Critical Nitrogen Dilution Curve Research Articles

Fruits-Based Critical Nitrogen Dilution Curve for Diagnosing Nitrogen Status in Cotton.

Estimating the precise nutritional status of crop nitrogen (N) after flowering period is not only important to predict deficiency but the excess that could be revised by fertilization in future crops. Critical N dilution curves describing the critical N concentration ([N]c) in plant tissues during crop growth have been used to estimate the N status of whole plants in cotton. Little is known, however, about the critical N dilution curve for specific plant organs such as cotton fruits. The objective of this study was to verify the feasibility of fruits-based critical N dilution curve as a useful diagnostic tool for diagnosing the N status of cotton crops. A 3-year field experiment was conducted with seven N application rates (0–360 kg N ha–1) using the high-yielding cultivars Jimian 228 and Lumian 28, which differ in maturity. The relationship between fruits dry mass (DM) and N concentration ([N]) was analyzed, and a model of [N]c for cotton fruits was constructed and validated. The results showed that fruits [N]c decreased with increasing fruits DM. The critical N dilution curve based on cotton fruits was described by the equation [N]c = 2.49 × DM–0.12 (R2 = 0.649, P < 0.0001) across cultivar-years. The N nutrition index (NNI) of the fruits (NNIf) with the N dilution curve was significantly related to the NNI of shoot DM, relative yield (RY), and boll density at most sampling dates. For an NNIf of approximately 1, the RY was nearly 95%, while it decreased with a decreasing NNIf below 1. The petiole nitrate-N (NO3-N) concentration was also linearly related to the NNIf, suggesting that the NO3-N concentration in the petiole was a good predictor of the NNIf. Therefore, fruits-based critical N dilution curve and the derived NNIf values will serve as a useful diagnostic tool for diagnosing N status in cotton crops.

Establishment of a critical nitrogen dilution curve for drip-irrigated cotton under reduced nitrogen application rates

The goal of this study was to establish the feasibility of using the critical nitrogen (N) dilution curve of cotton leaves for diagnosing N nutrition, so as to provide a theoretical basis and guidance for accurate fertilization in drip-irrigated cotton fields. We conducted field experiments using Lumianyan 24 under four different reduced N treatments including (506 kg hm−2 (N1), 402.5 kg hm−2 (N2), 299 kg hm−2 (N3), and 195.5 kg hm−2 (N4)) between 2018 and 2019. We subsequently measured N concentration and leaf dry matter (LDM). We also calculated the critical N concentration (Nc) dilution model, allometric growth model, N nutrient index (NNI), and N accumulation. Our results revealed that with the development of growth period, the leaf NNI and N accumulation displayed an increasing trend followed by a decreasing pattern in 2018. On the other hand, the leaf NNI in 2019 showed a similar performance as presented in 2018, while the N accumulation depicted a gradually increasing trend. We also found that NNI and N accumulation of cotton leaves reduced with decreasing N application. The Nc dilution curve model for drip-irrigated cotton fields was Nc = 5.163LDM−0.171 (LDM > 1.65), Nc = 4.7% (LDM ≤ 1.65), R2 = 0.933, with a highly significant fit and RMSE = 0.374, accompanied by excellent model simulation performance. In conclusion, this study established the Nc dilution curve model. Additionally, the calculated NNI can efficiently diagnose the status of N nutrients, thus providing a valuable theoretical basis for accurate fertilization of drip-irrigated cotton fields.

Leaf Area Index and Aboveground Biomass Based Critical Nitrogen Dilution Curves for Predicting Nitrogen Status of Greenhouse Cherry Tomato Using Bayesian Analysis

Leaf Area Index and Aboveground Biomass Based Critical Nitrogen Dilution Curves for Predicting Nitrogen Status of Greenhouse Cherry Tomato Using Bayesian Analysis

Key variable for simulating critical nitrogen dilution curve of wheat: Leaf area ratio-driven approach

Nitrogen (N) dilution curves, a pivotal tool for N nutrition diagnosis, have been developed using different winter wheat (Triticum aestivum L.) tissues. However, few studies have attempted to establish critical nitrogen (Nc) dilution curves based on the leaf area ratio (LAR) to improve the monitoring accuracy of N status. In this study, three field experiments using eight N treatments and four wheat varieties were conducted in Jiangsu Province of China from 2013 to 2016. The empirical relationship of LAR with shoot biomass (expressed as dry matter) was developed under different N conditions. The results showed that LAR was a reliable index, which reduced the effects of wheat varieties and years compared with the traditional indicators. The N nutrition index (NNI) based on the LAR approach (NNI-LAR) produced equivalent results to that based on shoot biomass. Moreover, the NNI-LAR better predicted accumulated N deficit and best estimated the relative yield compared with the other two indicator-based NNI models. Therefore, the LAR-based approach improved the prediction accuracy of Nc, accumulated N deficit, and relative yield, and it would be an optimal choice to conveniently diagnose the N status of winter wheat under field conditions.

