Critical Nitrogen Dilution Curve Research Articles

Developing a new active canopy sensor- and machine learning-based in-season rice nitrogen status diagnosis and recommendation strategy

ContextTraditional critical nitrogen (N) dilution curve (CNDC) construction for N nutrition index (NNI) determination has limitations for in-season crop N diagnosis and recommendation under diverse on-farm conditions. ObjectivesThis study was conducted to (i) develop a new rice (Oryza sativa L.) critical N concentration (Nc) determination approach using vegetation index-based CNDCs; and (ii) develop an N recommendation strategy with this new Nc determination approach and evaluate its reliability and practicality. MethodsFive years of plot and on-farm experiments involving three japonica rice varieties were conducted at fourteen sites in Qixing Farm, Northeast China. Two machine learning (ML) methods, random forest (RF) and extended gradient boosting (XGBoost) regression, were used to fuse multi-source data including genotype, environment, management, growth stage, normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) from portable active canopy sensor RapidSCAN. The CNDC was established using NDVI and NDRE instead of aboveground biomass (AGB) measured by destructive sampling. A new in-season N diagnosis and recommendation strategy was further developed using direct and indirect NNI prediction using multi-source data fusion and ML models. ResultsThe new CNDC based on NDVI or NDRE explained 94−96 % of Nc variability in the evaluation dataset when it was coupled with environmental and agronomic factors using ML models. The ML-based PNC and NNI prediction models explained 85 % and 21–36 % more variability over simple regression models using NDVI or NDRE in the evaluation dataset, respectively. The new in-season N diagnosis strategy using the NDVI and NDRE-based CNDCs and plant N concentration (PNC) predicted with RF model and multi-source data fusion performed slightly better than direct NNI prediction, explaining 7 % more of NNI variability and achieving 89 % of the areal agreement for N diagnosis across all evaluation experiments. Integrating this new N management strategy into the precision rice management system (as ML_PRM) increased yield, N use efficiency (NUE) and economic benefits over farmer’s practice (FP) by 7–15 %, 11–71 % and 4–16 % (161–596 $ ha−1), respectively, and increased NUE by 11–26 % and economic benefits by 8–97 $ ha−1 than regional optimum rice management (RORM) under rice N surplus status under on-farm conditions. ConclusionsIn-season rice N status diagnosis can be improved using NDVI- and NDRE-based CNDC and PNC predicted by ML modeling with multi-source data fusion. ImplicationsThe active canopy sensor- and ML-based in-season N diagnosis and management strategy is more practical for applications under diverse on-farm conditions and has the potential to improve rice yield and ecological and economic benefits.

Determining nitrogen status using a universal critical nitrogen dilution curve for predicting flue-cured tobacco yield and quality

The critical nitrogen (Nc) dilution curve is considered an effective method for crop nitrogen (N) diagnosis, fertilization decision-making, and crop modeling. The Nc dilution curve is typically described using a power function curve (Nc = A1W−A2). This study established a universal Nc dilution curve and evaluated its potential application in flue-cured tobacco (Nicotiana tabacum L.) N diagnosis, yield, and quality regulation. Field experiments were conducted involving three tobacco varieties (Honghuadajinyuan, Yunyan87, and K326) and four N application rates (0 to > 90 kg N ha−1). The study was conducted in Southwest China from 2021 to 2022. The universal Nc curve obtained across all experimental data was 3.45 W−0.39. The parameter A2 was more susceptible to genotype and environment interactions than parameter A1. The uncertainty first rapidly decreased and then remained at a lower value as biomass increased. The relationship between leaf biomass and days after transplantation and accumulated growth degree was robust. The N nutrition index (NNI) and accumulated N deficiency effectively determined leaf N status and N demand, respectively. There was an inverse correlation between the NNI, leaf yield, and between the superior and medium leaf ratios. The quantitative relationship can be used to adjust the synergistic production of tobacco yield and leaf quality.

