scholarly journals Brace root phenotypes predict root lodging susceptibility and the contribution to anchorage in maize

2021 ◽  
Author(s):  
Ashley N Hostetler ◽  
Lindsay Erndwein ◽  
Jonathan W Reneau ◽  
William Cantera ◽  
Adam Stager ◽  
...  
Keyword(s):  
Plant Height ◽  
Prediction Accuracy ◽  
Crop Production ◽  
Global Climate ◽  
Root Traits ◽  
The United States ◽  
Lodging Resistance ◽  
Node Number ◽  
Plant Biomechanics ◽  
Root Lodging

A changing global climate brings increasingly prevalent and severe storms that threaten crop production by imparting mechanical stresses. Plant failure due to mechanical stress is termed lodging and in the United States, yield loss due to lodging has been estimated at 7-25% for maize (Zea mays). In maize, the presence of specialized aerial brace roots has been shown to increase anchorage and root lodging resistance. However, beyond scoring for presence, there have been limited attempts to define the brace root phenotypes that optimize anchorage. This study reports variable root lodging and plant biomechanics in a population of 52 maize inbred lines. To quantify the variation in brace root phenotypes within this population, a semi-automated phenotyping workflow was developed. These empirical measurements were integrated into predictive random forest models to demonstrate that brace root phenotypes can classify root lodging incidence and plant biomechanics. The prediction accuracy of these models is driven by multiple brace root phenotypes suggesting that anchorage can be optimized by the manipulation of multiple functional traits. Plant height has been previously associated with lodging susceptibility yet the inclusion of plant height as a predictor does not always improve prediction accuracy. Previously, brace root node number has been shown to be genetically linked to plant height and here we show that additional brace root phenotypes are linked to plant height but with opposing effects on root lodging susceptibility. Together these data define the important brace root phenotypes that predict root lodging resistance and demonstrate the need to uncouple the linkage between plant height and root traits for the development of climate resilient crops.

scholarly journals Maize brace roots provide stalk anchorage

2020 ◽  
Author(s):  
Jonathan W. Reneau ◽  
Rajdeep S. Khangura ◽  
Adam Stager ◽  
Lindsay Erndwein ◽  
Teclemariam Weldekidan ◽  
...  
Keyword(s):  
Flowering Time ◽  
Grain Quality ◽  
Plant Traits ◽  
Mechanical Failure ◽  
Rigid Base ◽  
Crop Loss ◽  
Lodging Resistance ◽  
Plant Biomechanics ◽  
Root Lodging ◽  
Time Selection

AbstractMechanical failure, known as lodging, negatively impacts yield and grain quality in crops. Limiting crop loss from lodging requires an understanding of the plant traits that contribute to lodging-resistance. In maize, specialized aerial brace roots are reported to reduce root lodging. However, their direct contribution to plant biomechanics has not been measured. In this manuscript, we find that brace roots establish a rigid base (i.e. stalk anchorage) to limit plant deflection in maize. The more brace root whorls that contact the soil, the greater the contribution of brace roots to anchorage. Previous studies have linked the number of brace root whorls to flowering time in maize. To determine if flowering time selection alters the brace root contribution to anchorage, a subset of the Hallauer’s Tusón tropical population was analyzed. Despite a significant change in flowering time, selection neither altered the number of brace root whorls in the soil nor the overall contribution of brace roots to anchorage. These results demonstrate that brace roots provide a rigid base in maize, but the contribution to anchorage is not linearly related to flowering time.

scholarly journals Silicon Effects on the Root System of Diverse Crop Species Using Root Phenotyping Technology

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 885
Author(s):  
Pooja Tripathi ◽  
Sangita Subedi ◽  
Abdul Latif Khan ◽  
Yong-Suk Chung ◽  
Yoonha Kim
Keyword(s):  
Root System ◽  
Root Morphology ◽  
Morphological Traits ◽  
Crop Production ◽  
Spatial Configuration ◽  
Global Climate ◽  
Learning Technologies ◽  
Climate Change Scenarios ◽  
Crop Species ◽  
Wide Range

