Nitrogen Source, Timing, and Rate Alternatives for Furrow-irrigated Sugarbeet

Norton, Jay B.

doi:10.1094/cm-2011-0829-01-rs

Cited by 10 publications

(8 citation statements)

References 17 publications

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“…They also found that optimum yield from soil with a low available N content was obtained with the application of 160 kg N•ha −1 . Norton [53] recorded that application of diverse rates of nitrogen (26,134, and 220 lbs•acre −1 ) resulted in non-significant differences in the sugar content (%) and sugar yield in the USA on Garland series soils (fine loamy over sandy or sandy-skeletal, mixed, super active, mesic Typic Haplargids). Barik [54] worked in Calicutta (India) on medium organic carbon soils and reported that applying nitrogen fertilizer at the rate of 150 kg N•ha −1 resulted in the greatest root yield and sugar yield per hectare, while the highest values of sugar concentration were recorded when 120 kg N•ha −1 was applied.…”

Section: Sugar Beet Root Yield and Sugar Content Under The Influence mentioning

confidence: 99%

Impact of Irrigation and Fertigation on the Yield and Quality of Sugar Beet (Beta vulgaris L.) in a Moderate Climate

Żarski

Kuśmierek‐Tomaszewska

Dudek

2020

Agronomy

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In Poland, under conditions of the moderate climate and transition between maritime and continental climates, the average rainfall totals of the growing season are in the range of 350–400 mm; however, they are distinguished by great temporal and spatial variability. Climatological studies demonstrate that the drought frequency is approximately 30%. Therefore, under such conditions, irrigation has a supplementary and intervention nature and is applied only when dry periods occur. The aim of this study was to determine the impact of sprinkler irrigation and increased nitrogen fertilization on the yield and quality of sugar beet roots and yield of sugar. The average increase of the yield under irrigation was 18.1 t·ha−1 which constituted a 22.8% increase in the yield. Furthermore, there was a marked tendency of a higher sugar content in the roots of irrigated plants. The absolute, relative, and unit average sugar beet root yield increases obtained under the influence of sprinkler irrigation and the lack of a significant diversity in the sugar content in roots confirm that irrigation contributed to an appropriate pace of plant growth and development. The increased rate of nitrogen fertilization (N2) of 160 kg N·ha−1 plus an additional 40 kg N·ha−1 resulted in the significantly greater root yields compared to the control (N1) (160 kg N·ha−1), i.e., an average of 7.6 t·ha−1 (9%). Based on the crop-water production function, the maximum root yields were obtained for the N1 rate at a total precipitation and irrigation amount of 382 mm, compared with 367 mm for the N2 rate.

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Section: Sugar Beet Root Yield and Sugar Content Under The Influence mentioning

confidence: 99%

Impact of Irrigation and Fertigation on the Yield and Quality of Sugar Beet (Beta vulgaris L.) in a Moderate Climate

Żarski

Kuśmierek‐Tomaszewska

Dudek

2020

Agronomy

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“…The literature on Nutrisphere‐N is mixed as to its value as a fertilizer additive. Some studies have reported crop yield increases (Gordon, 2014; Heiniger et al, 2014; Maharjan et al, 2017; Wiatrak, 2014; Wiatrak and Gordon, 2014), while others have shown little effect on crop production or N transformations (Cahill et al, 2010; Chien et al, 2014; Connell et al, 2011; Edmeades and McBride, 2012; Forrestal et al, 2016; Franzen et al, 2011; Harty et al, 2017; Henning et al, 2013; Norton, 2011). Peng et al (2015) measured a reduction in nitrate leaching from soil columns when UAN was treated with Nutrisphere‐N.…”

Section: Nitrification Inhibitors and Granular Ureamentioning

confidence: 99%

Evaluation of Commercial Additives Used with Granular Urea for Nitrogen Conservation