Establishment of lettuce critical nitrogen dilution curves based on total dry matter, total leaf area and leaf area duration

ABSTRACT Considering the environmental issues linked to over fertilization, optimizing N fertilizer use is crucial for sustainable agriculture. Assessing the crop N status through calculating the N nutrition index (NNI) on the basis of critical N concentration (Nc) concept could help determine the minimum amount of N fertilizer to ensure maximum crop production. The present study aimed to develop, validate and compare three new critical N dilution curves (CNDCs) on the basis of lettuce total dry matter (TDM), total leaf area (TLA) and leaf area duration (LAD). Greenhouse experiments were conducted with six N application rates at the University of Tehran, Iran. Aboveground TDM, TLA and N concentration were measured at weekly intervals during the lettuce growth cycle. Relationships between Nc and TDM, TLA and LAD were described by three power functions (%Nc = 4.84 TDM−0.11, %Nc = 7.73 TLA−0.11, %Nc = 9.40 LAD−0.11). Furthermore, an allometric relationship between lettuce TDM and TLA (TLA = 0.75 TDM0.34) was obtained. The developed TLA and LAD-based CNDCs have the benefit of being non-destructive if TLA could be measured by portable devices. Overall, the CNDCs developed in the present research could provide accurate N status diagnosis for lettuce N management under greenhouse conditions.

Comprehensive Evaluation of Tomato Growth Status under Aerated Drip Irrigation Based on Critical Nitrogen Concentration and Nitrogen Nutrient Diagnosis.

In order to provide a theoretical basis for the rational application of nitrogen fertilizer for tomatoes under aerated drip irrigation, a model of the critical nitrogen dilution curve was established in this study, and the feasibility of the nitrogen nutrition index (NNI) for the real-time diagnosis and evaluation of the nitrogen nutrient status was explored. The tomato variety "FENOUYA" was used as the test crop, and aerated drip irrigation was adopted by setting three levels of aeration rates, namely, A1 (dissolved oxygen concentration of irrigation water is 5 mg L-1), A2 (dissolved oxygen concentration of irrigation water is 15 mg L-1), and A3 (dissolved oxygen concentration of irrigation water is 40 mg L-1), and three levels of nitrogen rates, namely, N1 (120 kg ha-1), N2 (180 kg ha-1) and N3 (240 kg ha-1). The model of the critical nitrogen concentration dilution of tomatoes under different aerated treatments was established. The results showed that (1) the dry matter accumulation of tomatoes increased with the increase in the nitrogen application rate in a certain range and it showed a trend of first increase and then decrease with the increase in aeration rate. (2) As the reproductive period progressed, the nitrogen concentration in tomato plants showed a decreasing trend. (3) There was a power exponential relationship between the critical nitrogen concentration of tomato plant growth and above-ground biomass under different levels of aeration and nitrogen application rate, but the power exponential curves were characterized by A1 (Nc = 15.674DM-0.658), A2 (Nc = 101.116DM-0.455), A3 (Nc = 119.527DM-0.535), N1 (Nc = 33.819DM-0.153), N2 (Nc = 127.759DM-0.555) and N3 (Nc = 209.696DM-0.683). The standardized root mean square error (n-RMSE) values were 0.08%, 3.68%, 3.79% 0.50%, 1.08%, and 0.55%, which were less than 10%, and the model has good stability. (4) The effect of an increased nitrogen application rate on the critical nitrogen concentration dilution curve was more significant than that of the increase in aeration rate. (5) A nitrogen nutrition index model was built based on the critical nitrogen concentration model to evaluate the nitrogen nutritional status of tomatoes, whereby 180 kg ha-1 was the optimal nitrogen application rate, and 15 mg L-1 dissolved oxygen of irrigation water was the optimal aeration rate for tomatoes.

