ALS inhibitor–resistant smallflower umbrella sedge (Cyperus difformis) seed germination requires fewer growing degree days and lower soil moisture. Issue 1 (November 2019) - Pedroso, Rafael M.; van Kessel, Chris; Dourado Neto, Durval; Linquist, Bruce A.; Boddy, Louis G.; Al-Khatib, Kassim; Fischer, Albert J.
Abstract: The repetitive use of ALS inhibitors for smallflower umbrella sedge ( Cyperus difformis L.) control has selected for herbicide-resistant (R) populations that threaten the sustainability of rice ( Oryza sativa L.) production and demand alternative control measures be developed. A better understanding of seedling recruitment patterns at the field level is required to optimize the timing and efficacy of control measures. Therefore, a population-based threshold model was developed for optimizing germination prediction in multiple acetolactate synthase (ALS)-R and ALS-susceptible (ALS-S) C. difformis biotypes and applied to field-level emergence predictions. Estimated base temperatures ( T b ) ranged from 16.5 to 17.6 C with no clear pattern between biotypes; such values are higher than T b values of other important rice weeds, as well as for rice. Germination rates increased linearly from 16 to 33.7 C. ALS-R seeds germinate faster due to smaller median thermal times to germination (θT(50) ) while also displaying lower germination synchronicity across water potentials. Interestingly, ALS-R biotypes were capable of germinating under lower moisture availability, as indicated by their lower (more negative) base water potential values (Ψb(50) ) for seed germination; Ψb(50) values ranged from −0.24 to −1.13 MPa. In-field soil germination measurements found thermal times to emergence varied across three water regimes (daily water, flooded, or saturated). Seedling emergence under the daily water treatment was fastest; however, total seedling density was lower than for the other water regimes. In order to optimize springtime C. difformis seedling emergence, soil moisture should be kept around field capacity, as germination is hindered at lower moisture contents. By predicting when most of the seed population germinates, the thermal-time model can address issues regarding the optimal timing for herbicide applications, thereby allowing for improved C. difformis management in rice fields.