Late watergrass is a competitive weed of rice that is well adapted to both aerobic and anaerobic environments. Cultural controls such as a stale-seedbed and alternating from wet- to dry-seeding have been proposed as management options. However, the effects of these systems on its emergence and early growth are unknown. The objective of this study was to modify a previously developed population-based threshold model (PBTM) to predict emergence and early growth under field conditions. In 2013, a series of experiments were conducted at the California Rice Experiment Station (CRES) in Biggs, CA, to evaluate emergence and early growth of multiple herbicide–resistant and -susceptible late watergrass at four burial depths (0.5, 2, 4, and 6 cm) under three irrigation regimes: continuously flooded (CF), daily flush (DF), and intermittent flush (IF). Resistant plants emerged at a significantly higher rate under the IF treatment (P < 0.05). Both biotypes showed decreasing emergence with increasing depth, and no plants emerged from the 4- or 6-cm depths in the CF treatment. Using the Gompertz growth curve, resistant plants had greater predicted growth rates (k), lower predicted maximum heights (h max ), and a shorter time to predicted maximum growth rate (t m ) than susceptible plants under the CF and DF treatments. Under the IF treatment, the susceptible plants had greater k, lower h max , and shorter time to predicted t m . Information about burial depth and irrigation was incorporated into a previously developed PBTM for late watergrass, and validated at the CRES in a field with a susceptible late watergrass population in 2013 and 2014, under two irrigation systems, CF and IF. Model fit was best in the CF treatments (average Akaike information criteria [AIC] = 199.05) compared to the IF treatments (average AIC = 208.6).

Seeds from natural populations of fierce thornapple and velvetleaf collected in a corn-growing area in central Spain were incubated at a range of constant temperatures and water potentials to model the progress of germination on the basis of the accumulation of hydrothermal time. Previous to the germination tests, the seeds were treated in two different ways: (1) dark storage under dry conditions (nonchilled seeds), and (2) burying in the original soil at 10-cm depth during 2 mo in winter (naturally chilled seeds). The results indicated different mechanisms inhibiting germination in both weed species. Whereas fierce thornapple displayed some type of embryo dormancy, the lack of germination in velvetleaf appeared to be entirely due to the seed coat. On the other hand, significant differences between nonchilled and naturally chilled seeds in fierce thornapple were observed, mainly due to the decrease in the mean base water potential of the 50th percentile in the latter, which indicated a loss of dormancy by exposure of the seeds to natural conditions. Hydrothermal time appears to be a good description of the germination patterns in both weed species, but in the case of fierce thornapple, only for naturally chilled seeds. Thus, the development of the hydrothermal model in fierce thornapple raises some questions for consideration concerning the influence of the type of seeds (conditions of storage, pretreatments of the seeds before germination tests) on its germination capacity.

Seed germination is responsive to diverse environmental, hormonal and chemical signals. Germination rates (i.e. speed and distribution in time) reveal information about timing, uniformity and extent of germination in seed populations and are sensitive indicators of seed vigour and stress tolerance. Population-based threshold (PBT) models have been applied to describe germination responses to temperature, water potential, hormones, ageing and oxygen. However, obtaining detailed data on germination rates of seed populations requires repeated observations at frequent times to construct germination time courses, which is labour intensive and often impractical. Recently, instruments have been developed to measure repeatedly the respiration (oxygen consumption) of individual seeds following imbibition, providing complete respiratory time courses for populations of individual seeds in an automated manner. In this study, we demonstrate a new approach that enables the use of single-seed respiratory data, rather than germination data, to characterize the responses of seed populations to diverse conditions. We applied PBT models to single-seed respiratory data and compared the results to similar analyses of germination time courses. We found consistent and quantitatively comparable relationships between seed respiratory and germination patterns in response to temperature, water potential, abscisic acid, gibberellin, respiratory inhibitors, ageing and priming. This close correspondence between seed respiration and germination time courses enables the use of semi-automated respiratory measurements to assess seed vigour and quality parameters. It also raises intriguing questions about the fundamental relationship between the respiratory capacities of seeds and the rates at which they proceed toward completion of germination.