Optimizing nitrogen application rate by establishing a unified critical nitrogen dilution curve for maize under different mulching planting patterns

Nitrogen (N) nutrition is essential for crop production and a critical N dilution curve (CNDC) could provide a novel strategy for diagnosing plant N status. CNDCs for several crops under different scenarios have been established to optimize N management. However, few studies have been conducted to establish a CNDC for maize (Zea mays L.) under ridge-furrow planting with film mulching over ridges, a planting pattern that has been widely adopted in semi-arid regions due to its improvement in soil water status. In addition, the effects of varied planting patterns on CNDC remain unknown. Therefore, a four-year (2018–2021) field experiment was conducted to establish CNDCs and provide a precise diagnosis of maize N status under different mulching planting patterns. Four N levels (0, 90, 180, and 270 kg N ha1 for the 2018–2020 period; and 100, 150, 200, and 300 kg N ha1 for 2021) were applied under three mulching planting patterns: flat planting without film mulching, ridge-furrow planting with transparent plastic film mulching over ridges, and ridge-furrow planting with biodegradable film mulching over ridges. Taking into consideration of the 95 % credibility intervals, no significant differences in CNDCs and its estimated parameters were observed across years and mulching planting patterns. Therefore, we derived a unified CNDC equation defined as NC = 3.10 W0.40 based on data obtained from the three mulching planting patterns during the four years. Furthermore, no significant differences were observed in critical N nutrition index thresholds. Consequently, the results supported establishing a universal CNDC model to diagnose maize N status in northwest China. The optimal N application rate for maize to obtain great yield and high N use efficiency in the region was 180–200 kg ha1. Further studies are required to evaluate CNDC for maize grown under various N fertilizer types, planting patterns, rainfall years, and regions, which would lead to a more precise diagnosis of maize N status and a more accurate N management regime.

Evaluating Critical Nitrogen Dilution Curves for Assessing Maize Nitrogen Status across the US Midwest

Plant N concentration (PNC) has been commonly used to guide farmers in assessing maize (Zea mays L.) N status and making in-season N fertilization decisions. However, PNC varies based on the development stage. Therefore, a relationship between biomass and N concentration is needed (i.e., critical N dilution curve; CNDC) to better understand when plants are N deficient. A few CNDCs have been developed and used for plant N status diagnoses but have not been tested in the US Midwest. The objective of this study was to evaluate under highly diverse soil and weather conditions in the US Midwest the performance of CNDCs developed in France and China for assessing maize N status. Maize N rate response trials were conducted across eight US Midwest states over three years. This analysis utilized plant and soil measurements at V9 and VT development stages and final grain yield. Results showed that the French CNDC (y = 34.0x−0.37, where y is critical PNC, and x is aboveground biomass) was better with a 91% N status classification accuracy compared to only 62% with the Chinese CNDC (y = 36.5x−0.48). The N nutrition index (NNI), which is the quotient of the measured PNC and the calculated critical N concentration (Nc) based on the French CNDC was significantly related to soil nitrate-N content (R2 = 0.38–0.56). Relative grain yield on average reached a plateau at NNI values of 1.36 at V9 and 1.21 at VT but for individual sites ranging from 0.80 to 1.41 at V9 and from 0.62 to 1.75 at VT. The NNI threshold values or ranges optimal for crop biomass production may not be optimal for grain yield production. It is concluded that the CNDC developed in France is suitable as a general diagnostic tool for assessing maize N status in US Midwest. However, the threshold values of NNI for diagnosing maize N status and guiding N applications vary significantly across the region, making it challenging to guide specific on-farm N management. More studies are needed to determine how to effectively use CNDC to make in-season N recommendations in the US Midwest.

Determination of a critical nitrogen dilution curve and nitrogen nutrition index for maize in Western Nile Delta of Egypt

