10 research outputs found
Tomato root transcriptome response to a nitrogen-enriched soil patch
Background: Nitrogen (N), the primary limiting factor for plant growth and yield in agriculture, has a patchy distribution in soils due to fertilizer application or decomposing organic matter. Studies in solution culture oversimplify the complex soil environment where microbial competition and spatial and temporal heterogeneity challenge roots\u27 ability to acquire adequate amounts of nutrients required for plant growth. In this study, various ammonium treatments (as 15N) were applied to a discrete volume of soil containing tomato (Solanum lycopersicum) roots to simulate encounters with a localized enriched patch of soil. Transcriptome analysis was used to identify genes differentially expressed in roots 53 hrs after treatment.
Results: The ammonium treatments resulted in significantly higher concentrations of both ammonium and nitrate in the patch soil. The plant roots and shoots exhibited increased levels of 15N over time, indicating a sustained response to the enriched environment. Root transcriptome analysis identified 585 genes differentially regulated 53 hrs after the treatments. Nitrogen metabolism and cell growth genes were induced by the high ammonium (65 μg NH4 +-N g-1 soil), while stress response genes were repressed. The complex regulation of specific transporters following the ammonium pulse reflects a simultaneous and synergistic response to rapidly changing concentrations of both forms of inorganic N in the soil patch. Transcriptional analysis of the phosphate transporters demonstrates cross-talk between N and phosphate uptake pathways and suggests that roots increase phosphate uptake via the arbuscular mycorrhizal symbiosis in response to N.
Conclusion: This work enhances our understanding of root function by providing a snapshot of the response of the tomato root transcriptome to a pulse of ammonium in a complex soil environment. This response includes an important role for the mycorrhizal symbiosis in the utilization of an N patch.
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Modeling vegetative vigour in grapevine: unraveling underlying mechanisms
Mechanistic modeling constitutes a powerful tool to unravel complex biological phenomena. This study describes the construction of a mechanistic, dynamic model for grapevine plant growth and canopy biomass (vigor). To parametrize and validate the model, the progeny from a cross of Ramsey (Vitis champinii) × Riparia Gloire (V. riparia) was evaluated. Plants with different vigor were grown in a greenhouse during the summer of 2014 and 2015. One set of plants was grafted with Cabernet Sauvignon. Shoot growth rate (b), leaf area (LA), dry biomass, whole plant and root specific hydraulic conductance (kH and Lpr), stomatal conductance (gs), and water potential (Ψ) were measured. Partitioning indices and specific leaf area (SLA) were calculated. The model includes an empirical fit of a purported seasonal pattern of bioactive GAs based on published seasonal evolutionary levels and reference values. The model provided a good fit of the experimental data, with R = 0.85. Simulation of single trait variations defined the individual effect of each variable on vigor determination. The model predicts, with acceptable accuracy, the vigor of a young plant through the measurement of Lpr and SLA. The model also permits further understanding of the functional traits that govern vigor, and, ultimately, could be considered useful for growers, breeders and those studying climate change.EEA MendozaFil: Hugalde, Ines Pilar. Instituto Nacional de TecnologÃa Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Agüero, Cecilia B. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Barrios-Masias, Felipe H. University of California at Davis. Department of Viticulture and Enology; Estados Unidos. University of Nevada. Department of Agriculture, Veterinary and Rangeland Sciences; Estados UnidosFil: Romero, Nina. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Nguyen, Andy Viet. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Riaz, Summaira. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Piccoli, Patricia NoemÃ. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - Mendoza. Instituto de BiologÃa AgrÃcola de Mendoza. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Instituto de BiologÃa AgrÃcola de Mendoza; ArgentinaFil: McElrone, Andrew J. University of California at Davis. Department of Viticulture and Enology; Estados Unidos. US Department of Agriculture. ARS; Estados UnidosFil: Walker, M. Andrew. University of California at Davis. Department of Viticulture and Enology; Estados UnidosFil: Vila, Hernan Felix. Instituto Nacional de TecnologÃa Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentin
Leaf Gas Exchange Performance of Ten Quinoa Genotypes under a Simulated Heat Wave
