Perennial plants provide extensive environmental services and increasing their prevalence on the agricultural landscape is one way to improve sustainability. Direct domestication of intermediate wheatgrass [Thinopyrum intermedium; (Host) Barkworth & D.R. Dewey] as a perennial grain crop is underway, and selection has focused primarily on improving seed size and grain yield.

Core Ideas Golf course superintendents often overseed winter‐damaged areas with creeping bentgrass in the early spring when temperatures are not ideal for rapid germination. Typical spring temperatures in the upper Midwest were used to define treatments in a controlled environment study to determine general germination response from early April to late May. Response was measured across 21 cultivars to find those with superior germinability under suboptimal conditions. The study found that creeping bentgrass does not germinate below 45°F. At temperatures typical to mid‐April, the cultivars Proclamation, Declaration, and Pure Select had the best germinability. Re‐establishing creeping bentgrass greens after winter damage can be a significant challenge in cold climates. Golf course superintendents require creeping bentgrass (Agrostis stolonifera L.) cultivars that are able to germinate under suboptimal temperatures to ensure early spring play. Little is known about cultivar differences for cold temperature germination; therefore, we assessed the germinability of 21 creeping bentgrass cultivars in a controlled environment. Temperature treatments represented a range of spring temperatures in Minnesota from 7 April to 25 May. Germination began occurring at the 19 April treatment. Top‐performing cultivars included Proclamation, Declaration, and Pure Select while Independence and Memorial performed poorly. Overall, we found that temperatures below 45°F do not allow for sufficient creeping bentgrass germination regardless of cultivar. There were few relevant differences for the 25 May treatment. Golf course superintendents should carefully consider cultivar differences when seeding at suboptimal temperatures.

Hairy vetch (Vicia villosa Roth) is a winter‐annual legume that is grown as a cover crop and for forage. Although more winter tolerant than most leguminous winter annuals, it does not reliably overwinter in the upper Midwestern United States. Our objectives were to screen a collection of accessions for winter hardiness and develop a screening method for freezing tolerance in a controlled setting. We evaluated 30 accessions (commercial germplasm and breeding populations) in multiple Minnesota environments. Average winter survival among accessions ranged from 13 to 73% and resembled a bimodal distribution, where two distinct phenotypic groupings were apparent. Commercial VNS (variety‐not‐stated) accessions were found to be highly variable for winter survival. Seed derived from Minnesota was generally winter hardy (>65% survival), and seed from Oregon was not (<39%). Due to large variation among and within field environments, a method of controlled freezing was developed to supplement winter hardiness evaluations. No differences in freezing tolerance were found among accessions without cold acclimation. However, large differences in freezing tolerance occurred when plants were first grown for 2 wk in greenhouse conditions (22°C, 16‐h photoperiod) and then cold acclimated for 4 wk (3°C, 10‐h photoperiod). Lethal temperatures were determined from six 24‐h programmed freezing treatments, where treatment temperatures ranged from −13 to −21°C. Accessions differed significantly for freezing tolerance, with median lethal temperature values ranging from −8.4 to −16.0°C. This method of controlled freezing correlated highly with winter survival in field evaluations (ρ = 0.77).

Core Ideas An automated open‐source analysis system was developed to rate crown and stem rust. The system was validated against manual measurements and visual rater ability. Consistency in rater (n = 9) ability was excellent for crown rust and fair to good for stem rust. Agreement in rater scores for individual images was low and showed high levels of variation. The automated system can replace visual rating of crown rust in the field but not stem rust. Crown and stem rust are major diseases of perennial ryegrass (Lolium perenne L.). Plant breeders and pathologists often rate rust severity in the field using the modified Cobb scale, but this method is subjective and labor intensive. A novel, open‐source system using ImageJ and R was developed to quantify pustule number and area using digital images collected from spaced plants in the field. The computer‐processing pipeline included development of training data for prediction of pixel identity using random forest and noise reduction spatial processing. Raters and the computer scored rust severity on plant images of varying complexity including whole‐plant (WP), five‐leaf (FL), and single‐leaf (SL) image series. Computer accuracy was determined using the SL, while the FL series gave insight into the true value of WP severity. Rater ability was assessed using a panel of nine scientists with varying levels of disease rating experience. Results showed rater perceptions of crown rust severity were very consistent across images, but agreement on severity values for a given image were low. Rater consistency for stem rust severity was low and FL scores were not strongly correlated with WP scores (r = 0.36, P = 0.03), indicating low rater accuracy. The computer‐processing pipeline was able to accurately discriminate, count, and quantify crown and stem rust pustules on leaf samples. Correlations between computer and the median rater score for crown rust were excellent (r > 0.90, P < 0.001) for all image series. Similar to raters, there was a lack of correlation between WP and FL series (r = 0.20, not significant) indicating that this technique is limited to leaf or stem samples for stem rust and not applicable to WP. However, the computer‐processing pipeline shows promise in replacing visual rating of WP for crown rust.

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