Critical nitrogen (N) dilution curves are valuable tools for diagnosing N deficiency and managing its levels in plants. The objectives of this study were to establish a critical N dilution curve for maize in Egypt’s West Delta region, assess the potential of using it to compute the N nutrition index (NNI) and compare this curve with existing curves for maize in other regions. The experiment was carried out across four site years (2020–2021), with seven N fertilization rates (0–360 kg N ha−1) used to induce variability in plant growth. Aboveground shoot biomass (W; Mg DM [dry matter] ha−1) and N concentration (Nc ; g kg−1 DM) were determined on five sampling dates during the growing season. A critical N dilution curve ( was developed, which differed moderately from those reported in France, Germany, and China. The NNI computed from this curve recognized both limited and non-limited N nutrition conditions. The findings of progressing NNI suggest that the period between V9 (9th leaf collar fully unfolded) and V12 is critical and that a sufficient supply of N fertilizer is essential. Furthermore, the NNI derived from an independent dataset, utilizing the Nc established in this study, exhibited a strong relationship with the relative grain yield. The relationship was characterized by a linear plateau function, which accounted for 74% of the observed variance. The results of this study will offer dependable guidance for detecting N levels in maize and customizing the application of precision N fertilizers to enhance yield and use efficiency.

Estimation of in-season nitrogen requirement for drip-irrigated spring maize without or with straw incorporation using critical nitrogen dilution curve

Estimation of in-season nitrogen requirement for drip-irrigated spring maize without or with straw incorporation using critical nitrogen dilution curve

In-season assessment of agronomic nitrogen use efficiency and its components in winter wheat using critical nitrogen dilution curve.

Accurate and timely nitrogen (N) scheduling requires knowledge of in-season crop N deficit. Therefore, understanding the association between crop growth and crop N demand during its growth period is imperative for fine-tuning N scheduling decisions to actual crop N demand and to enhance N use efficiency. The concept of the critical N dilution curve has been employed to assess and quantify the intensity and time of crop N deficit. However, research regarding the association between crop N deficit and N use efficiency in wheat is limited. The present study was carried out to determine whether there are relationships between the accumulated nitrogen deficit (Nand) and agronomic N use efficiency (AEN) as well as with its components (N fertilizer recovery efficiency (REN) and N fertilizer physiological efficiency (PEN)) of winter wheat and to explore the potential capacity of Nand for predicting AEN and its components. Data acquired from five variable N rates (0, 75, 150, 225, and 300kg ha-1) field experiments using six winter wheat cultivars were used to establish and validate the relationships between Nand and AEN, REN, and PEN. The results indicated that plant N concentration in winter wheat was significantly affected by N application rates. Nand varied from -65.73 to 104.37kg ha-1 after Feekes stage 6 under different N application rates. The AEN and its components were also affected by cultivars, N levels, seasons, and growth stages. A positive correlation was observed between Nand, AEN, and its components. Validation using an independent data set showed the robustness of the newly developed empirical models to accurately predict AEN, REN, and PEN with an RMSE of 3.43kg kg-1, 4.22%, and 3.67kg kg-1 and RRMSE of 17.53%, 12.46%, and 13.17%, respectively. This indicates that Nand has the potential to predict AEN and its components during the growth period of winter wheat. The findings will assist in improving in-season N use efficiency by fine-tuning N scheduling decisions in winter wheat cultivation.

Developing a nitrogen fertilizer management model for wheat in calcareous soils using the critical nitrogen dilution curve

The critical nitrogen (N) dilution curve, which expresses whole-plant critical N concentration as a function of shoot biomass, can be used as a N management diagnostic tool for cereals. The objectives of this research were to develop a critical N dilution curve for wheat grown in calcareous soils and to formulate a model for estimating N fertilizer requirement of wheat crop at different growth stages. Six N fertilization rates (0–250 kg N ha−1) were used to induce variability in plant growth throughout six site-years (three locations at West Delta of Egypt and two seasons [2020/21-2021/22]). Aboveground shoot biomass (W; Mg DM [dry matter] ha−1) and N concentration (Nc; g kg−1 DM) were determined on five sampling dates during the growing season. A critical N dilution curve was developed as: {N}_{mathrm{c}}=50.141 {mathrm{W}}^{-0.424}. The Nc dilution curve was then used to develop a N fertilizer topdressing strategy. The study relied on N nutrition index inferred from the Nc based on N uptake, and instead of relying on a single N recovery efficiency coefficient, a variable N recovery efficiency was developed. This approach increased the hypothetical N requirements at low N application rates while decreased requirements at high N application rates, implying that the Nc dilution curve can be used successfully to estimate the rates of supplemental N application. The developed strategy will provide a solid basis for precisely managing N fertilizer, though challenge ahead at the farm level will be in determining the actual shoot biomass and N concentration.