Quinoa (Chenopodium quinoa Willd.) is a highly nutritious crop that is resilient to a wide range of abiotic stresses; however, sensitivity to high temperatures is regarded as an impediment to adoption in regions prone to heat waves. Heat stress is usually associated with a decrease in crop reproductive capacity (e.g., pollen viability), yet little is known about how leaf physiological performance of quinoa is affected by high temperatures. Several trials were conducted to understand the effect of high temperatures, without confounding stressors such as drought, on ten selected quinoa genotypes considered to encompass heat sensitive and heat tolerant plant material. Plants were grown under favorable temperatures and exposed to two temperature treatments over four consecutive days. The heat treatment simulated heat waves with maximum and minimum temperatures higher during the day and night, while the control treatment was maintained under favorable temperatures (maximum and minimum temperatures for ‘Heat’: 45/30 °C and ‘Control’: 20/14 °C). Leaf gas exchange (day), chlorophyll fluorescence (predawn and day) and dark respiration (night) were measured. Results show that most quinoa genotypes under the heat treatment increased their photosynthetic rates and stomatal conductance, resulting in a lower intrinsic water use efficiency. This was partly corroborated by an increase in the maximum quantum yield of photosystem II (Fv/Fm). Dark respiration decreased under the heat treatment in most genotypes, and temperature treatment did not affect aboveground biomass by harvest (shoot and seeds). These results suggest that heat stress alone favors increases in leaf carbon assimilation capacity although the tradeoff is higher plant water demand, which may lead to plant water stress and lower yields under non-irrigated field conditions
Cultivar mixtures of processing tomato in an organic agroecosystem
At an organic farm in California, managed biodiversity was manipulated by establishing a mustard cover crop (MCC) and fallow during winter, and after incorporation, tomato mixtures of one, three, and five cultivars were planted in the spring (1-cv, 3-cv, and 5-cv, respectively). It was hypothesized that cultivar mixtures may increase yields over a monoculture if disease pressure or nitrogen (N) availability is affected by the previous cover crop. The monoculture (1-cv) of the grower’s preferred cultivar was compared with mixtures of it and other high-yielding cultivars in the region. Soil nitrogen, soil microbial biomass carbon (MBC), soil emissions of carbon dioxide (CO2) and nitrous oxide (N2O), crop nutrient uptake, biomass, fruit quality, intercepted photosynthetically active radiation (PAR), and disease symptoms were measured. The MCC reduced soil N leaching potential during winter and immobilized soil N early in the tomato season as suggested by higher soil MBC and CO2 emissions. Tomatoes had higher PAR, aboveground biomass, fruit yields, and harvest index in the winter fallow than in the winter MCC, likely due to higher N availability in the fallow plots after transplanting. All cultivar mixtures had fairly similar yield and shoot biomass within fallow and MCC, probably explained by the low genetic diversity among California modern tomato cultivars. However, at mid-season (75 days after planting (DAP)), the 3-cv mixture had higher shoot and fruit biomass, by 46% and 63%, than the monoculture in the MCC, indicating some plasticity under lower N availability. In the fallow treatment, soil CO2 emissions were lower in the 3-cv mixture than the monoculture at 77 and 100 DAP. Tomatoes in the 3-cv mixture were redder than the monoculture. The 3-cv mixture thus had some minor advantages compared with the monoculture, but overall, there was little evidence of higher ecosystem functions from mixtures vs. monoculture. Further research on mixtures of processing tomatoes may only be warranted for conditions of higher environmental stress than occur in California organic farms or if specific genotypic traits become available such as for disease resistance or improved nutrient uptake
Quinoa Abiotic Stress Responses: A Review
Quinoa (
Willd.) is a genetically diverse Andean crop that has earned special attention worldwide due to its nutritional and health benefits and its ability to adapt to contrasting environments, including nutrient-poor and saline soils and drought stressed marginal agroecosystems. Drought and salinity are the abiotic stresses most studied in quinoa; however, studies of other important stress factors, such as heat, cold, heavy metals, and UV-B light irradiance, are severely limited. In the last few decades, the incidence of abiotic stress has been accentuated by the increase in unpredictable weather patterns. Furthermore, stresses habitually occur as combinations of two or more. The goals of this review are to: (1) provide an in-depth description of the existing knowledge of quinoa's tolerance to different abiotic stressors; (2) summarize quinoa's physiological responses to these stressors; and (3) describe novel advances in molecular tools that can aid our understanding of the mechanisms underlying quinoa's abiotic stress tolerance
Floral hemp (Cannabis sativa L.) responses to nitrogen fertilization under field conditions in the high desert.
