Recreational microplastics as emerging pollutants: effects of crumb rubber leachate across ecosystems - Sharon T. Pochron; Xiayan Ye; Amith S. Maroli; Arjun K. Venkatesan; Samy Sasoun; Thomas J. Gaylor; Mary Girgis; Morgan A. Jacobellis; Alec Miranda; Johanna A. Mitra; Grace Van Gelder; Samantha H. Byrne; et al. (Chemosphere, 2026)

Cord-blood black carbon particle burden is associated with a C19MC small extracellular vesicle miRNA signature enriched for neurodevelopmental pathways - Houman Kahroba; Kenneth Vanbrabant; Marcel van Herwijnen; Rick Kamps; Matthew Walker; Dagmar Waiblinger; Marcel Ameloot; Michelle Plusquin; John Wright; Tim Nawrot; Theo M. de Kok; Julian Krauskopf (Environmental Research, 2026)

Cord-blood black carbon burden is associated with coordinated inflammatory and heme-metabolic transcriptional programs at birth in Bradford, United Kingdom - Houman Kahroba; Kenneth Vanbrabant; Marcel van Herwijnen; Rick Kamps; Dagmar Waiblinger; Matthew Walker; Marcel Ameloot; Maarten Roeffaers; John Wright; Tim Nawrot; Theo M. de Kok; Julian Krauskopf (Science of The Total Environment, 2026)

Modernization of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program: Rationale and Overview of the THIS-WIC (Telehealth Intervention Strategies for WIC) Project - Catherine Wright; Pascasie Adedze; Alice Ammerman; Lauren Au; Alan Barnosky; Jonathan Blitstein; Karen Castellanos-Brown; Sheryl Cates; Madhur Chandra; Kenneth Kwan Ho Chui; Katharine Clarke; Christina Economos; et al. (Journal of Nutrition Education and Behavior, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Mass spectrometry monitoring of drilling operations in water-doped lunar simulant under cryogenic conditions - Roberto Aguilar Ayala; Morgan A. Crabtree; Matthew L. Hancock; Alexander Jarnot; Janine E. Captain; Julie Kleinhenz; Erin Rezich; Kris Zacny; Vincent Vendiola; Zack Mank; Kenneth C. Wright; Jaime L. Winfield; et al. (Advances in Space Research, 2026)

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

20 Years in the Making: Advancing Postdoctoral Training in Translational Behavioral Oncology - Marilyn Horta; Bianca M. Augusto; Kenneth L. Wright; Paul Jacobsen; Brian Gonzalez; Thomas H. Brandon; Susan T. Vadaparampil; Vani N. Simmons (Journal of Cancer Education, 2025)

Traits and functional diversity of a bee assemblage are linked to aridity - Benjamin D. Turnley; Melanie R. Kazenel; Karen W. Wright; Terry L. Griswold; Jennifer A. Rudgers; Kenneth D. Whitney (Oecologia, 2025)

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Beyond cyanogenesis: Temperature gradients drive environmental adaptation in North American white clover ( Trifolium repens L.) - Wen‐Hsi Kuo; Limei Zhong; Sara J. Wright; David M. Goad; Kenneth M. Olsen (Molecular Ecology, 2024)
Species that repeatedly evolve phenotypic clines across environmental gradients have been highlighted as ideal systems for characterizing the genomic basis of local environmental adaptation. However, few studies have assessed the importance of observed phenotypic clines for local adaptation: conspicuous traits that vary clinally may not necessarily be the most critical in determining local fitness. The present study was designed to fill this gap, using a plant species characterized by repeatedly evolved adaptive phenotypic clines. White clover is naturally polymorphic for its chemical defence cyanogenesis (HCN release with tissue damage); climate‐associated cyanogenesis clines have evolved throughout its native and introduced range worldwide. We performed landscape genomic analyses on 415 wild genotypes from 43 locations spanning much of the North American species range to assess the relative importance of cyanogenesis loci vs. other genomic factors in local climatic adaptation. We find clear evidence of local adaptation, with temperature‐related climatic variables best describing genome‐wide differentiation between sampling locations. The same climatic variables are also strongly correlated with cyanogenesis frequencies and gene copy number variations (CNVs) at cyanogenesis loci. However, landscape genomic analyses indicate no significant contribution of cyanogenesis loci to local adaptation. Instead, several genomic regions containing promising candidate genes for plant response to seasonal cues are identified — some of which are shared with previously identified QTLs for locally adaptive fitness traits in North American white clover. Our findings suggest that local adaptation in white clover is likely determined primarily by genes controlling the timing of growth and flowering in response to local seasonal cues. More generally, this work suggests that caution is warranted when considering the importance of conspicuous phenotypic clines as primary determinants of local adaptation.