Exploring the nitrogen source-sink ratio to quantify ear nitrogen accumulation in maize and wheat using critical nitrogen dilution curve

Ear nitrogen (N) accumulation plays an imperative role in ear photosynthesis and the formation of grain yield and quality of maize and wheat. However, the mechanism governing ear N accumulation (NAe) especially under different N levels is not yet clear. For this purpose, this study endeavored to describe the N source-sink ratio of NAe by developing a model using ear critical N concentration (%Nc) dilution curves of maize and wheat. The data obtained include ear dry matter (DMe), NAe, ear N nutrition index (NNIe), ear N accumulation rate index (NARIe), post-anthesis N uptake (PANU), grain number (GN), and thousand-grain weight (TGW) were collected from 12 varied N rates (0–300 kg N ha−1) field experiments conducted using four wheat and three maize cultivars. Integrated models were developed to show the effect of N source and sink on NAe in maize and wheat. The ratio between PANU and NAe was used to represent the post-anthesis supply capacity of N source, while DMe was used as the storage capacity of N sink in these models. Robust relationships of NARIe with the ratio between PANU and NAe in maize and wheat indicated that NAe was controlled by N source from N-limiting to non-N-limiting levels. The relationship between the rate of ear dry matter accumulation (DMRe) and NNIe showed a linear plateau model across different N levels due to the similar DMe under non-N-limiting levels, indicating that ear N status was regulated by DMe (N sink) under N-limiting levels. Therefore, NAe under N-limiting levels was co-regulated by N source and sink. Besides, the temporal effect of plant N status before anthesis on NAe was also observed. The close relationship between DMe and plant N status at anthesis across different N levels in maize and wheat indicated that the potential ear N sink was controlled by the pre-anthesis supply capacity of plant N source. Consequently, pre-anthesis plant N status was imperative for quantifying potential ear N sink. This was the first-ever attempt to investigate the N source-sink ratio of NAe using ear %Nc curve and highlighted the effect of pre-anthesis plant N status on NAe. The findings will contribute towards a better understanding of the process of NAe under different N levels for developing a judicious N management strategy for improving the N use efficiency of wheat and maize.

Development of critical nitrogen dilution curves for different leaf layers within the rice canopy

Understanding the effect of nitrogen (N) vertical distribution within the rice canopy at different growth stages and development of critical nitrogen dilution curves for upper leaf layers will not only help accurate estimations of the spatial and temporal variation in N status, but will also provide a basis for analyses of N nutrition in rice. Based on a three-year field experiment with 2 rice varieties, 3 N levels and 4 planting densities, the effect of heterogeneity in N vertical distribution on the nitrogen nutrition index (NNI) was then determined, and for the first time, critical N dilution curves of upper leaf layers were constructed based on a Bayesian statistical model. The relationship for NNI entire canopy and its relationship with the other tested leaf layers was investigated. The leaf layer suitable for analyses of N nutrition and directly inversion of NNI by remote sensing is determined. The results revealed that the main contributor to plant N concentration (PNC) of entire canopy (PNCCanopy) was found to be the lower leaf layer of the rice canopy, and may lead to misdiagnosis under the non-N-limiting condition by using the canopy level based NNI. The PNC of top half leaf layer of the canopy was more stable in terms of short-term environmental changes, and more accurately representing the overall N status. The top half leaf layer was the main contributor to canopy reflectance. Thus, compared with the NNI of other upper leaf layers, the NNI of the top half leaf layer is more suitable for direct inversion by using CI (1113, 743) with the R2 = 0.70. Overall, these findings suggest that the NNI of the top half leaf layer is the optimal remote sensing indicator of N nutrition in rice.

Simulation of the critical nitrogen dilution curve in Jiangxi double-cropped rice region based on leaf dry matter weight.