Roots play an essential function in the plant life cycle, as they utilize water and essential nutrients to promote growth and plant productivity. In particular, root morphology characteristics (such as length, diameter, hairs, and lateral growth) and the architecture of the root system (spatial configuration in soil, shape, and structure) are the key elements that ensure growth and a fine-tuned response to stressful conditions. Silicon (Si) is a ubiquitous element in soil, and it can affect a wide range of physiological processes occurring in the rhizosphere of various crop species. Studies have shown that Si significantly and positively enhances root morphological traits, including root length in rice, soybean, barley, sorghum, mustard, alfalfa, ginseng, and wheat. The analysis of these morphological traits using conventional methods is particularly challenging. Currently, image analysis methods based on advanced machine learning technologies allowed researchers to screen numerous samples at the same time considering multiple features, and to investigate root functions after the application of Si. These methods include root scanning, endoscopy, two-dimensional, and three-dimensional imaging, which can measure Si uptake, translocation and root morphological traits. Small variations in root morphology and architecture can reveal different positive impacts of Si on the root system of crops, with or without exposure to stressful environmental conditions. This review comprehensively illustrates the influences of Si on root morphology and root architecture in various crop species. Furthermore, it includes recommendations in regard to advanced methods and strategies to be employed to maintain sustainable plant growth rates and crop production in the currently predicted global climate change scenarios.

Improving Soybean Production Using Light Supplementation at Field-Scale: A Case Study

2021 ◽  
Vol 9 (3) ◽  
pp. 259
Author(s):  
Ernane M Lemes ◽  
Breno N R Azevedo ◽  
Matheus F I Domiciano ◽  
Samuel L Andrade
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Crop Production ◽  
High Efficiency ◽  
Field Scale ◽  
Soybean Crop ◽  
Illumination System ◽  
Progress Curve ◽  
Commercial Area ◽  
Yield Responses

In modern agriculture, there is a growing need for increasing crop efficiency while minimizing environmental impacts. The use of high-efficiency light supplementation to enhance plant development is limited for high-productive crops at field conditions (outdoor). This study evaluated the soybean plant’s yield responses in an open commercial area (field scale) cultivated under conditions of artificial light supplementation. A commercial irrigated (pivot) area received an illumination system for light supplementation (LS) in its inner pivot spans. About 40 hours of LS were applied to the plants during the soybean crop cycle. The area’s outer pivot spans did not receive light supplementation (nLS). The internode number, the plant height, the pods per plant were evaluated weekly to compute the area under the progress curve (AUPC). The grain yield at harvest was also assessed. The AUPC of the internode number, plant height and pods per plant were positively affected by the LS treatment. The regular soybean cycle (nLS) is about 17 weeks; however, the LS harvest occurred three weeks later. Light supplementation increased soybean grain yield by 57.3% and profitability by 180% when compared to nLS. Although light supplementation at field scale poses a challenge, it is now affordable since sustainable field resistant technologies are now available. The present study is the first known report of light supplementation used to improve soybean crop production at field scale.

scholarly journals Growing climatic sensitivity of U.S. agriculture linked to technological change and regional specialization

2018 ◽  
Vol 4 (12) ◽  
pp. eaat4343 ◽  
Author(s):  
Ariel Ortiz-Bobea ◽  
Erwin Knippenberg ◽  
Robert G. Chambers
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Agricultural Sector ◽  
State Level ◽  
The United States ◽  
Climate Data ◽  
Specialty Crops ◽  
Regional Specialization ◽  
Vulnerability To Climate Change ◽  
Climatic Sensitivity

A pressing question for climate change adaptation is whether ongoing transformations of the agricultural sector affect its ability to cope with climatic variations. We examine this question in the United States, where major increases in productivity have fueled most of agricultural production growth over the past half-century. To quantify the evolving climate sensitivity of the sector and identify its sources, we combine state-level measures of agricultural productivity with detailed climate data for 1960–2004. We find that agriculture is growing more sensitive to climate in Midwestern states for two distinct but compounding reasons: a rising climatic sensitivity of nonirrigated cereal and oilseed crops and a growing specialization in crop production. In contrast, other regions specialize in less climate-sensitive production such as irrigated specialty crops or livestock. Results suggest that reducing vulnerability to climate change should consider the role of policies in inducing regional specialization.

scholarly journals A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

scholarly journals An Optimal Redesign Approach for Optimal Global Supply Chain Redesign: Brazilian Soybean Grain Study

2017 ◽  
Vol 5 (2) ◽  
pp. 84
Author(s):  
Juan José Uchuya Lopéz ◽  
Raad Yahya Qassim
Keyword(s):  
United States ◽  
Supply Chain ◽  
Competitive Advantage ◽  
Crop Production ◽  
The United States ◽  
Global Supply Chains ◽  
Rail Transportation ◽  
Road Transportation ◽  
Mato Grosso ◽  
Inland Waterways