Geographic and taxonomic variation in adaptive capacity among mountain-dwelling small mammals: Implications for conservation status and actions - Erik A. Beever; Jennifer L. Wilkening; Peter D. Billman; Lindsey L. Thurman; Kristina A. Ernest; David H. Wright; Alisha M. Gill; April C. Craighead; Nolan A. Helmstetter; Leona K. Svancara; Meghan J. Camp; Sabuj Bhattacharyya; et al. (Biological Conservation, 2023)

Differences in leaf gas exchange strategies explain Quercus rubra and Liriodendron tulipifera intrinsic water use efficiency responses to air pollution and climate change - Justin M. Mathias; Kenneth R. Smith; Kristin E. Lantz; Keanan T. Allen; Marvin J. Wright; Afsoon Sabet; Kristina J. Anderson‐Teixeira; Richard B. Thomas (Global Change Biology, 2023)
Trees continuously regulate leaf physiology to acquire CO 2 while simultaneously avoiding excessive water loss. The balance between these two processes, or water use efficiency (WUE), is fundamentally important to understanding changes in carbon uptake and transpiration from the leaf to the globe under environmental change. While increasing atmospheric CO 2 (iCO 2 ) is known to increase tree intrinsic water use efficiency (iWUE), less clear are the additional impacts of climate and acidic air pollution and how they vary by tree species. Here, we couple annually resolved long‐term records of tree‐ring carbon isotope signatures with leaf physiological measurements of Quercus rubra ( Quru ) and Liriodendron tulipifera ( Litu ) at four study locations spanning nearly 100 km in the eastern United States to reconstruct historical iWUE, net photosynthesis ( A net ), and stomatal conductance to water ( g s ) since 1940. We first show 16%–25% increases in tree iWUE since the mid‐20th century, primarily driven by iCO 2 , but also document the individual and interactive effects of nitrogen (NO x ) and sulfur (SO 2 ) air pollution overwhelming climate. We find evidence for Quru leaf gas exchange being less tightly regulated than Litu through an analysis of isotope‐derived leaf internal CO 2 (C i ), particularly in wetter, recent years. Modeled estimates of seasonally integrated A net and g s revealed a 43%–50% stimulation of A net was responsible for increasing iWUE in both tree species throughout 79%–86% of the chronologies with reductions in g s attributable to the remaining 14%–21%, building upon a growing body of literature documenting stimulated A net overwhelming reductions in g s as a primary mechanism of increasing iWUE of trees. Finally, our results underscore the importance of considering air pollution, which remains a major environmental issue in many areas of the world, alongside climate in the interpretation of leaf physiology derived from tree rings.

Genetic trade‐offs underlie divergent life history strategies for local adaptation in white clover - Sara J. Wright; David M. Goad; Briana L. Gross; Patricio R. Muñoz; Kenneth M. Olsen (Molecular Ecology, 2022)
Local adaptation is common in plants, yet characterization of its underlying genetic basis is rare in herbaceous perennials. Moreover, while many plant species exhibit intraspecific chemical defence polymorphisms, their importance for local adaptation remains poorly understood. We examined the genetic architecture of local adaptation in a perennial, obligately‐outcrossing herbaceous legume, white clover ( Trifolium repens ). This widespread species displays a well‐studied chemical defence polymorphism for cyanogenesis (HCN release following tissue damage) and has evolved climate‐associated cyanogenesis clines throughout its range. Two biparental F 2 mapping populations, derived from three parents collected in environments spanning the U.S. latitudinal species range (Duluth, MN, St. Louis, MO and Gainesville, FL), were grown in triplicate for two years in reciprocal common garden experiments in the parental environments (6,012 total plants). Vegetative growth and reproductive fitness traits displayed trade‐offs across reciprocal environments, indicating local adaptation. Genetic mapping of fitness traits revealed a genetic architecture characterized by allelic trade‐offs between environments, with 100% and 80% of fitness QTL in the two mapping populations showing significant QTL×E interactions, consistent with antagonistic pleiotropy. Across the genome there were three hotspots of QTL colocalization. Unexpectedly, we found little evidence that the cyanogenesis polymorphism contributes to local adaptation. Instead, divergent life history strategies in reciprocal environments were major fitness determinants: selection favoured early investment in flowering at the cost of multiyear survival in the southernmost site versus delayed flowering and multiyear persistence in the northern environments. Our findings demonstrate that multilocus genetic trade‐offs contribute to contrasting life history characteristics that allow for local adaptation in this outcrossing herbaceous perennial.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Ancient Sea Level as Key to the Future - Kenneth Miller; John Schmelz; James Browning; Robert Kopp; Gregory Mountain; James Wright (Oceanography, 2020)