In order to investigate the feasibility of using rice critical nitrogen concentration as a nitrogen nutrition diagnosis index, a two-year positioning field gradient experiment using four rice varieties and four nitrogen levels (0, 75, 150, 225 kg·ha-1 for early rice; 0, 90, 180, 270 kg·ha-1 for late rice) was conducted for early and late rice. The critical dilution curves (Nc%) of the double-cropped rice based on leaf dry matter (LDM) were constructed and verified using the field data. Two critical nitrogen dilution curves and nitrogen nutrition indexes (NNI) of rice LDM were constructed for early rice [Nc% = 2.66LDM-0.79, R2 = 0.88, NNI ranged between 0.29-1.74, and the average normalized root mean square error (n-RMSE = 19.35%)] and late rice [Nc% = 7.46LDM-1.42, R2 = 0.91, NNI was between 0.55-1.53, and the average (n-RMSE = 15.14%)]. The relationship between NNI and relative yield was a quadratic polynomial equation and suggested that the optimum nitrogen application rate for early rice was sightly smaller than 150 kg·ha-1, and that for late rice was about 180 kg·ha-1. The developed critical nitrogen concentration dilution curves, based on leaf dry matter, were able to diagnose nitrogen nutrition in the double-cropped rice region.

Revisiting the critical nitrogen dilution curve for tall fescue: A quantitative synthesis

Assessing the plant nitrogen (N) status is one of the major challenges for improving N fertilization management and reducing its environmental footprint on forage-based agricultural systems. We re-analyzed a dataset of biomass (W) and plant N concentration (%N) of tall fescue (Festuca arundinacea Schreb.) using a Bayesian statistical model for estimating the coefficients of the critical N (%Nc) dilution curve (Nc = A1 W −A2) with two objectives in mind: i) to revise the reference %Nc dilution curve established for tall fescue by Lemaire and Salette (1984), and ii) to analyze how the determination of %Nc curves is affected by the structure of the dataset (number of sampling dates and N rates) along with the range of shoot %N and W achieved. Our analysis suggests that the original tall fescue %Nc curve of Lemaire and Salette (1984) was overestimated. A critical %N curve for tall fescue was obtained using the Bayesian method across 14 unique genotype × environment × management (G × E × M) conditions (Nc = 3.93 W -0.42). We show that the high uncertainty associated with the %Nc curve could be reduced by increasing the number of experiments. When a single dataset was used, 95 % credibility intervals (95 % CI) were [2.52, 5.66] for A1 and [0.06, 0.63] for A2. However, 95 % CI were reduced up to a 73 % when the critical N dilution curve was based on 14 studies. We also show that a minimum of five studies (+100 data points for our study) are needed to avoid large biases and uncertainty levels in coefficient estimations with the Bayesian method. However, these studies must be carefully designed. The reliability of critical %N curves is greatly reduced when they are estimated with datasets comprising only a few data under non-limiting N conditions or data covering only very low or high W values. Our results suggest that more reliable critical N dilution curves for species can be developed by grouping numerous datasets covering a broad range of G × E × M conditions.

Organ-specific critical N dilution curves and derived NNI relationships for winter wheat, winter oilseed rape and maize

The concept of the critical nitrogen (Ncrit) dilution curve and the derived NNI is generally accepted and used for many crops to describe the crop N status during vegetative growth. Based on field trials with different N treatments carried out in northern Germany, we identified Ncrit curves based on shoot DM, leaf DM and stem DM for winter wheat (2003/04 - 2007/08), winter oilseed rape (OSR, 2003/04 - 2005/06, 2012/13 - 2014/15), and maize (2007 + 2008), and related the derived organ-specific NNI (Nitrogen Nutrition Index) values. For each sampling date, Ncrit values were estimated using 'Linear-Plateau' functions, in order to fit a broken function for the shoot and stem fraction consisting of a constant N concentration and a negative power function describing the decrease of the N concentration. For the leaf fractions of wheat and OSR, a linear regression gave the best fit, in maize a negative power function. The relationship between the organ-specific NNI was described by a broken function with two linear branches differing in their slope.Shoot dry matter (DM) based Ncrit curves were comparable to previously published dilution curves. Maize leaf N concentration was clearly lower than that of wheat and OSR. Leaf Ncrit of wheat and OSR decreased only slightly during the growth period, but maize Ncrit showed a more substantial decrease at low DM. Contrarily, all crops showed similar stem Ncrit curves. Comparison of organ-specific N nutrition index (NNI) revealed that at lower NNIshoot, the increase in NNIleaf was initially higher, while NNIstem exhibited a steeper increase at higher NNIshoot. Our results suggest that plants use primarily the stem compared to the leaves as temporary N storage at high N availability; however, the effect in wheat was less pronounced leading to the question of the capacity of N translocation for an adequate grain protein concentration.

