Effects of spatial variability of nitrogen supply on environmentally acceptable nitrogen application rates to arable crops.

Noordwijk, Meine van; Wadman, W.P.

doi:10.18174/njas.v40i1.16529

Cited by 21 publications

(12 citation statements)

References 14 publications

(11 reference statements)

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“…Nutrient acquisition by the crop from the soil is significantly related to the size of the root system ( Van Noordwijk and Wadman , ; Dai et al, ). In classical recommendation systems, a single sample of the topsoil (0–0.3 m) representing approximately 4 ha is investigated for immobile nutrients such as P and K ( Stępień et al, ).…”

Section: Introductionmentioning

confidence: 99%

Predicting the content of soil mineral nitrogen based on the content of calcium chloride‐extractable nutrients

Barłóg

Łukowiak

Grzebisz

2017

J. Plant Nutr. Soil Sci.

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Sustainable management of nitrogen (N) in crop production requires a multifactorial assessment of the soil inorganic nitrogen pool (Nmin). It is assumed that the reliable prediction of the total Nmin content requires data on the content of mineral N forms (NO3‐N, NH4‐N), the contents of other extractable macronutrients and the soil pH. This hypothesis was tested during three growing seasons on a production farm in Górzno, Poland. The contents of 0.01 M CaCl2‐extractable NO3‐N, NH4‐N, P, K, and Mg and the pH were measured in soil layers of 0–0.3, 0.3–0.6, and 0.6–0.9 m just prior to the start of spring vegetation of a given crop and immediately after its harvest (autumn). This study was conducted in 17 fields differing in cropping sequence (CS): 10 with oilseed rape (Brassica napus L.) (OSR‐CS) and seven with maize (Zea mays L.) (SM‐CS) as the dominant crops. Principal factor analysis (PFA) was applied to explore and interpret patterns in data sets defined by the changeability in the content of Nmin in association with variability in contents of other CaCl2‐extractable nutrients. In spring, the first principal factor (PF1) for OSR‐CS was associated with phosphorus (P), whereas PF2 and PF3 were loaded by NO3‐N and NH4‐N, respectively. For SM‐CS, PF1 was loaded by both inorganic N forms, whereas PF2 and PF3 were loaded by potassium (K), magnesium (Mg), and P. In autumn, the dominance of P as the key variable associated with the PFs was stronger in both CSs compared with those in the spring. The prediction of Nmin, in spite of the moderate strength of the PFs (“r” coefficients), can be conducted based on the inorganic N content. In spring, the reliable prediction of Nmin for the OSR‐CS requires data on both N forms. In the SM‐CS, the content of NO3‐N can be used as the sole Nmin predictor. In autumn, the variability in Nmin content can be explained based solely on the NH4‐N content. This was also the main factor affecting the variability in other soil fertility characteristics, such as the contents of K and Mg and the soil pH.

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Section: Introductionmentioning

confidence: 99%

Predicting the content of soil mineral nitrogen based on the content of calcium chloride‐extractable nutrients

Barłóg

Łukowiak

Grzebisz

2017

J. Plant Nutr. Soil Sci.

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“…, sandy soil with split nitrogen application). (Herkelrath et al 1977;, (c) locally decreased soil water contents around water-absorbing roots (Herkelrath et al 1977 ;Hainsworth & Aylmore 1986;Kage & Ehlers 1996), (d) horizontally uneven distribution of soil nitrate (Van Noordwijk & Wadman 1992;Hodge et al 1999). The incorporation of these effects into the model may reduce the contradiction between the functional time of roots in the model and physiologically realistic values, but would also increase the number of unknown and hardly measurable model parameters.…”

Section: Discussionmentioning

confidence: 99%

Aspects of nitrogen use efficiency of cauliflower I. A simulation modelling based analysis of nitrogen availability under field conditions

2003

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Data from several field experiments (eight crops grown under a widely varying nitrogen supply on a loess loam soil) were used for a simulation modelling based analysis of nitrogen availability of cauliflower. The model was built out of components describing root growth, nitrate transport to the roots and the vertical nitrate transport within the soil.Root observations obtained over 2 years indicated an increased fraction of dry matter allocated to the fine roots under N deficiency. An adopted version of a root growth model for cauliflower described the rooting data with an R2=0·75. Based upon an acceptable description of the soil water budget, vertical nitrate movement during the growth period of cauliflower was accurately described. The magnitude of this movement, however, was limited to soil depths of about 60 cm even after periods of high rainfall, because of a high soil water holding capacity. An analysis of the factors determining nitrate availability indicated that apparent mass flow was only of high importance for conditions of extremely high N supply where high amounts of nitrate nitrogen remain in the soil up to the end of the growing season. Otherwise, the dominating fraction of nitrate has to be transported to the roots by diffusion. Single root model based calculations of maximum nitrate transport to roots overestimated N availability as indicated by estimates of critical soil nitrate N that were too low. The introduction of a restricted uptake activity period of the roots was used to bridge the gap between theoretical calculations and empirical results. Scenario calculations were carried out to obtain functional relationships between N supply and residual soil nitrate levels for different soil conditions and management practices.

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“…Spatial variability and diversity has often been seen as a problem, in that it does not allow simplistic perspective on scaling up to perform. As 'homogeneity' has often been used as a siteselection criterion for field experiments, as it increases the chance of "statistically significant" treatment effects to be seen with practically feasible levels of replication, scientists reviewing experimental evidence have a biased view of the world (van Noordwijk and Wadman, 1992). Technologies that were carefully packaged by scientists are generally unpacked by farmerswho will adopt the parts they like, and find new ways around the parts they don't (Sanchez et al, 2001;Sanchez, 2002;Ajayi et al, 2007;Place et al, 2002).…”

Section: The Challenge Of Demonstrating Development Impact Through Somentioning

confidence: 99%

The rooted pedon in a dynamic multifunctional landscape: Soil science at the World Agroforestry Centre

Noordwijk¹,

Barrios²,

Bayala³

et al. 2015

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Effects of spatial variability of nitrogen supply on environmentally acceptable nitrogen application rates to arable crops.

Cited by 21 publications

References 14 publications

Predicting the content of soil mineral nitrogen based on the content of calcium chloride‐extractable nutrients

Predicting the content of soil mineral nitrogen based on the content of calcium chloride‐extractable nutrients

Aspects of nitrogen use efficiency of cauliflower I. A simulation modelling based analysis of nitrogen availability under field conditions

The rooted pedon in a dynamic multifunctional landscape: Soil science at the World Agroforestry Centre

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