability across the four water regimes. In the final year of the study, foliar ascorbic acid (AsA) measurements were determined approximately 17 days before heading to evaluate the association between AsA and water-deficit stress tolerance. A selected set of genotypes were evaluated for net photosynthesis, stomatal conductance, and evaporation at this same stage. Based on the results an association was established between AsA, stomatal conductance, and yield under water-deficit stress tolerance and will be presented. The data supports that SDI is a viable and effective method for germplasm evaluation at a targeted water-deficit stress level. The study revealed that two mapping populations available at DBNRRC (PI 312777 x Katy, and Lemont x Teqing) are the best choices to screen under 20-40% water deficit conditions, while Rondo x Francis mapping population could be an excellent choice for higher water-deficit stress conditions and to look for transgressive variants among the mapping population.