Goos

Guertal

2019

Agronomy Journal

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Core Ideas Urease and nitrification inhibitors can reduce N loss from granular urea. Agrotain Ultra functioned as a urease inhibitor, Nutrisphere‐N, and NZone did not. Agrotain Ultra reduced ammonia volatilization, Nutrisphere‐N, and NZone had little effect. SuperU and Instinct inhibited nitrification, Nutrisphere‐N, and NZone did not. ABSTRACT Urea is subject to loss by ammonia volatilization, and, after nitrification, by leaching and denitrification. This study evaluated commercial products marketed as fertilizer additives for granular urea for the purpose of reducing N loss. In a urea hydrolysis study, urea granules were applied to three soils, and hydrolysis measured for 10 d. The urea granules were untreated, or treated with Nutrisphere‐N (Verdesian Life Sciences, Cary, NC), NZone (AgXplore, Parma, MO), or Agrotain Ultra (Koch Agronomic Services, Wichita, KS). Agrotain Ultra was effective in slowing urea hydrolysis, but amending the granules with Nutrisphere‐N and NZone did not slow urea hydrolysis. In a ammonia volatilization study, the treatments were the same, two soils were used, and volatilization was measured over 14 d. Agrotain Ultra was effective in reducing ammonia loss compared to untreated urea granules, but amending the granules with Nutrisphere‐N and NZone had little effect. In a nitrification study, three soils were treated with urea granules, SuperU granules (Koch Agronomic Services, Wichita, KS), or urea granules treated with Nutrisphere‐N, NZone, or Instinct (Dow Agrosciences, Indianapolis, IN). The progress of nitrification was measured after 2 and 4 wk of incubation. SuperU granules, or granules treated with Instinct nitrified more slowly than untreated urea granules, amending urea granules with Nutrisphere‐N and NZone did not slow nitrification. The three experiments do not support the use of Nutrisphere‐N or NZone as fertilizer additives for granular urea, for the purpose of reducing N loss.

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“…The yield of sugar and fodder beet depends, among others, on assimilation surface including the number of leaves (Norton, ; Stevanato et al, ). The number of leaves in this data set comes from the two‐factor experiment (seeding data and nitrogen fertilization) carried out in the Experimental Station of the Faculty of Agriculture and Biology, Warsaw University of Life Science, Poland.…”

Section: Methodsmentioning

confidence: 99%

Over‐dispersed count data in crop and agronomy research

Kosma

Studnicki

Wójcik-Seliga

et al. 2019

J Agronomy Crop Science

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While evaluating plant response to biotic or abiotic stress and genotype–environment interactions and searching causes of yield gap, very often are observed data with non‐normal distributions. One of the commonly encountered types of variables with a non‐normal distribution is count data. Count data are defined as the type of observations which have a positive, non‐zero, integer value. The selection of appropriate probability distributions and model types is very important due to the risk of estimating the variance incorrectly—the phenomenon of over‐dispersion. Increasingly, biologists and agronomists have been using methods based on generalized linear models. However, sometimes, when including count data, they are not aware of or disregard their over‐dispersion. One of the solutions for over‐dispersed count data is to use probability distributions and model types which assume a more flexible mean and variance relationship. Thus, the aim of this study is to present various ways of assessing over‐dispersion. Additionally, we present alternative distributions and discuss other approaches to solve the problem of over‐dispersion in count data sets. As examples in this study are used real data sets from different agricultural experiments. In our study, in one out of the two data sets used, this phenomenon occurred. Thus, in the analysis of count data, instead of using default distribution (usually Poisson distribution), other distributions should be considered because of the possible occurrence of over‐dispersion. We also observed that there is not one universal distribution to use and each data set might need a separate assessment to choose its distribution. For an efficient and proper count data analysis, with potential over‐dispersion, it is important to explore several options, i.e. evaluate models with an alternative to Poisson probability distributions and then make an informed choice.

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Nitrogen Source, Timing, and Rate Alternatives for Furrow-irrigated Sugarbeet

Cited by 10 publications

References 17 publications

Impact of Irrigation and Fertigation on the Yield and Quality of Sugar Beet (Beta vulgaris L.) in a Moderate Climate

Impact of Irrigation and Fertigation on the Yield and Quality of Sugar Beet (Beta vulgaris L.) in a Moderate Climate

Evaluation of Commercial Additives Used with Granular Urea for Nitrogen Conservation

Over‐dispersed count data in crop and agronomy research

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