Comparison of statistical methods to fit critical nitrogen dilution curves

The critical nitrogen dilution curve (CNDC) is one of the most important models underpinning diagnostic tools of crop nitrogen (N) status. The CNDC relates plant N content (%N) to plant biomass under optimal nutritional conditions, using a simple nonlinear function with two parameters. More precisely, the CNDC estimates the critical %N (%NC) - the amount of %N needed to achieve maximum biomass at a certain moment. Thus, the comparison of a measured %N to %NC diagnoses if a plant is N deficient and if application of N fertilizer is necessary. Because of the practical importance of the CNDC, its parameters should be estimated as accurately as possible from field data. Two contrasting frameworks have been proposed in the literature for parameter estimation of the CNDC. The most popular approach is a sequential framework that consists of fitting two statistical models sequentially. Recently, an alternative framework has been introduced to estimate the parameters in a single step, using a hierarchical Bayesian model (hierarchical framework). In this study, we compare both methods and evaluate their performances for a large range of experimental designs. We consider datasets with different numbers of observation times (4, 8, 16), N fertilizer rates (3, 4, 5), and levels of measurement accuracy (low, medium, high). Our results show that the hierarchical framework outperforms the sequential framework under most scenarios. The sequential framework often resulted in poor statistical properties of the parameter estimates (e.g., increased bias and poorly calibrated confidence intervals) and to overestimated %NC values. The estimates for the amount of N needed to sustain N sufficiency levels were between 30 and 100 kg N ha−1 greater under the sequential framework, compared to the hierarchical framework. Thus, adopting the hierarchical framework could contribute to decreasing the risk of overfertilization and increasing the sustainability of agricultural systems.

Learning about the growing habits and reproductive strategy of Thinopyrum intermedium through the establishment of its critical nitrogen dilution curve

The perennial grain crop Thinopyrum intermedium can provide various ecosystem services and a dual production of grains and forage. Yet, to improve crop management, better knowledges of its physiological behavior and growing habits are required. The goal of this study was to characterize Th. intermedium nitrogen (N) requirements through the evaluation of its response to N fertilization and the subsequent determination of its critical nitrogen dilution curve (CNDC). A field experiment was implemented in Belgium during three growing seasons with various N fertilization schemes. Biomass of the different organs and their N contents were measured at specific phenological stages. To estimate the CNDC, a Bayesian hierarchical model was applied on the assembled dataset. The validity of the curve was assessed on an independent dataset including contrasted N situations. Globally, N fertilization had a positive impact on the dry matter (DM) of leaves, stems and ears (p-value<0.05). The aboveground biomass and N uptake were found maximum with fertilization comprised between 100 and 150 kg N/ha applied over the entire growing year. At grain harvest, total DM ranged from 7.0 to 16.4 t DM/ha for a fertilization strategy of 100 kg N/ha, depending upon the growing season. The N amount of the aboveground biomass was found to decrease during the second phase of the growing cycle. As observed with the proposed CNDC, the aerial N content tended to decrease with the evolution of growing stages and biomass accumulation. Through the low a-coefficient determined for the CNDC, it was confirmed that the crop had reduced need in terms of N nutrition. The reduced N requirements can be linked to the high N use efficiency and a potential resource-conservative strategy of the crop. This, combined with the observed decrease of the N uptake by the aboveground biomass during the second phase of growth, can be related to the long-term survival strategy of the crop. The latter requires substantial investments in perennial belowground structures coupled with reduced resource allocations to seeds. Our study has highlighted that Th. intermedium is able to reach a high shoot DM production with low N needs. Our proposed CNDC will be highly helpful to help define N requirements in various pedo-climatic environments and adjust accordingly the soil-crop management, among which the N fertilization. Ultimately, the low N requirements of Th. intermedium coupled with a high N use efficiency demonstrated that it could enhance agronomic and environmental benefits.

