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Grapevine rootstocks are gaining importance in viticulture as a strategy to combat abiotic challenges, as well as enhance scion physiology. Direct leaf-level physiological parameters like net assimilation rate, stomatal conductance to water vapor, quantum yield of PSII, and transpiration can illuminate the rootstock effect on scion physiology. However, these measures are time-consuming and limited to leaf-level analysis. This study used different rootstocks to investigate the potential application of aerial hyperspectral imagery in the estimation of canopy level measurements. A statistical framework was developed as an ensemble stacked regression (REGST) that aggregated five different individual machine learning algorithms: Least absolute shrinkage and selection operator (Lasso), Partial least squares regression (PLSR), Ridge regression (RR), Elastic net (ENET), and Principal component regression (PCR) to optimize high-throughput assessment of vine physiology. In addition, a Convolutional Neural Network (CNN) algorithm was integrated into an existing REGST, forming a hybrid CNN-REGST model with the aim of capturing patterns from the hyperspectral signal. Based on the findings, the performance of individual base models exhibited variable prediction accuracies. In most cases, Ridge Regression (RR) demonstrated the lowest test Root Mean Squared Error (RMSE). The ensemble stacked regression model (REGST) outperformed the individual machine learning algorithms with an increase in R2 by (0.03 to 0.1). The performances of CNN-REGST and REGST were similar in estimating the four different traits. Overall, these models were able to explain approximately 55–67% of the variation in the actual ground-truth data. This study suggests that hyperspectral features integrated with powerful AI approaches show great potential in tracing functional traits in grapevines. 

Molecular hydrogen is produced by the fermentation of organic matter and consumed by organisms including hydrogenotrophic methanogens and sulfate reducers in anoxic marine sediment. The thermodynamic feasibility of these metabolisms depends strongly on organic matter reactivity and hydrogen concentrations; low organic matter reactivity and high hydrogen concentrations can inhibit fermentation so when organic matter is poor, fermenters might form syntrophies with methanogens and/or sulfate reducers who alleviate thermodynamic stress by keeping hydrogen concentrations low and tightly controlled. However, it is unclear how these metabolisms effect porewater hydrogen concentrations in natural marine sediments of different organic matter reactivities. MethodsWe measured aqueous concentrations of hydrogen, sulfate, methane, dissolved inorganic carbon, and sulfide with high-depth-resolution and 16S rRNA gene assays in sediment cores with low carbon reactivity in White Oak River (WOR) estuary, North Carolina, and those with high carbon reactivity in Cape Lookout Bight (CLB), North Carolina. We calculated the Gibbs energies of sulfate reduction and hydrogenotrophic methanogenesis. ResultsHydrogen concentrations were significantly higher in the sulfate reduction zone at CLB than WOR (mean: 0.716 vs. 0.437 nM H₂) with highly contrasting hydrogen profiles. At WOR, hydrogen was extremely low and invariant (range: 0.41–0.52 nM H₂) in the upper 15 cm. Deeper than 15 cm, hydrogen became more variable (range: 0.312–2.56 nM H₂) and increased until methane production began at ~30 cm. At CLB, hydrogen was highly variable in the upper 15 cm (range: 0.08–2.18 nM H₂). Ratios of inorganic carbon production to sulfate consumption show AOM drives sulfate reduction in WOR while degradation of organics drive sulfate reduction in CLB. DiscussionWe conclude more reactive organic matter increases hydrogen concentrations and their variability in anoxic marine sediments. In our AOM-dominated site, WOR, sulfate reducers have tight control on hydrogen via consortia with fermenters which leads to the lower observed variance due to interspecies hydrogen transfer. After sulfate depletion, hydrogen accumulates and becomes variable, supporting methanogenesis. This suggests that CLB’s more reactive organic matter allows fermentation to occur without tight metabolic coupling of fermenters to sulfate reducers, resulting in high and variable porewater hydrogen concentrations that prevent AOM from occurring through reverse hydrogenotrophic methanogenesis.