Brazil and the United States are the leading soybean grain producing and exporting countries in the world. Although crop production cost is significantly lower in Brazil than in the United States due to more advanced crop production technology, this competitive advantage vanishes in view of the higher logistics costs in Brazil than in the United States, in view of the dominance of road transportation in Brazil, whilst river and rail transportation are prevalent in the United States. In order to regain its competitive advantage, there is a clear need for a redesign of the inland supply chain in Brazil through the use and expansion of existent inland waterways and rail networks. In this paper, an optimal supply chain redesign methodology is presented to achieve the aforesaid objective, with a focus on Mato Grosso which is the largest producer and exporting state in Brazil. This methodology is in fact applicable to multiply echelon global supply chains in general.

scholarly journals The Effect of Abiotic Stresses on the Protein Composition of Four Hungarian Wheat Varieties

Plants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Dalma Nagy-Réder ◽  
Zsófia Birinyi ◽  
Marianna Rakszegi ◽  
Ferenc Békés ◽  
Gyöngyvér Gell
Keyword(s):  
Abiotic Stress ◽  
Protein Content ◽  
Functional Properties ◽  
Crop Production ◽  
Global Climate ◽  
Protein Composition ◽  
Grain Protein Content ◽  
Wheat Varieties ◽  
Significant Difference ◽  
Negative Effect

Global climate change in recent years has resulted in extreme heat and drought events that significantly influence crop production and endanger food security. Such abiotic stress during the growing season has a negative effect on yield as well as on the functional properties of wheat grain protein content and composition. This reduces the value of grain, as these factors significantly reduce end-use quality. In this study, four Hungarian bread wheat cultivars (Triticum aestivum ssp. aestivum) with different drought and heat tolerance were examined. Changes in the size- and hydrophobicity-based distribution of the total proteins of the samples have been monitored by SE- and RP-HPLC, respectively, together with parallel investigations of changes in the amounts of the R5 and G12 antibodies related to celiac disease immunoreactive peptides. Significant difference in yield, protein content and composition have been observed in each cultivar, altering the amounts of CD-related gliadin, as well as the protein parameters directly related to techno-functional properties (Glu/Gli ratio, UPP%). The extent of changes largely depended on the timing of the abiotic stress. The severity of the negative effect depended on the growth stage in which abiotic stress occurred.

scholarly journals Climate change will increase potential hydropower production in six Arctic Council member countries based on probabilistic hydrological projections

2018 ◽  
Author(s):  
Elena Shevnina ◽  
Karoliina Pilli-Sihvola ◽  
Riina Haavisto ◽  
Timo Vihma ◽  
Andrey Silaev
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
The United States ◽  
Annual Runoff ◽  
Global Climate Models ◽  
Exceedance Probability ◽  
Arctic Council ◽  
Pearson Type ◽  
Hydropower Production ◽  
Runoff Rate

Abstract. Potential hydropower production for 2020–2050 is calculated for 173 catchments located over the territories of Finland, Sweden, Norway, the Russian Federation, Canada and the United States. The results are based on hydrological river runoff projections assessed together with their exceedance probabilities. The annual runoff rate of particular exceedance probability was modelled with the Pearson type 3 distribution from three parameters (mean values, coefficient of variation and coefficient of skewness) simulated by the probabilistic hydrological MARcov Chain System (MARCS) model. The probabilistic projections of annual runoff were simulated from outputs of four global climate models under three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). The future potential hydropower production was evaluated based on annual runoff of low and high exceedance probabilities, and then aggregated at a country level. Under forcing from climate models that project a large increase in precipitation (CaEMS2 and MPI-EMS-LM), the expected potential hydropower production in the six countries increased by 14.0 to 18.0 % according to the projected values of annual runoff rate on exceedance probabilities of 10 and 90 %. This increase in water resources allows for 10–15 % more hydropower energy generation by rivers located in Russia, Finland, Norway, and Sweden. For the USA and Canada, the potential hydropower production is projected to increases by 4.0–9.0 %. Under forcing from climate models that project a smaller increase in precipitation (HadGEM2-ES and INMCM4), the increase of potential hydropower production by 2050 was predicted to be 2.1–8.4 % over the six countries considered.

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