Uncertainty analysis of critical nitrogen dilution curves for wheat

Critical nitrogen (Nc) dilution curves have been widely used for the plant N status diagnosis, N management, crop modeling, and remote sensing. Wheat is a major crop worldwide whose Nc dilution curves developed under different conditions (genotype × environment × management) show large parameter variations. Herein, a dataset of 19 nitrogen fertilizer experiments (n = 656) from five wheat planting sites in China was used to evaluate the uncertainty in these curves and explain the sources of differences using the Bayesian theory method. The uncertainty of the fitted curve decreased with the increase in plant biomass. The parameter A2 of fitted curves of genotype × environment × management combinations showed a greater variation than A1, with slight parameter differences among different genotypes and planting sites. The variables related to genotype and growth environment, i.e., maximum N concentration, maximum biomass, and accumulated growing degree days during the vegetative growth period, were the sources of differences in curve parameters. Though the Nc curve differences between genotype × environment × management were statistically significant, the nitrogen nutrition index (NNI) differences remained relatively small. This study provides insights for developing a more diverse Nc dilution curve to aid in optimal nitrogen fertilization management in wheat.

Determining nitrogen status and quantifying nitrogen fertilizer requirement using a critical nitrogen dilution curve for hybrid indica rice under mechanical pot-seedling transplanting pattern

Field experiments of nitrogen (N) treatment at five different application rates (0, 75, 150, 225, and 300 kg ha−1) were conducted under pot-seedling mechanical transplanting (PMT) in 2018 and 2019. Two high-quality and high-yielding hybrids of indica rice, Huiliangyou 898 and Y Liangyou 900, were used in this study. The N nutrition index (NNI) and accumulated N deficit (Nand), used to assess the N nutrition status in real-time, were calculated for the indica cultivars under PMT with a critical nitrogen concentration (Nc) dilution model based on shoot dry matter (DM) during the whole rice growth stage. The relationships between NNI and Nand with relative yield (RY) were determined, and accurate N application schemes were developed for hybrids indica rice under PMT. The results indicated that high application rate of N-fertilizer significantly increased the concentrations of shoot DM and N in aboveground organs during the observed stages in the two cultivars for two years (P<0.05). The Nc dilution model of hybrid indica cultivars was Nc=4.02DM−0.42 (R2=0.97) combining the two cultivars under PMT. Root-mean-square error and normalized root-mean-square error of the curve verification were 0.23 and 10.61%, respectively. The NNI and Nand ranged from 0.58 to 1.31 and 109 to –55 kg ha−1, respectively, in the two cultivars for all N treatments. NNI showed a linear relationship with Nand during the entire growth stage (0.53<R2<0.99, P<0.01). In addition, NNI showed a linear-plateau relationship with RY (0.73<R2<0.92, P<0.01) throughout the observed stages. These results suggest that the models can accurately diagnose the N-nutrition status and support effective N-fertilizer management in real-time for hybrid indica rice under PMT.

A new canopy chlorophyll index-based paddy rice critical nitrogen dilution curve in eastern China

Abstract Nitrogen (N) plays an essential role in the crop growing cycle. Canopy vegetation indexes and chlorophyll concentration were important tools in-crop N status diagnosis and provided a crucial guide for agricultural managers. This work focused on evaluating the performance of different chlorophyll-related indexes (canopy chlorophyll index, CCI) and Greenseeker RT 200 values (GS values, normalized difference vegetation index, NDVI & Ratio vegetation index, RVI) in crop N nutrient diagnosis. Four experiments were conducted with multiple N fertilizer rates (0 ∼ 390 kg N ha−1) and seven Japonica rice (Oryza sativa L.). Results suggested that the relationship between CCI value and tissue nitrogen accumulation [including leaf nitrogen accumulation (LNA) and plant N accumulation (PNA)] was more reliable than that of GS values. Compered GS values with CCI values-based N concentration dilution curves, CCI-based Nc curve showed better accuracy and lower bias than GS values-based curves. And this curve lower than the reference LAI basis Nc curve and higher than the dry matter-based curve. The N nutrition index (NNI), calculated by the CCI-based curve, ranged from 0.31 to 1.33 during the vegetative stage. A significant positive relationship between CCI values and accumulated N deficit (AND) applications over the rice developmental stages. This present study also proved that CCI could be used to predict grain yield in total growth periods. These developed canopy level vegetation indexes-based Nc curve as a novel tool to offer more choices for evaluating crop N nutrition status and precision N topdressing management in Japonica rice of China.

