Soil pH and Lime Management for Corn and Soybean

Pagani, Agustín

doi:10.31274/etd-180810-2005

Cited by 7 publications

(8 citation statements)

References 77 publications

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“…The major grain yield response to lime application, determined in soybean than wheat crop, would be consequence to growth responses in leguminous attributed to favorable soil pH for rhizobium activity (Mengel and Kamprat, 1978;Brauer et al, 2002;Ouertatania et al, 2011). Optimum soil range pH for soybean and wheat is around 5.5-7.5 for both crops (Fageria and Zimmermann, 1998;Bongiovanni and Lowenberg-DeBoer, 2000;Sawyer et al, 2002;Pagani, 2011). However, no significant relationship was determined between RY and soil pH in both crops, in spite of pH values in no lime treatment was from 5.5 to 5.9 ( Fig.…”

Section: Grain Yieldmentioning

confidence: 99%

Soybean and wheat response to lime in no-till Argentinean mollisols

Barbieri¹,

Echeverría²,

Rozas³

et al. 2015

Soil and Tillage Research

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Crop production in Argentina has significantly increased over the past few years; this increase was consequence of better management practices which included P and N fertilization and, occasionally, S fertilization. Commonly used rates, however, are not sufficient to balance nutrients export in grain crops. This situation is particularly negative for meso-nutrients (Ca +2 and Mg +2) because they are not normally applied by farmers. The objective of this study was to determine the effect of lime over four years period on soybean, one year period on wheat and on a one year double cropped wheat/soybean combination on no-till. The experimental design was a randomized complete blocks design with three replications and two combinations of lime (with and without). Results showed that lime application significantly increased soil pH, exchangeable Ca +2 content, and therefore, base saturation and Ca +2 saturation in cation exchangeable capacity (CEC). As average growing seasons, the relative increments due to lime application were 8, 22, 18, and 20% for pH, soil exchangeable Ca +2 content, base saturation and Ca +2 saturation in CEC, respectively. Results showed that soil bulk density and penetration resistance were not affected by lime application. Soil structure stability was significantly affected by lime application. Wheat grain yield was not affected by lime, but soybean grain yield was significantly increased by lime (7% average across year). Cumulative grain yield was significantly increased by lime application indicating that the benefits of liming were cumulative over time (27,556 vs 28,629 kg ha À1 for lime and no lime, respectively). Increments in relative grain yield were not associated with soil pH in both crops; however, significant relationships were determined between relative soybean grain yield and soil Ca +2 content, base saturation and Ca +2 content in CEC. A soil Ca +2 critical concentration of 12.4 meq 100 g À1 was determined to obtain 95% of relative soybean grain yield. The study concluded that soil Ca +2 content would limit soybean grain yield as a consequence of cation unbalance in intensive agriculture soil. 2015 Elsevier B.V. All rights reserved.

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Section: Grain Yieldmentioning

confidence: 99%

Soybean and wheat response to lime in no-till Argentinean mollisols

Barbieri¹,

Echeverría²,

Rozas³

et al. 2015

Soil and Tillage Research

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“…found that pH of the soil surface is often more acidic than lower in the soil profile where sampling occurs. In an Iowa soil survey, Pagani et al . determined soil pH ranged from 4.6 to 8.0.…”

Section: Introductionmentioning

confidence: 99%

Identification of environmental factors that influence the likelihood of off‐target movement of dicamba

Oseland

Bish

Steckel

et al. 2020

Pest Management Science

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BACKGROUNDCommercialization of dicamba‐resistant soybean and cotton and subsequent post‐emergence applications of dicamba contributed to at least 1.4 and 0.5 million hectares of dicamba‐injured soybean in the United States in 2017 and 2018, respectively. This research was initiated to identify environmental factors that contribute to off‐target dicamba movement. A survey was conducted following the 2017 growing season to collect information from dicamba applications that remained on the target field and those where dicamba moved. Weather and environmental data surrounding applications were collected and used to identify factors that reduce the likelihood of off‐target movement. Soil pH was one factor identified in the model, and field experiments were conducted in 2018 and 2019 to validate the model. Three commercially‐available dicamba formulations and one formulation currently in development were applied to soil at five distinct pH values. Sensitive soybean was used as a bioassay plant to detect dicamba volatilization.RESULTSWind speeds the day of and following application, nearest water source to the field, soybean production acreage in the county, and soil pH were identified as factors that influence the likelihood for off‐target movement. In the field study, when dicamba was applied to pH‐adjusted soil and placed under low tunnels for 72 h, dicamba volatility increased when soil pH decreased as the model predicted. Dicamba choline, which is not commercially available, had reduced volatility compared to other formulations tested.CONCLUSIONResults of this study identified specific factors that contribute to successful and unsuccessful dicamba applications and should be considered prior to applications. © 2020 Society of Chemical Industry

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“…For W ± H production it is the largest source of uncertainty [6]. The photon distribution is also potentially relevant for the production of lepton-pairs [7][8][9][10][11], top-quarks [12], pairs of weak bosons [13][14][15][16][17][18] and generally enters into electroweak corrections for almost any LHC process. The diphoton excess around 750 GeV seen by ATLAS and CMS [19,20] has also generated interest in understanding f γ/p .…”

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confidence: 99%

How Bright is the Proton? A Precise Determination of the Photon Parton Distribution Function

et al. 2016

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It has become apparent in recent years that it is important, notably for a range of physics studies at the Large Hadron Collider, to have accurate knowledge on the distribution of photons in the proton. We show how the photon parton distribution function (PDF) can be determined in a model-independent manner, using electron-proton (ep) scattering data, in effect viewing the ep→e+X process as an electron scattering off the photon field of the proton. To this end, we consider an imaginary, beyond the Standard Model process with a flavor changing photon-lepton vertex. We write its cross section in two ways: one in terms of proton structure functions, the other in terms of a photon distribution. Requiring their equivalence yields the photon distribution as an integral over proton structure functions. As a result of the good precision of ep data, we constrain the photon PDF at the level of 1%-2% over a wide range of momentum fractions.

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Soil pH and Lime Management for Corn and Soybean

Cited by 7 publications

References 77 publications

Soybean and wheat response to lime in no-till Argentinean mollisols

Soybean and wheat response to lime in no-till Argentinean mollisols

Identification of environmental factors that influence the likelihood of off‐target movement of dicamba

How Bright is the Proton? A Precise Determination of the Photon Parton Distribution Function

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