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Nutritional composition of honey bee food stores vary with floral composition - Philip Donkersley; Glenn Rhodes; Roger W. Pickup; Kevin C. Jones; Eileen F. Power; Geraldine A. Wright; Kenneth Wilson (Oecologia, 2017)

Contrasting outcomes of species‐ and community‐level analyses of the temporal consistency of functional composition - Masatoshi Katabuchi; S. Joseph Wright; Nathan G. Swenson; Kenneth J. Feeley; Richard Condit; Stephen P. Hubbell; Stuart J. Davies (Ecology, 2017)
Multiple anthropogenic drivers affect every natural community, and there is broad interest in using functional traits to understand and predict the consequences for future biodiversity. There is, however, no consensus regarding the choice of analytical methods. We contrast species‐ and community‐level analyses of change in the functional composition for four traits related to drought tolerance using three decades of repeat censuses of trees in the 50‐ha Forest Dynamics Plot on Barro Colorado Island, Panama. Community trait distributions shifted significantly through time, which may indicate a shift toward more drought tolerant species. However, at the species level, changes in abundance were unrelated to trait values. To reconcile these seemingly contrasting results, we evaluated species‐specific contributions to the directional shifts observed at the community level. Abundance changes of just one to six of 312 species were responsible for the community‐level shifts observed for each trait. Our results demonstrate that directional changes in community‐level functional composition can result from idiosyncratic change in a few species rather than widespread community‐wide changes associated with functional traits. Future analyses of directional change in natural communities should combine community‐, species‐, and possibly individual‐level analyses to uncover relationships with function that can improve understanding and enable prediction.

The Microbiota, Immunoregulation, and Mental Health: Implications for Public Health - Christopher A. Lowry; David G. Smith; Philip H. Siebler; Dominic Schmidt; Christopher E. Stamper; James E. Hassell; Paula S. Yamashita; James H. Fox; Stefan O. Reber; Lisa A. Brenner; Andrew J. Hoisington; Teodor T. Postolache; et al. (Current Environmental Health Reports, 2016)

Melatonin administration alters nicotine preference consumption via signaling through high-affinity melatonin receptors - William J. Horton; Hannah J. Gissel; Jennifer E. Saboy; Kenneth P. Wright; Jerry A. Stitzel (Psychopharmacology, 2015)

Revisiting the past to foretell the future: summer temperature and habitat area predict pika extirpations in California - Joseph A. E. Stewart; John D. Perrine; Lyle B. Nichols; James H. Thorne; Constance I. Millar; Kenneth E. Goehring; Cody P. Massing; David H. Wright (Journal of Biogeography, 2015)
Aim The American pika ( Ochotona princeps ) appears to have experienced climate‐mediated upslope range contraction in the Great Basin of North America, but this result has not yet been extended to other portions of the pika's range. Our goals were: first, to determine the environmental parameters that most influence current pika distribution within California; second, to infer whether these constraints explain extirpations that have occurred in California; third, to predict future extirpations; and fourth, to advance methods for assessing the degree to which pikas and other climate‐sensitive mammals are threatened by climate change. Location Historical pika record locations in California, USA , spanning four degrees of latitude and longitude, from Mount Shasta to the southern Sierra Nevada. Methods We identified 67 precise historical pika record locations and surveyed them exhaustively, over multiple years, to determine whether pika populations persist at those sites. We used an information theoretic approach and logistic regression to model current pika occupancy as a function of 16 environmental variables, tested our best‐performing model as a predictor of historical occupancy, and then used our model to predict future pika occupancy given anticipated climate change. Results Pikas no longer occurred at 10 of 67 (15%) historical sites in California. The best predictors of occupancy were average summer temperature and talus habitat area within a 1‐km radius. A logistic model fitted to this relationship correctly predicted current occupancy at 94% of sites and correctly hindcasted past occupancy at 93% of sites, suggesting that the model has strong temporal transferability. Depending on the future climate scenario, our model projects that by 2070 pikas will be extirpated from 39% to 88% of these historical sites in California. Main conclusions Our simple species distribution model for pikas performs remarkably well for both current and historical periods. Pika distribution appears to be governed primarily by behavioural restrictions mediated by summer temperature and by the configuration of talus habitat available to pikas locally. Pikas, and other montane species in the western USA, may be subjected to above‐average exposure to climate change because summer temperature is projected to rise more than annual temperature.