Plastic film mulching affects the critical nitrogen dilution curve of drip-irrigated maize

Critical nitrogen dilution curves (CNDC) can efficiently diagnose nitrogen (N) condition of crops. Unfortunately, no CNDC exits for mulched drip-irrigated crops. Here we determine the CNDCs of drip-irrigated maize (Zea mays L.) with and without plastic mulch and investigate effects of plastic mulch on soil NO3−-N concentration in root zone (Nsoil), maize morphology, and CNDC changes. Aboveground dry biomass (DM), crop N concentration, soil N concentration, and related morphological characteristics of maize were measured in Northwest China under five N application rates with and without plastic mulch to calculate critical N concentration (Nc) and develop CNDCs. Plastic film mulching decreased Nsoil by 16.5 % and increased DM by 25.9 %. Mulching increased DM more than root growth and resulted in a lower root to shoot ratio compared with that of no mulching. Plastic film mulching affected CNDC and grain yields by increasing DM, thus lowering root to shoot ratio. CNDCs were Nc = 3.58DM−0.36 [R2 = 0.98] for drip-irrigated maize and Nc = 4.17DM−0.35 [R2 = 0.94] for mulched drip-irrigated maize. Mulching lowered nitrogen nutrition index at silking stage and increased it at physiological maturity stage. These results indicate that CNDC can be used to correctly determine N application rates for mulched drip-irrigated maize production.

Construction of critical nitrogen dilution curve based on dry matter in diffe rent organs of summer maize and estimation of grain yield

Construction of critical nitrogen dilution curve based on dry matter in diffe rent organs of summer maize and estimation of grain yield

Diagnosis of camelina seed yield and quality across an on-farm experimental network

Camelina [Camelina sativa (L.) Crantz] is an emerging oilseed crop combining both industrial and agronomic advantages. Camelina seed yield, oil and protein contents, and fatty-acid composition, vary across genotypes, environments, and agricultural practices. However, no studies have been conducted to identify and rank major limiting factors explaining yield and quality variations under on-farm conditions. Camelina performance was measured on 39 experimental strips corresponding to five camelina crop management routes (grown as an intercrop or sole crop), implemented in nine farmers’ fields across northern France in 2017 and 2018. The ranking of candidate limiting factors, defined a priori from scientific literature, was carried out using a model mixing method based on the Akaike Information Criterion. Main limiting factors of camelina yield (ranging from 62 to 2585 kg ha−1) were nitrogen crop status at flowering stage and downy mildew. Camelina yield was indeed positively correlated with the Nitrogen Nutrition Index at flowering stage (R2 = 0.44, p = 0.007). Oil content varied from 36.6 to 46.5 % and was negatively correlated with protein content. Main indicators explaining oil content variations were grain filling duration and downy mildew. Both poly-unsaturated and linolenic acid contents were positively correlated to grain filling duration, and negatively correlated to temperature during grain filling period. Camelina nitrogen status at flowering stage was mainly explained by N uptake of the intercropped species (pea or barley), and the amount of available inorganic nitrogen in the soil between sowing and flowering. Downy mildew was influenced by both weather conditions and the amount of weed biomass.This study showed a large variability in camelina seed yield and quality under on-farm conditions. The identification of the major limiting factors made it possible to pinpoint ways of improving camelina performance namely choosing genotypes with high resistance to mildew, better managing nitrogen fertilization or delaying camelina sowing date. Finally we also identified major research topics to be addressed to support the adoption of this new crop by farmers as the elaboration of the critical nitrogen dilution curve.

A Modified Critical Nitrogen Dilution Curve for Winter Wheat to Diagnose Nitrogen Status Under Different Nitrogen and Irrigation Rates.

