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We investigated the effect of supplemental CO2, gibberellic acid (GA3), and light on the quality and yield of Humulus lupulus L. strobili (cones). When applied separately, CO2 and light increased the yield by 22% and 43%, respectively, and had a significant effect on the components of cone mass and quality. Exogenous GA3 increased flower set; however, the yield decreased by approximately 33%. Combining CO2, GA3, and light, and any combination thereof, resulted in significant increases in flower set and cone yield enhancement compared to separate applications. A synergistic effect occurred when some factors were combined. For example, the combination of CO2 and light resulted in a yield increase of approximately 122%. The combination of all three resources, CO2, GA3, and light, resulted in an approximate 185% yield increase per plant. Thus, in comparison to the addition of one supplementary resource, a greater increase in yield resulted from the combination of two or more supplemental resources. Flower set stimulation due to GA3 decreased cone alpha- and beta-acid quality attributes, unless combined with CO2 and light as additional carbohydrate-generating resources. Additional research is needed to close the hop yield gap between current hop yields and the achievement of the plant's genetic potential. [ABSTRACT FROM AUTHOR]

Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V(cm)) rate scaled to 25 degrees C (i.e., V(c),25; μmol CO2 x m(-2)x s(-1)) and maximum electron transport rate (J(max)) scaled to 25 degrees C (i.e., J25; μmol electron x m(-2) x s(-1)) at the global scale. Our results showed that the percentage of variation in observed V(c),25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2-2.5 times and 6-9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain -56% and -66% of the variation in V(c),25 and J25 at the global scale, respectively. Our analyses suggest that model projections of plant photosynthetic capacity and hence land-atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.

Abstract Background The identification of the loci and specific alleles underlying variation in quantitative traits is an important goal for evolutionary biologists and breeders. Despite major advancements in genomics technology, moving from QTL to causal alleles remains a major challenge in genetics research. Near-isogenic lines are the ideal raw material for QTL validation, refinement of QTL location and, ultimately, gene discovery. Results In this study, a population of 75 Arabidopsis thaliana near-isogenic lines was developed from an existing recombinant inbred line (RIL) population derived from a cross between physiologically divergent accessions Kas-1 and Tsu-1. First, a novel algorithm was developed to utilize genome-wide marker data in selecting RILs fully isogenic to Kas-1 for a single chromosome. Seven such RILs were used in 2 generations of crossing to Tsu-1 to create BC1 seed. BC1 plants were genotyped with SSR markers so that lines could be selected that carried Kas-1 introgressions, resulting in a population carrying chromosomal introgressions spanning the genome. BC1 lines were genotyped with 48 genome-wide SSRs to identify lines with a targeted Kas-1 introgression and the fewest genomic introgressions elsewhere. 75 such lines were selected and genotyped at an additional 41 SNP loci and another 930 tags using 2b-RAD genotyping by sequencing. The final population carried an average of 1.35 homozygous and 2.49 heterozygous introgressions per line with average introgression sizes of 5.32 and 5.16 Mb, respectively. In a simple case study, we demonstrate the advantage of maintaining heterozygotes in our library whereby fine-mapping efforts are conducted simply by self-pollination. Crossovers in the heterozygous interval during this single selfing generation break the introgression into smaller, homozygous fragments (sub-NILs). Additionally, we utilize a homozygous NIL for validation of a QTL underlying stomatal conductance, a low heritability trait. Conclusions The present results introduce a new and valuable resource to the Brassicaceae research community that enables rapid fine-mapping of candidate loci in parallel with QTL validation. These attributes along with dense marker coverage and genome-wide chromosomal introgressions make this population an ideal starting point for discovery of genes underlying important complex traits of agricultural and ecological significance.

Mineral nutrient requirements of Cannabis sativa 'cherry wine' (hemp) were studied under steady-state nutrition where nutrients and water (H2O) removed via transpiration uptake were replenished daily. Nitrate (NO3−), potassium (K+), and H2O uptake for hemp are presented for 24 h periods over the course of vegetative growth. This can estimate the changes in potential NO3− and K+ uptake rate in accordance with demand. Daily nutrient uptake and transpiration rates are discussed relative to the plant's H2O uptake and relative growth rate. Non-limiting conditions were achieved at base nutrient recipe NO3− and K+ concentrations of 201 and 290 ppm. Biomass accumulation and stem caliper increment increase over the vegetative growth cycle were found to have a positive linear correlation with NO3−, K+, and H2O uptake. Consequently, NO3− and K+ concentrations in the irrigation solution can be steadily increased throughout the hemp vegetative cycle in relation to the driving relative variables growth and transpiration rate. In so doing, a time dimension is introduced concerning the nutrient amount supplied relative to plant biomass accumulation and nutrient uptake via the transpiration stream. Overall, lower amounts of NO3− and K+ were needed to optimize plant growth than previously thought by industry professionals. [ABSTRACT FROM AUTHOR]