Estimated effects of climate change on flood vulnerability of U.S. bridges - Len Wright; Paul Chinowsky; Kenneth Strzepek; Russell Jones; Richard Streeter; Joel B. Smith; Jean-Marc Mayotte; Anthony Powell; Lesley Jantarasami; William Perkins (Mitigation and Adaptation Strategies for Global Change, 2012)

A 180-Million-Year Record of Sea Level and Ice Volume Variations from Continental Margin and Deep-Sea Isotopic Records - Kenneth Miller; Gregory Mountain; James Wright; James Browning (Oceanography, 2011)

Adapting to climate change: an integrated biophysical and economic assessment for Mozambique - Channing Arndt; Kenneth Strzepeck; Finn Tarp; James Thurlow; Charles Fant; Len Wright (Sustainability Science, 2011)

Historical and paleolimnological evidence for expansion of Lake Athabasca (Canada) during the Little Ice Age - R. Niloshini Sinnatamby; Yi Yi; Michael A. Sokal; Kenneth P. Clogg-Wright; Taro Asada; Sheila R. Vardy; Tammy L. Karst-Riddoch; William M. Last; John W. Johnston; Roland I. Hall; Brent B. Wolfe; Thomas W. D. Edwards (Journal of Paleolimnology, 2010)

Decelerating growth in tropical forest trees - Kenneth J. Feeley; S. Joseph Wright; M. N. Nur Supardi; Abd Rahman Kassim; Stuart J. Davies (Ecology Letters, 2007)
The impacts of global change on tropical forests remain poorly understood. We examined changes in tree growth rates over the past two decades for all species occurring in large (50‐ha) forest dynamics plots in Panama and Malaysia. Stem growth rates declined significantly at both forests regardless of initial size or organizational level (species, community or stand). Decreasing growth rates were widespread, occurring in 24–71% of species at Barro Colorado Island, Panama (BCI) and in 58–95% of species at Pasoh, Malaysia (depending on the sizes of stems included). Changes in growth were not consistently associated with initial growth rate, adult stature, or wood density. Changes in growth were significantly associated with regional climate changes: at both sites growth was negatively correlated with annual mean daily minimum temperatures, and at BCI growth was positively correlated with annual precipitation and number of rainfree days (a measure of relative insolation). While the underlying cause(s) of decelerating growth is still unresolved, these patterns strongly contradict the hypothesized pantropical increase in tree growth rates caused by carbon fertilization. Decelerating tree growth will have important economic and environmental implications.

The symbiotic role of marine microbes on living surfaces - Evelyn Armstrong; Liming Yan; Kenneth G. Boyd; Phillip C. Wright; J. Grant Burgess (Hydrobiologia, 2001)

Sex linkage in salmonids: Evidence from a hybridized genome of brook trout and arctic charr - Bernie May; Kenneth R. Johnson; James E. Wright (Biochemical Genetics, 1989)

Joint segregation of biochemical loci in Salmonidae. III. Linkage associations in Salmonidae including data from rainbow trout (Salmo gairdneri) - Bernie May; James E. Wright; Kenneth R. Johnson (Biochemical Genetics, 1982)

s 60th annual meeting The Potato Association of America - R. Kunkel; N. M. Holstad; R. E. Thornton; J. C. Bishop; Herman Timm; V. C. Shekhar; W. M. Iritani; Thornton Robert; Gary Hyde; Malamud Oscar; Robert B. O’Keefe; Mccown Brent; et al. (American Journal of Potato Research, 1976)

s of papers presented at Annual Meeting - F. Heiligman; J. R. Wagner; WM. G. Hoyman; Jack R. Wallin; D. R. Isleib; N. R. Thompson; Robert H. Johansen; Knutson Kenneth; Carl J. Eide; F. A. Krantz; Florian Lauer; F. I. Lauer; et al. (American Journal of Potato Research, 1957)