The accuracy of nitrogen (N) diagnosis is essential to improve N use efficiency. The standard critical N concentration (standard Nc) dilution curves, an expression of the dynamics of N uptake and dry matter accumulation in plants, are widely used to diagnose the N status of crops. Several standard Nc dilution curves were proposed and validated for several crops, based on experiments involving different N fertilizer treatments. However, standard Nc dilution curves are affected by crop water status, e.g., resulting from differences in irrigation management. This paper aimed at developing a N diagnostic model under the coupling effect of irrigation and fertilizer managements. For this purpose, Nc dilution curves were developed under different irrigation rates. Additionally, plant water content (PWC), leaf water content (LWC), leaf area index (LAI), equivalent water thickness (EWT), and leaf area duration (LAD) were introduced into the model, to construct a modified Nc (mNc) dilution curve. The mNc dilution curves were designed using the principle of hierarchical linear model (HLM), introducing aboveground dry biomass (AGB) as the first layer of information, whereas the second layer of information included the different agronomic variables (PWC, LWC, LAI, EWT, and LAD). The results showed that parameters “a” and “b” of the standard Nc dilution curves ranged from 5.17 to 6.52 and −0.69 to −0.38 respectively. Parameter “a” was easily affected by different management conditions. The performance of standard Nc dilution models obtained by the cross-validation method was worse than that of mNc dilution models. The Nc dilution curve based on 4 years of data was described by the negative power equation Nc = 5.05 × AGB–0.47, with R2 and nRMSE of 0.63 and 0.21, respectively. The mNc dilution curve considers different treatments and was represented by the equation mNc = a×AGB−b, where a = 2.09 × PWC + 3.24, b = −0.02 × LAI + 0.51, with R2 and nRMSE of 0.79 and 0.13, respectively. For winter wheat, C3 crop, there would be a few problems in using standard Nc dilution methods to guide field management, however, this study provides a reliable method for constructing mNc dilution curves under different water and N fertilizer management. Due to the significant differences in hereditary, CO2 fixation efficiency and N metabolism pathways for C3 and C4 crops, the construction of mNc dilution curve suitable for different N response mechanisms will be conducive to the sustainable N management in crop plants.

Determination of Critical Nitrogen Dilution Curve Based on Canopy Cover Data for Summer Maize

ABSTRACT Estimation of canopy cover (CC) can be replaced with measurement of dry matter (DM) during the growing season, which leads to saving cost and time. A variety of software programs, such as Canopeo, have recently been launched for estimating CC by processing digital images. The main objective of the present study was to validate whether the CC estimated by Canopeo could be used to determine the critical nitrogen dilution curve (CNDC) of maize. DM and critical nitrogen concentration (%Nc) of summer maize were measured during the growing seasons in 2015 and 2016. On the same dates, CC was estimated by digital images and Canopeo. The CNDC based on DM (Nc, DM) was accurately described by the equation Nc, DM = 2.9DM−0.27. Furthermore, an exponential relationship was observed between CC and DM (R2 = 0.934) that resulted in the estimation of DM based on CC (DMcc). A new CNDC based on CC was determined (Nc,CC = 4e −1.17CC) by replacing DMcc in the Nc,DM which has an acceptable accuracy in estimating Nitrogen Nutrition Index. These results demonstrate that Canopeo can be applied as a useful tool to develop CNDC and Nitrogen management for different varieties of plants under various climatic conditions.