Boreal forests are crucial in regulating global vegetation‐atmosphere feedbacks, but the impact of climate change on boreal tree carbon fluxes is still unclear. Given the sensitivity of global vegetation models to photosynthetic and respiration parameters, we determined how predictions of net carbon gain (C‐gain) respond to variation in these parameters using a stand‐level model (MAESTRA). We also modelled how thermal acclimation of photosynthetic and respiratory temperature sensitivity alters predicted net C‐gain responses to climate change. We modelled net C‐gain of seven common boreal tree species under eight climate scenarios across a latitudinal gradient to capture a range of seasonal temperature conditions. Physiological parameter values were taken from the literature together with different approaches for thermally acclimating photosynthesis and respiration. At high latitudes, net C‐gain was stimulated up to 400% by elevated temperatures and CO2 in the autumn but suppressed at the lowest latitudes during midsummer under climate scenarios that included warming. Modelled net C‐gain was more sensitive to photosynthetic capacity parameters (Vcmax, Jmax, Arrhenius temperature response parameters, and the ratio of Jmax to Vcmax) than stomatal conductance or respiration parameters. The effect of photosynthetic thermal acclimation depended on the temperatures where it was applied: acclimation reduced net C‐gain by 10%–15% within the temperature range where the equations were derived but decreased net C‐gain by 175% at temperatures outside this range. Thermal acclimation of respiration had small, but positive, impacts on net C‐gain. We show that model simulations are highly sensitive to variation in photosynthetic parameters and highlight the need to better understand the mechanisms and drivers underlying this variability (e.g., whether variability is environmentally and/or biologically driven) for further model improvement. Photosynthetic parameters have strong impacts on the temperature response of net carbon assimilation, which can alter the magnitude and direction of modelled carbon gain responses to climate warming. [ABSTRACT FROM AUTHOR]

Abstract: Photosynthetic temperature acclimation could strongly affect coupled vegetation–atmosphere feedbacks in the global carbon cycle, especially as the climate warms. Thermal acclimation of photosynthesis can be modelled as changes in the parameters describing the direct effect of temperature on photosynthetic capacity (i.e., activation energy, Ea; deactivation energy, Hd; entropy parameter, ΔS) or the basal value of photosynthetic capacity (i.e., photosynthetic capacity measured at 25°C). However, the impact of acclimating these parameters (individually or in combination) on vegetative carbon gain is relatively unexplored. Here we compare the ability of 66 photosynthetic temperature acclimation scenarios to improve the ability of a spatially explicit canopy carbon flux model, MAESTRA, to predict eddy covariance data from a loblolly pine forest. We show that: (1) incorporating seasonal temperature acclimation of basal photosynthetic capacity improves the model's ability to capture seasonal changes in carbon fluxes and outperforms acclimation of other single factors (i.e., Ea or ΔS alone); (2) multifactor scenarios of photosynthetic temperature acclimation provide minimal (if any) improvement in model performance over single factor acclimation scenarios; (3) acclimation of Ea should be restricted to the temperature ranges of the data from which the equations are derived; and (4) model performance is strongly affected by the Hd parameter. We suggest that a renewed effort be made into understanding whether basal photosynthetic capacity, Ea, Hd and ΔS co‐acclimate across broad temperature ranges to determine whether and how multifactor thermal acclimation of photosynthesis occurs. [ABSTRACT FROM AUTHOR]

The Ball-Berry (BB) model of stomatal conductance (gs) is frequently coupled with a model of assimilation to estimate water and carbon exchanges in plant canopies. The empirical slope ( m) and 'residual' gs (g0) parameters of the BB model influence transpiration estimates, but the time-intensive nature of measurement limits species-specific data on seasonal and stress responses. We measured m and g0 seasonally and under different water availability for maize and sunflower. The statistical method used to estimate parameters impacted values nominally when inter-plant variability was low, but had substantial impact with larger inter-plant variability. Values for maize ( m = 4.53 ± 0.65; g0 = 0.017 ± 0.016 mol m−2 s−1) were 40% higher than other published values. In maize, we found no seasonal changes in m or g0, supporting the use of constant seasonal values, but water stress reduced both parameters. In sunflower, inter-plant variability of m and g0 was large ( m = 8.84 ± 3.77; g0 = 0.354 ± 0.226 mol m−2 s−1), presenting a challenge to clear interpretation of seasonal and water stress responses - m values were stable seasonally, even as g0 values trended downward, and m values trended downward with water stress while g0 values declined substantially. [ABSTRACT FROM AUTHOR]

Transpiration is controlled by evaporative demand and stomatal conductance ( gs), and there can be substantial genetic variation in gs. A key parameter in empirical models of transpiration is minimum stomatal conductance ( g0), a trait that can be measured and has a large effect on gs and transpiration. In A rabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci ( QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. [ABSTRACT FROM AUTHOR]