Late watergrass is a serious weed of California rice that has evolved resistance to molinate, thiobencarb, fenoxaprop-ethyl, and bispyribac-sodium. To obtain an insight into the origin and spread of resistant (R) late watergrass in California rice fields, we evaluated similarities in morphological traits and amplified fragment length polymorphism (AFLP) fingerprints among 15 R strains compared with susceptible (S) strains. All strains were derived by inbreeding from accessions collected in rice fields of the Sacramento Valley, CA. In the field, R plants were shorter than S plants; they also had narrower and shorter flag leaves and thinner culms. Spikelets also appeared smaller and more slender in R plants. There was greater morphological similarity among the 15 R strains than among the eight S strains. The mean coefficients of variation for morphological traits were much smaller among R strains, which in a cluster analysis (Ward's method) were grouped morphologically apart at early clustering stages from the more variable S strains. AFLP electropherograms also showed greater similarity between R strains. R strains were grouped separately from the S strains in a cluster analysis based on calculated Nei and Li coefficients used in an unweighted pair group method using arithmetic means. However, small genetic differences also existed because the R strains were grouped into six clusters, suggesting that R strains were not samples from an identical strain. It was concluded that R strains originated from a preexisting and preadapted mutant late watergrass population in the Sacramento Valley. This study establishes that resistance moved by spikelet dispersal, not independent mutation events, most likely defined the geographical distribution of R late watergrass in California. Prevention and control of this dispersal combined with elimination of seed-producing survivors after herbicide treatment should be relevant components of the integrated management of herbicide-resistant late watergrass in California rice.

, 55 % lower compared to CF30, while no differences in nitrous oxide emissions were observed between treatments (p > 0.05). No yield differences between irrigation systems were observed in two of the rice seasons (p > 0.05) while AWDI promoted yield reduction in one of the seasons (p < 0.05). When rice yield and greenhouse gases (GHG) emissions were considered together, the AWDI irrigation system allowed for lower yield-scaled total global warming potential (GWP). Higher irrigation water productivity was achieved under AWDI in two of the three rice seasons. These findings suggest that AWDI could be an option for reducing GHG emissions and increasing irrigation water productivity. However, AWDI may compromise grain yield in certain years, reflecting the importance of the need for fine tuning of this irrigation strategy and an assessment of the overall tradeoff between relationships in order to promote its adoption by farmers.

Water temperature has increasingly become a matter of concern for California rice (Oryza sativa L.) growers due to a need for public water agencies to improve habitat for fish. Prudent management of water resources to balance the needs of environmental and agricultural interests requires the quantification of water temperature effects on rice productivity. Our objective was to evaluate two alternative thermal unit models for the effect of low water temperature on yield. One model was based on the total number of hours below a given threshold water temperature Tb (abbreviated TNHB Tb) and the other was based on the concept of inverse degree days (i.e., degree days below a given threshold water temperature) (abbreviated IDD). We tested these models at a range of values of Tb between 10 and 25°C on data from two commercial fields during 2 yr. Results showed that the effect of low water temperature may be much greater than would be apparent from the visual appearance of the rice plants. Values of IDD and TNHB Tb were very highly correlated for 4 of the 4‐yr field combinations. A logistic curve model based on TNHB 20°C provided the best fit to the aggregated data.

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