Potential of Establishing the Universal Critical Nitrogen Dilution Curve for Japonica Rice.

Establishing the universal critical nitrogen (NC) dilution curve can assist in crop N diagnosis at the regional scale. This study conducted 10-year N fertilizer experiments in Yangtze River Reaches to establish universal NC dilution curves for Japonica rice based on simple data-mixing (SDM), random forest algorithm (RFA), and Bayesian hierarchical model (BHM), respectively. Results showed that parameters a and b were affected by the genetic and environmental conditions. Based on RFA, highly related factors of a (plant height, specific leaf area at tillering end, and maximum dry matter weight during vegetative growth period) and b (accumulated growing degree days at tillering end, stem-leaf ratio at tillering end, and maximum leaf area index during vegetative growth period) were successfully applied to establish the universal curve. In addition, representative values (most probable number [MPN]) were selected from posterior distributions obtained by the BHM approach to explore universal parameters a and b. The universal curves established by SDM, RFA, and BHM-MPN were verified to have a strong N diagnostic capacity (N nutrition index validation R 2 ≥ 0.81). In summary, compared with the SDM approach, RFA and BHM-MPN can greatly simplify the modeling process (e.g., defining N-limiting or non-N-limiting groups) while maintaining a good accuracy, which are more conducive to the application and promotion at the regional scale.

Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat.

The organ-specific critical nitrogen (Nc) dilution curves are widely thought to represent a new approach for crop nitrogen (N) nutrition diagnosis, N management, and crop modeling. The Nc dilution curve can be described by a power function (Nc = A1·W-A2), while parameters A1 and A2 control the starting point and slope. This study aimed to investigate the uncertainty and drivers of organ-specific curves under different conditions. By using hierarchical Bayesian theory, parameters A1 and A2 of the organ-specific Nc dilution curves for wheat were derived and evaluated under 14 different genotype × environment × management (G × E × M) N fertilizer experiments. Our results show that parameters A1 and A2 are highly correlated. Although the variation of parameter A1 was less than that of A2, the values of both parameters can change significantly in response to G × E × M. Nitrogen nutrition index (NNI) calculated using organ-specific Nc is in general consistent with NNI estimated with overall shoot Nc, indicating that a simple organ-specific Nc dilution curve may be used for wheat N diagnosis to assist N management. However, the significant differences in organ-specific Nc dilution curves across G × E × M conditions imply potential errors in Nc and crop N demand estimated using a general Nc dilution curve in crop models, highlighting a clear need for improvement in Nc calculations in such models. Our results provide new insights into how to improve modeling of crop nitrogen-biomass relations and N management practices under G × E × M.

Establishing a critical nitrogen dilution curve for estimating nitrogen nutrition index of potato crop in tropical environments

The critical nitrogen (N) dilution curve (CNDC) ( Nc = A 1 W -A2 ) and the N nutrition index (NNI) have shown to be a robust diagnostic tool to assess crop N status. Several CNDCs were established for potatoes ( Solanum tuberosum L.) in various conditions. However, it is difficult to know if these different CNDCs reflect a true variability across genotype × environment × management (G×E × M) scenarios, or are rather linked to estimation errors. Therefore, the aims of this study were to (i) estimate and compare CNDCs via a Bayesian statistical approach for different G×E × M scenarios in tropical environments and (ii) assess the uncertainty in the relationship between tuber yield and NNI. Field experiments were conducted in three site-years (SYs) in the southeastern region of Brazil. Treatments consisted of two potato cultivars (Agata and Electra) and five N fertilization managements [differing in the N rates (0 −320 kg N ha -1 ) and/or application timings]. Based on 95% credibility intervals, we found no significant differences between CNDCs across G×E × M scenarios assessed and thus derived a single generic CNDC for both cultivars and all SYs defined by Nc = 3.86 W - 0.34 . This global CNDC was used to compute NNI and discriminate tuber yields obtained under N-limiting and non-N-limiting conditions. An uncertainty analysis revealed that critical NNI threshold values for the tuber yield response to N management were not statistically different among G×E × M scenarios. Therefore, these results support the use of a unique CNDC for estimating the N status (NNI) of potato crop in tropical environments. We found no evidence of the need for SY- or cultivar-specific CNDCs. Future studies should evaluate N dilution curves and NNI for potato across different production environments worldwide. • A new critical N curve was derived for potato in tropical environments. • The critical N curve ( Nc = 3.86 W -0.34 ) was obtained using a Bayesian analysis. • No evidence of variability in the critical N nutrition index threshold for yield. • No evidence of the need for cultivar- or site-specific parameters.