Construction of a critical nitrogen dilution curve for maize in Southwest China

There is an urgent need for suitable nitrogen nutrition models for Southwest China, which take into account nutritional differences at the cultivar level, to provide scientific guidance for cultivar-specific fertilizer applications during maize production. In this study, the nitrogen-efficient maize cultivar Zhenghong 311 and the nitrogen-inefficient maize cultivar Xianyu 508 were used in a three-year field experiment and a 2-year field pot experiment with nitrogen application rates ranging from 0 to 450 kg·hm−2 to construct a critical nitrogen dilution curve model for each maize cultivar. The usefulness of this model to diagnose nitrogen status and evaluate maize fertilization needs was subsequently analyzed. We found that the critical nitrogen concentration in maize aboveground tissues was a power function of the biomass, described by the equations Nc = 26.126 W−0.292 and Nc = 25.826 W−0.302 for ZH 311 and XY 508 cultivars, respectively. The fitting degree of these equations was significant or highly significant, demonstrating the suitability of these models to diagnose N deficiency and fertilization needs in maize plants grown in the hilly areas of central Sichuan. A very significant linear positive correlation between the nitrogen nutrient index (NNI) and nitrogen concentration in the aboveground tissues was detected. Based on this, we calculated the nitrogen concentration (Nt) for an NNI equal to 1 at different maize growth stages in both cultivars and observed that the Nt value can be used as a reference index for nitrogen nutrition diagnosis. Additionally, we found a highly significant quadratic convex function relationship between the NNI (y) and the nitrogen fertilizer level (x). The following regression equations were derived for these maize cultivars with the data obtained from each growth period along five consecutive years (2011–2015): yZH 311 = − 0.000005x2 + 0.003074x + 0.553206 (R2 = 0.5432**) and yXY 508 = − 0.000004x2 + 0.002914x + 0.512555 (R2 = 0.6279**). For an NNI value equal to 1, the nitrogen application level required was 224.07 kg·hm−2 for ZH 311 and 283.01 kg·hm−2 for XY 508, indicating that the suitable application rate for the nitrogen-efficient cultivar is lower than that for the nitrogen-inefficient cultivar. Our experimental data reinforce the concept that selecting nitrogen-efficient maize cultivars is an effective technical measure to reduce nitrogen input needs and increase nitrogen use efficiency during maize production.

Shoot- and tuber-based critical nitrogen dilution curves for the prediction of the N status in potato

Abstract Critical nitrogen (N) dilution curves describe the critical N concentration in plant tissues during crop growth and they are used to estimate the N nutriton status of whole plants in potato. Little is known, however, about the critical N dilution curves in specific plant parts such as shoots and tubers. Our objectives were (i) to determine critical shoot and tuber N dilution curves; (ii) to compare these curves with critical N dilution curves determined on whole plants (shoot + tubers); and (iii) to assess the possibility of using the critical shoot and tuber N dilution curves to estimate the N nutrition status of potato and tuber quality. Seven potato cultivars were assessed under different N supplies and environmental conditions in Canada and Argentina. Shoot biomass (leaves + stems) and tuber biomass along with their N concentrations were measured at regular intervals during the growing season. Tuber yield, dry matter concentration, and nitrate (N-NO3−) concentration were measured at harvest. We determined the coefficients of the critical N dilution curves expressed as N = a × W-b with N as the N concentration in shoot or tuber biomass, and W their respective biomass. Among cultivars, coefficients a and b for shoot biomass ranged from 5.08 to 5.68 and from 0.18 to 0.28, respectively, while coefficients a and b for tubers ranged from 1.54 to 1.87 and from 0.17 to 0.21, respectively. The shoot (NNIsh) and tuber (NNIt) N nutrition indices were both highly related to the N nutrition index in whole plants (R2 = 0.88; R2 = 0.98; P

Analyzing uncertainty in critical nitrogen dilution curves

Abstract Nitrogen critical curves are frequently used to diagnose the N status of crops and grasslands. They play an important role in plant modelling and are frequently used in fertilizer management tools. During the last 20 years, a number of studies have been conducted for comparing critical curves obtained in various conditions (e.g., different cultivars) and understanding the origin of their differences. However, uncertainty in the determination of these curves is generally poorly analyzed in these studies, which increase the risk of false conclusions, in particular on the existence of differences between species, cultivars and cropping systems. Here, we present a Bayesian statistical model for estimating parameters of critical nitrogen dilution curve from experimental data. Contrary to standard methods commonly used for fitting critical nitrogen dilution curves, the proposed approach allows one to fit these curves in only one step, i.e., directly from the original biomass and nitrogen content measurements. Specifically, this method does not require the classification of nitrogen-limited data against non-nitrogen-limited data and does not necessitate the preliminary identification of critical nitrogen concentrations. Another advantage of the proposed method is that it can be easily implemented using freely-available software. We illustrate its practical interest using experimental data collected for winter wheat in France, and for maize and rice in China. We show that this method is useful for analyzing uncertainty in the fitted critical nitrogen curves and for comparing several curves obtained for different crop species and cultivars. The proposed method is based on the specification of prior probability distributions defining plausible ranges of values for the critical curve parameters, and we show here that it is preferable to use prior distributions that are not very informative if we want to limit their influence on the final result.