ScholarWorks

ScholarWorks is an open access repository for the capture of the intellectual work of Montana State University (MSU) in support of its teaching, research and service missions. MSU ScholarWorks is a central point of discovery for accessing, collecting, sharing, preserving, and distributing knowledge to the Montana State University community and the world.

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Scholarship & Research

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Right-to-farm laws: Legal shields of Big Ag [Book review]
(Lyson Center for Civic Agriculture and Food Systems, 2026-01)
Ebel, Roland
In the 1970s and 1980s, U.S. agriculture faced its worst crisis since the Great Depression. Dire finances due to collapsed land and commodity prices forced almost a third of farms nationwide to close, negatively affecting rural economies beyond farming (Barnett, 2000). During this period, right-to-farm (RTF) state laws were enacted to protect farmers from nuisance lawsuits resulting from agricultural practices, such as complaints about noise or odor. These laws were promoted to safeguard family farms and slow down the urbanization of rural areas, a trend contributing to the emergence of post-agrarian rural societies in the U.S. (Salamon, 2007).
Not all purslane (Portulaca oleracea) is equal: varietal differences under greenhouse conditions
(CABI Publishing, 2026-05)
Ebel, Roland
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Walterskirchen, Josephine
Purslane (Portulaca oleracea L.) is a cosmopolitan annual herb with succulent foliage, widely consumed raw, cooked or pickled, and distinguished by its high α-linolenic acid (ALA) content, higher than that of common leafy greens. Purslane also provides linoleic acid (LA), diverse minerals, as well as vitamins A, C and E, underscoring its nutritional potential. Although cultivated commercially in parts of Asia, Europe and Mexico, purslane is often treated as a weed among conventional farmers. In temperate and cold climates, greenhouse production of purslane is essential to ensure year-round supply, yet research on promising varieties has been limited. We evaluated five commercially available purslane varieties (‘Red Gruner Microgreen Seed’, ‘Green Purslane’, ‘Scarlet’, ‘French Green Leaf’ and ‘Heirloom Verdolaga’) for growth, biomass and fatty acid profiles under greenhouse conditions. In addition to dry biomass, we measured plant height and diameter, which were integrated into a z-score growth index to assess temporal growth dynamics. The fatty acid profile of each variety was quantified using the Folch method. Biomass differed among varieties. ‘Green Purslane’ produced the highest yield (0.68 g plant−1), exceeding ‘Scarlet,’ ‘Heirloom Verdolaga’ and ‘Red Gruner,’ while ‘French Green’ showed intermediate yield. Growth trajectories were fastest for ‘French Green’ and ‘Red Gruner’. Although statistical analysis of this parameter was not performed, fatty acid composition of ‘Green’ showed a trend towards superiority, with 421 mg kg−1 LA, an exceptional 1625 mg kg−1 ALA, the lowest LA/ALA ratio of 0.26, and the highest polyunsaturated fatty acid proportion (73%), exceeding published ranges. We identified ‘Green’ as a strong candidate for indoor purslane production.
Ecology of methyl-coenzyme M reductase encoding Thermoproteota
(Elsevier BV, 2025-12)
Jay, Zackary J.
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Kellom, Matthew
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Eloe-Fadrosh, Emiley
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Hatzenpichler, Roland
The recent demonstration that members of at least three classes of archaea affiliated with the Thermoproteota superphylum are involved in the production of the climate-active gas methane has sparked discussions about how well we understand the diversity of methanogens. Here, we show that members of all three of these lineages, as well as several other, yet uncultured and physiologically uncharacterized groups within the Thermoproteota that encode the key enzyme of anaerobic methane cycling, methyl-coenzyme M reductase (MCR), are widely distributed in anoxic ecosystems. We postulate that the taxonomic, metabolic, and ecological diversity of methanogenic and MCR-encoding Thermoproteota are poorly understood, and that the contribution of methylotrophic and thermoproteotal methanogenesis to methane production is largely unknown. We hypothesize that thermoproteotal methanogens could contribute, potentially substantially, to methane emissions in many anoxic environments that harbor methylated precursors, including wetlands, sediments, peat, rice paddies, wastewater sludge, and geothermal systems. We highlight the necessity to experimentally test the (eco)physiology of these widely distributed archaea using both culture-dependent (in vitro) and culture-independent (in situ) approaches to assess their potential contribution to methane emissions. Last, we stress the importance of remaining agnostic about the physiology of MCR-encoding Thermoproteota in the absence of experimental data because most of these archaea also carry the genetic potential to grow non-methanogenically.
Data fusion approach for predicting high resolution estimates of crop evapotranspiration
(Springer Science and Business Media LLC, 2025-08)
Nazrul Shimim, Farshina
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Fortin, Mathieu Pagé
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Nocco, Mallika
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Whitaker, Bradley
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Gal, Andrew
Purpose. Spatial estimates of crop water use during the growing season are crucial for precision irrigation management, especially under conditions of water scarcity and climate change. The on-farm trial detailed in this paper focuses on a processing tomato field in the Sacramento Valley of California. Methodology. Different meteorological parameters, including temperature, precipitation, relative humidity, shortwave radiation, and wind speed, were measured hourly at three specific locations in the field using on-the-ground sensors. Additionally, these sensors captured canopy surface reflectance properties in multiple bands, covering the wavelength range of 420–956 nm. The collected hourly meteorological and crop biophysical data were used to predict reference evapotranspiration (ETo) and calculate crop coefficients (Kc), which were then used to derive point-based estimates of canopy evapotranspiration (ETc). High-resolution multispectral and thermal aerial imagery were collected eight times during the growing season of 2021 (June–August). Several canopy properties, including leaf area index and crop height, were computed from the aerial imagery. The spatial data was combined with meteorological information from nearby weather stations to map actual evapotranspiration (ETa) with the High-Resolution Mapping of EvapoTranspiration (HRMET) model at 5 m resolution. Analysis. The eight ETa maps and the daily sensor-based ETc estimates for the entire growing season were combined to predict high-resolution ETa maps for days when aerial imagery was not collected. Three different algorithms for prediction were implemented: Linear Regression, Weighted Piecewise Linear Interpolation, and Forward Interpolation. Results. The performance of these algorithms was evaluated using metrics such as Nash–Sutcliffe Efficiency (NSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Kling-Gupta Efficiency (KGE). Results indicate that Forward Interpolation is the most suitable algorithm (NSE = 0.694; MAE = 0.06; RMSE = 0.07; KGE = 0.894) for gap-filling and approximating daily high-resolution ETa maps (average hourly estimates for each day) for the entire growing season for our study site. Conclusion. This innovative procedure aims to establish a decision support system for efficient irrigation scheduling, fusing different sources of spatiotemporal information to optimize irrigation in drought-prone areas.
Petri net on expanded networks computes the dynamics of finite multilevel models
(The Royal Society, 2025-08)
Andreas, Elizabeth
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Quist, Eli
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Gedeon, Tomas
We discuss connections between different types of models of gene‑regulatory network dynamics that include Boolean, finite multilevel and monotone Boolean models. We recast the methodology of describing attractors of Boolean and finite multilevel dynamics using motifs of the expanded network eRN in terms of Petri net dynamics on eRN. We show that the Petri net can be used to recover dynamics of the finite multilevel dynamics on the state transition graph. We conclude with new insights that the expanded network viewpoint offers for the robustness of equilibria and complex attractors.