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a b s t r a c tGrowth and yield formation in rice (Oryza sativa L.) depend on integrated impacts of genotype, environment and management. A rice growth simulation model can provide a systematic and quantitative tool for predicting growth, development and productivity of rice under changing environmental conditions. Existing rice models perform well but are somewhat difficult to use because of the large number of parameters that users must estimate. Experience in modelling wheat suggested that using physiological development time (PDT) as a scaler for phenology and a partitioning index for organ growth could result in fewer parameters while providing good predictability and applicability. RiceGrow was developed using PDT and a partitioning index to quantify relations among rice growth and environmental factors, genotypic parameters and management practices. RiceGrow includes seven sub-models for simulating phenology, morphology and organ formation, photosynthesis and biomass production, dry matter partitioning, yield and quality formation, water relations and nutrient balance. The model was calibrated with three datasets involving various cultivars, sowing dates and N rates at multiple sites. Validation with independent datasets showed the model had good predictability and applicability. The RiceGrow model was compared with the ORYZA2000 model, showing that both provided satisfactory estimates for phenology, shoot biomass and yield. Overall, RiceGrow can be used to predict rice growth and development with varied genotypes, environmental conditions and management practices for multiple uses including scientific understanding, policy formulation and optimizing crop management.

This study was initiated to characterize Rhizobium isolates obtained from root nodules of ineffectively nodulated, field-grown alfalfa (Medicago sativa L.) plants. The purpose was to determine if these isolates possessed characteristics which would explain either their ineffectiveness in N2 fixation or their apparent ability to tolerate the moderately acid soil conditions from which they originated. Isolates were characterized by analysis of growth rate, 390C tolerance, acid production on conventional media, and symbiotic performance. All isolates were ineffective in N2 fixation on alfalfa, and they contained one or more anomalous characteristics. These included either slow growth rate, lack of 39°C tolerance, or lack of acid production on conventional media. Infectiveness tests on a broad range of legumes revealed that the isolates formed root nodules on M. sativa, Medicago lupulina L., and Phaseolus vulgaris (L.) Savi. (common bean). These results provide evidence that, in some situations, ineffective nodulation of M. sativa in the field may be due to the presence of promiscuous, native Rhizobium species.

Increasing seed yield and quality of key cool‐season perennial grasses is an important component of meeting China's environmental, food security, and urban beautification goals. Determining a suitable seed producing region and developing best management practices for this region with specific, high priority grasses will contribute to the availability of seed for reducing desertification, increasing livestock production, and improving urban living conditions. Previous research in other areas has addressed various agronomic practices on some grasses, but none has evaluated optimal row spacings for producing high yields of high quality seed in conditions similar to the Hexi Corridor, currently a major seed producing area in China for other seed crops. We compared our field trials in this area with those of other regions in China and the world to determine if this area would be suitable as a grass seed production center. Five important perennial, cool‐season grasses {[Elymus kamoji (ohwi) S.L. Chen, slender wheatgrass [Elymus trachycaulus (Link) Gould ex Shinners ssp. Trachycaulus], smooth bromegrass (Bromus inermis Leyss), Siberian wildrye (Elymus sibiricus L.), and Chinese sheepgrass [Leymus chinensis (Trin) Tzvel]} were evaluated from 2010 to 2012 under four row spacing treatments (30, 50, 70, and 90 cm). Results showed all five grasses have potential for high seed production in this region, with yields equivalent to or significantly higher than other areas. Optimal row spacing for Elymus kamoji and smooth bromegrass was 30 cm while a 50 cm row spacing was better for seed production and weed control for slender wheatgrass, Siberian wildrye, and Chinese sheepgrass. This work will allow multinational seed companies, development agencies, and government program directors to better evaluate the potential economic sustainability of grass seed production in this region compared to importing seed from other regions of the world.