Horticulture Research Data

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This collection holds research data and related products from the Horticulture Section of the Cornell School of Integrative Plant Science.


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    Data from: Carbon allocation to root exudates is maintained in mature temperate tree species under drought
    Hafner, Benjamin D; Brunn, Melanie; Zwetsloot, Marie J; Weikl, Fabian; Pritsch, Karin; Hikino, Kyohsuke; Ruehr, Nadine K; Sayer, Emma J; Bauerle, Taryn L (2022-04-08)
    Data in support of the following research: Carbon (C) exuded via roots is proposed to increase under drought and facilitate important ecosystem functions. However, it is unknown how exudate quantities relate to the total C budget of a drought-stressed tree, i.e. how much of net-C assimilation is allocated to exudation at the tree level. We calculated the proportion of daily C assimilation allocated to root exudation during early summer by collecting root exudates from mature Fagus sylvatica L. and Picea abies (L.) Karst. exposed to experimental drought, and combining above- and belowground C fluxes with leaf, stem, and fine-root surface area. Exudation from individual roots increased exponentially with decreasing soil moisture, with the highest increase at the wilting point. Despite ~50 % reduced C assimilation under drought, exudation from fine-root systems was maintained and trees exuded 1.0 % (F. sylvatica) to 2.5 % (P. abies) of net C into the rhizosphere, increasing the proportion of C allocation to exudates two- to threefold. Water-limited P. abies released two-thirds of its exudate-C into the surface soil, whereas it was only one-third in droughted F. sylvatica. Across the entire root system, droughted trees maintained exudation similar to controls, suggesting drought-imposed belowground C investment, which could be beneficial for ecosystem resilience.
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    Data from: Estimating agronomically relevant symbiotic N fixation in green manure breeding programs
    Muller, Katherine; Guinness, Joseph; Hecking, Matthew; Drinkwater, Laurie (2021)
    Widespread use of legume green manures is limited by a lack of reliable varieties that meet the needs of farmers. Improving symbiotic N fixation (SNF) in open-pollinated legume species poses a challenge because normal methods used for assessing SNF conflict with breeding practices such as seed production and removing low-quality sires. We investigated methods for measuring symbiotic N fixation that are compatible with breeding practice for two major legume cover crops: hairy vetch (Vicia villosa) and crimson clover (Trifolium incarnatum L.). We collected two non-destructive samples at the early-flowering stage (Meristem and Wedge) and a sample at seed harvest (Seed). Our objective was to determine which combination of measurements best predicted symbiotic N fixation (%Ndfa) and total N content at 50% flowering. Our statistical approach accommodated the problem that target traits and seed measurements cannot be measured in the same individuals. Overall, the Wedge sample provided the best prediction for Ndfa at 50% flowering. The best predictions for total N plant-1 came from combining vigor ratings with aboveground biomass at seed harvest. In addition to specific recommendations for legume cover crop breeding programs, we provide a flexible statistical method for studying relationships between traits that cannot be measured jointly.
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    Data from: Cultivar mixtures: A meta-analysis of the effect of intraspecific diversity on crop yield
    Reiss, Emily R.; Drinkwater, Laurie E. (2017-09-13)
    Extensive research has shown that greater plant community diversity leads to higher levels of productivity and other ecosystem services, and such increased diversity has been suggested as a way to improve yield and agricultural sustainability. Increasing intraspecific diversity with cultivar mixtures is one way to increase diversity in agricultural systems. We examined the relationship between intraspecific diversity and yield in cultivar mixtures using a meta-analysis of 91 studies and >3600 observations. Additionally, we investigated how environmental and management factors might influence this relationship, and if the yield stability of cultivar mixtures differed from that of monocultures. We found that the yield increased by 2.2% overall in cultivar mixtures relative to their monoculture components. Mixtures with more cultivars and those with more functional trait diversity showed higher relative yields. Under biotic stressors, such as disease pressure, and abiotic stressors, such as low levels of soil organic matter and nutrient availability, this diversity effect was stronger, resulting in higher relative yields. Finally, cultivar mixtures generally showed higher yield stability compared to monocultures, especially in response to annual weather variability at a site over time. This practice of mixing cultivars can be integrated into intensified cropping systems where species monocultures dominate, as well as in smallholder cropping systems where low-cost improvements are in demand. Overall, these results suggest that cultivar mixtures are a viable strategy to increase diversity in agroecosystems, promoting increased yield and yield stability, with minimal environmental impact.
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    Data from "Carbonate Determination by Mid-IR Spectroscopy with Regional and Continental Scale Models"
    Comstock, Jonathan P; Ferguson, Richard; Bailey, Scarlett; Beem-Miller, Jeffery P; Sherpa, Sonam R; Lin, Feng; Lehmann, Johannes; Wolfe, David W (2016-12)
    A carbonate (CO3) prediction model was developed for soils throughout the contiguous United States using mid-infrared (MIR) spectroscopy. Excellent performance was achieved over an extensive geographic and chemical diversity of soils. A single model for all soil types performed very well with a root mean square error of prediction (RMSEP) of 12.6 g kg-1 and was further improved if Histosols were excluded (RMSEP 11.1 g kg-1). Exclusion of Histosols was particularly beneficial for accurate prediction of CO3 values when the national model was applied to an independent regional dataset. Little advantage was found in further narrowing the taxonomic breadth of the calibration dataset, but higher precision could be obtained by running models for a restricted range of CO3. Ten absorbance peaks enabling CO3 prediction by mid-infrared (MIR) models were identified and evaluated for individual predictive power and the directness with which peak shape was translated into the loading vectors and cumulative loading function of a partial least squares (PLS) model. An absorbance peak centered at 1796 cm-1 was found to be the most informative with an RMSEP of 13.5 g kg-1 for carbonate prediction. This predictive power is attributed to the strength and sharpness of the peak, and an apparent minimal overlap with confounding co-occurring spectral features of other soil components. Soil CO3 is an excellent example of a soil parameter than can be predicted with great effectiveness and generality, and MIR models could replace direct laboratory measurement in many contexts. This eCommons item holds the datasets from this work.