While most studies on floral hemp (Cannabis sativa L.) concur that additions of nitrogen (N) increase plant growth, the performance of floral hemp is heavily influenced by environmental conditions, management and cultivar selection. In regions with a short growing season, the availability of soil N may determine plant developmental rates, final inflorescence biomass and cannabinoid concentrations, but no studies have addressed this for field-grown hemp under high-desert conditions. This field study evaluated the effect of no supplemental N and N fertilization at 90 kg ha-1 on three hemp cultivars (Berry Blossom, Red Bordeaux, and Tahoe Cinco) in Northern Nevada. N increased plant height, canopy cover, stem diameter and shoot biomass, but other physiological parameters were dependent on cultivar. For instance, inflorescence biomass and inflorescence-to-shoot ratio in Red Bordeaux was not affected by N fertilization. Similarly, cannabinoid concentrations were affected by timing of harvest and cultivar but not by N treatment. We evaluated the use of a SPAD meter for ease of determining leaf N deficiency, and correlations with leaf chlorophyll content showed that the SPAD meter was a reliable tool in two cultivars but not in Tahoe Cinco. N treatment increased overall CBD yield, which was driven by increases in inflorescence biomass. Tahoe Cinco was the best CBD yielding cultivar, as it maintained a high inflorescence-to-shoot ratio regardless of N treatment. Our study suggests that even though hemp may have a positive response to soil N management, adjustments based on genotype by environment interaction should be aimed at maximizing cannabinoid yield either by increasing biomass and/or CBD concentrations as long as THC levels are within the permissible <0.3% for U.S. industrial hemp cultivation
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Modeling vegetative vigour in grapevine: unraveling underlying mechanisms
Mechanistic modeling constitutes a powerful tool to unravel complex biological phenomena. This study describes the construction of a mechanistic, dynamic model for grapevine plant growth and canopy biomass (vigor). To parametrize and validate the model, the progeny from a cross of Ramsey (Vitis champinii) × Riparia Gloire (V. riparia) was evaluated. Plants with different vigor were grown in a greenhouse during the summer of 2014 and 2015. One set of plants was grafted with Cabernet Sauvignon. Shoot growth rate (b), leaf area (LA), dry biomass, whole plant and root specific hydraulic conductance (kH and Lpr), stomatal conductance (gs), and water potential (Ψ) were measured. Partitioning indices and specific leaf area (SLA) were calculated. The model includes an empirical fit of a purported seasonal pattern of bioactive GAs based on published seasonal evolutionary levels and reference values. The model provided a good fit of the experimental data, with R = 0.85. Simulation of single trait variations defined the individual effect of each variable on vigor determination. The model predicts, with acceptable accuracy, the vigor of a young plant through the measurement of Lpr and SLA. The model also permits further understanding of the functional traits that govern vigor, and, ultimately, could be considered useful for growers, breeders and those studying climate change
Use of introgression lines to determine the ecophysiological basis for changes in water use efficiency and yield in California processing tomatoes
Assessing the sensitivity and repeatability of permanganate oxidizable carbon as a soil health metric: An interlab comparison across soils
Soil organic matter is central to the soil health framework. Therefore, reliable indicators of changes in soil organic matter are essential to inform land management decisions. Permanganate oxidizable carbon (POXC), an emerging soil health indicator, has shown promise for being sensitive to soil management. However, strict standardization is required for widespread implementation in research and commercial contexts. Here, we used 36 soils—three from each of the 12 USDA soil orders—to determine the effects of sieve size and soil mass of analysis on POXC results. Using replicated measurements across 12 labs in the US and the EU (n = 7951 samples), we quantified the relative importance of 1) variation between labs, 2) variation within labs, 3) effect soil mass, and 4) effect of soil sieve size on the repeatability of POXC. We found a wide range of overall variability in POXC values across labs (0.03 to 171.8%; mean = 13.4%), and much of this variability was attributable to within-lab variation (median = 6.5%) independently of soil mass or sieve size. Greater soil mass (2.5 g) decreased absolute POXC values by a mean of 177 mg kg−1 soil and decreased analytical variability by 6.5%. For soils with organic carbon (SOC) >10%, greater soil mass (2.5 g) resulted in more frequent POXC values above the limit of detection whereas the lower soil mass (0.75 g) resulted in POXC values below the limit of detection for SOC contents −1 while decreasing the analytical variability by 1.8%. In general, soils with greater SOC contents had lower analytical variability. These results point to potential standardizations of the POXC protocol that can decrease the variability of the metric. We recommend that the POXC protocol be standardized to use 2.5 g for soils <10% SOC. Sieve size was a relatively small contributor to analytical variability and therefore we recommend that this decision be tailored to the study purpose. Tradeoffs associated with these standardizations can be mitigated, ultimately providing guidance on how to standardize POXC for routine analysis.</p