whose help in the field and in the office made my projects possible and fun. Many thanks to the OARDC farm staff for their help with our projects and helping me get the truck out of the mud hole on West Badger.

Producers of the eastern Corn Belt are often forced to either delay corn (Zea mays, L.) planting or replant due to unfavorable early season growing conditions. In these situations producers may decrease N rates due to decreased yield potential or switch to short season hybrids to reduce the risk of frost injury prior to maturity. Hybrids with differing yield potential may have different N requirements, but definitive research to determine the impact of hybrid selection on N response is lacking. Field experiments were conducted in Ohio during 2006 and 2007 to evaluate if corn grain yield and stalk lodging attributed to N fertilizer is affected by hybrid or planting date. This experiment evaluated two planting dates (late April/early May and early/mid‐June), with subplots comparing N fertilizer rates (0, 60, 120, and 180 lb N/acre), and sub‐subplots containing corn hybrids of differing maturities (104, 108, 109, and two 113 days relative maturity). In 2006, planting date did not affect the economically optimum N fertilizer rate (EONR), although late planted corn did produce lower grain yields. In 2007, late‐planted corn was less responsive to N with the optimum N rate being 38 lb N/acre less than early‐planted corn. Differences in N response between hybrids were noted, but optimum N rates were not markedly different.

The structured representation for semantic parsing in task-oriented assistant systems is geared towards simple understanding of one-turn queries.Due to the limitations of the representation, the session-based properties such as coreference resolution and context carryover are processed downstream in a pipelined system. In this paper, we propose a semantic representation for such task-oriented conversational systems that can represent concepts such as co-reference and context carryover, enabling comprehensive understanding of queries in a session. We release a new session-based, compositional taskoriented parsing dataset of 20k sessions consisting of 60k utterances. Unlike Dialog State Tracking Challenges, the queries in the dataset have compositional forms. We propose a new family of Seq2Seq models for the session-based parsing above, which achieve better or comparable performance to the current state-of-the-art on ATIS, SNIPS, TOP and DSTC2. Notably, we improve the best known results on DSTC2 by up to 5 points for slot-carryover.

Lime is used as a soil amendment to achieve the optimum pH suitable for good crop growth. Buffer pH (BpH) measurements have been calibrated to relate the linear drop in pH of the soil-buffer system to the amount of lime needed to neutralize soil to a certain pH level. The amount of lime required to neutralize soil acidity, called the lime requirement (LR), is obtained from soil-limestone (CaCO 3 ) incubations. In this study, 13 soils from Ohio were incubated with CaCO 3 for a period of 1 month to determine the LR to achieve different target pHs. This LR was then regressed with the different BpHs of four buffer solutions [(1) Shoemaker, McLean, and Pratt (SMP), (2) Sikora, (3) Mehlich, and (4) modified Mehlich] to obtain calibration equations. The Sikora and modified Mehlich buffers are variations of the SMP and Mehlich buffers, respectively, but they are designed to promote buffering without use of any hazardous constituents [i.e., chromium(VI) in SMP buffer and barium in the Mehlich buffer]. This study was done to verify the applicability of the buffers that do not contain any hazardous constituents and to calibrate these buffers for predicting lime requirement needs for Ohio soils. Comparing the calibrated equations of the SMP and Sikora buffers with CaCO 3 -incubation LR recommendations revealed that the SMP and Sikora buffer solutions were not significantly different, and a single calibrated equation can be used for these two buffers to determine LR predictions in Ohio. The Mehlich and modified Mehlich calibration equations differed significantly from the SMP calibration equations and were not as highly correlated with CaCO 3 -incubation LR recommendations using a linear model (r 2 , 0.54). Thus, it is possible to use the Mehlich and modified Mehlich for determining lime recommendations, but they require a correction factor such as inclusion of the initial soil pH to improve the precision of the LR prediction. We also found the various buffers tested in this study were better able to predict LR rates for greater LR soils than low LR soils. In conclusion, successful laboratory tests to predict LR for Ohio soils are possible using alternative buffers that do not contain hazardous constituents.

Commercial seed of glyphosate‐tolerant alfalfa contains small percentages of seeds, called nulls, that do not posses the herbicide trait. Differential competitiveness of glyphosate‐tolerant seedlings compared with null seedlings may be detrimental to alfalfa stand density if delayed glyphosate application allows the null and tolerant seedlings to compete with each other. Our objective was to determine if delayed glyphosate application affects plant density of glyphosate‐tolerant alfalfa stands. Commercially available glyphosate‐tolerant alfalfa was seeded at 17 and 29 kg/ha, plots were treated with glyphosate one month (3‐ to 6‐trifoliate leaf stage) or one‐year after planting and plant density was monitored throughout the study. Regardless of seedling rate an average of 6.5 and 5.5% of the alfalfa plants died when glyphosate was applied one month and one year after planting, respectively, but plant density remained unchanged during the same time periods when glyphosate was not applied. Planting alfalfa at 17 kg/ha resulted in lower seedling density, but also lower plant mortality during the seeding year than planting at 29 kg/ha. We conclude that delaying glyphosate application to glyphosate‐tolerant alfalfa until one year after planting does not alter the percent of glyphosate‐tolerant and non‐tolerant plants.