Establishing critical nitrogen dilution curves based on leaf area index and aboveground biomass for greenhouse cherry tomato: A Bayesian analysis

Intensification of greenhouse production is always closely related to massive nitrogen (N) losses to the environment. Therefore, precisely assessing crop N status and optimizing N fertilizer management are essential for the sustainability of greenhouse system. The study was endeavored to (1) assess whether the parameters of critical nitrogen (Nc) dilution curves were significantly affected by the irrigation level, and (2) compare if both leaf area index (LAI) and aboveground biomass (AGB) based Nc dilution curves could accurately diagnose cherry tomato N status using a recent Bayesian statistical approach. A three-year greenhouse cherry tomato experiment containing five N levels (0, 180, 270, 360 and 450 kg N ha−1) and three irrigation levels (60 %, 80 % and 100 % ET0, where ET0 was the reference evapotranspiration) was conducted from 2019 to 2021. The width of the 95 % credibility intervals of Nc dilution curves based on AGB and LAI decreased with the increasing AGB and LAI. Taking the 95 % credibility intervals of parameters A1 and A2 into consideration, water availability of 60 %–100 % ET0 had no significant effect on AGB-based Nc dilution curves in 2019 and 2021, and it also had no significant effect on LAI-based Nc dilution curves during 2019–2021. Delaying the transplanting date of greenhouse cherry tomato would significantly decrease parameter A1, while parameter A2 was not affected. The differences of nitrogen nutrition index (NNI) calculated from the AGB- and LAI-based Nc dilution curves were negligible under different irrigation levels and sampling dates. The maximum relative yield was associated with an NNI of 0.99 for both AGB and LAI. These results indicate that Nc dilution curves established based on both AGB and LAI could precisely diagnose cherry tomato N status. There is no need to establish specific Nc dilution curves for greenhouse cherry tomato under non-extremely water-stressed conditions.

Critical nitrogen dilution curve and dry matter production parameters for several Mediterranean vegetables

• Twelve typical Mediterranean vegetables were studied. • The average and critical nitrogen dilution curve coefficients were obtained. • The dry/fresh matter ratios and harvest indexes were also obtained. • There were no differences between the average and critical dilution curves. • Differences of dry matter yield did not affect any of the parameters. Inadequate nitrogen fertilizing practices lead to low nitrogen uptake efficiency (NUE), which increases water NO 3 − pollution, as well as N 2 O emissions to the atmosphere. In order to increase the NUE and decrease the N losses as NO 3 − and N 2 O from the soil-plant system, accurate data about optimum crop N concentrations and dry matter production throughout the growing season are still needed for many vegetables typically grown under Mediterranean climate. For this reason, several N fertilization trials were set up for globe artichoke, carrot, cauliflower, chard, chinese cabbage, early potato, leek, lettuce, onion, red cabbage, romanesco, and spinach, under the semiarid Mediterranean conditions of the Valencian Community (Eastern Spain) during several years. The fresh and dry matter weight ( W ), as well as the nitrogen concentration in the dry matter (% N ) in both the marketable and non-marketable crop parts, was measured between 3 and 7 times throughout their respective growing seasons. The a and b coefficients of the average N dilution curve (% N = a W − b ), for which all % N and W data were used, and the critical N dilution curve (% N c = a W c − b ), for which only the minimun % N for maximum W data were used if available, in addition to the dry/fresh yield matter ratio ( DM ) and the harvest index ( HI ), were calculated for all these crops. No significant differences were observed between the average and critical N dilution curve coefficients in this work. Interestingly, the coefficients of both N dilution curves differed from the ones found in the literature with the exception of those obtained for similar cultivars, e.g., early potatoes, and under similar climatic conditions, i.e., Mediterranean. Besides, there were neither differences of DM and HI among the several N fertilization treatments. Therefore, due to the absence of changes in the N dilution curve and dry matter production coefficients for the different N supplies, all these parameters were estimated on the basis of the whole dataset, i.e., regardless of the N input. The use of the critical nitrogen dilution curve coefficients and dry matter production parameters presented in this work should contribute to better fit the N fertilizer additions to N demands of these vegetables under Mediterranean conditions, mainly, by their use through simulation models. Therefore, the NUE in horticulture should increase and the N losses as NO 3 − to inland and sea waters in these environments, and as N 2 O to the atmosphere should decrease.

Estimation of Dry Matter and N Nutrient Status of Choy Sum by Analyzing Canopy Images and Plant Height Information

The estimation accuracy of plant dry matter by spectra- or remote sensing-based methods tends to decline when canopy coverage approaches closure; this is known as the saturation problem. This study aimed to enhance the estimation accuracy of plant dry matter and subsequently use the critical nitrogen dilution curve (CNDC) to diagnose N in Choy Sum by analyzing the combined information of canopy imaging and plant height. A three-year experiment with different N levels (0, 25, 50, 100, 150, and 200 kg∙ha−1) was conducted on Choy Sum. Variables of canopy coverage (CC) and plant height were used to build the dry matter and N estimation model. The results showed that the yields of N0 and N25 were significantly lower than those of high-N treatments (N50, N100, N150, and N200) for all three years. The variables of CC × Height had a significant linear relationship with dry matter, with R2 values above 0.87. The good performance of the CC × Height-based model implied that the saturation problem of dry matter prediction was well-addressed. By contrast, the relationship between dry matter and CC was best fitted by an exponential function. CNDC models built based on CC × Height information could satisfactorily differentiate groups of N deficiency and N abundance treatments, implying their feasibility in diagnosing N status. N application rates of 50–100 kgN/ha are recommended as optimal for a good yield of Choy Sum production in the study region.

Dataset characteristics for the determination of critical nitrogen dilution curves: From past to new guidelines

The determination of critical nitrogen (N) dilution curves (CNDCs) has been the subject of intensive study for the last decades due to its relevance to diagnosing crop N status. However, to date, minimum steps, data requirements and robust science-based guidelines to estimate CNDCs based on experimental data have not been formalized in the literature to ensure the reliability of an established nutrient dilution curve. In this study, we conducted a systematic review of the literature on CNDCs, described the main characteristics of the datasets used to establish CNDCs in the past, and finally identified a set of criteria specifying the minimum characteristics that a dataset must satisfy to be used to establish an accurate CNDC. Published CNDC studies showed large heterogeneity in the number of experiments (from 1 to 35), fertilizer N rates (from 2 to 7), and sampling times (from 2 to 16) used to fit the CNDCs. Given that, we quantified the sensitivity of the CNDC parameters to five dataset characteristics (number of experiments, N rates, and sampling times, attainment of Wmax plateau, and precision of the studies) using a Bayesian statistical model on a case-study estimation for maize. We found that the number of experiments is the main factor affecting the uncertainty of the fitted CNDC. Bootstrapping analyses showed that accurate CNDCs can be fitted with experiments having at least three N rates. Increasing the number of sampling times was more effective than using more than three N rates for reducing the uncertainty in the estimation of the parameters for the CNDCs. We also showed that more reliable CNDCs can be obtained when weighting each data by its precision. We concluded our analysis with formal recommendations of the minimum steps and data requirements to fit CNDC. The criteria established here should serve as a guide for the establishment of reliable dilution curves for N and other nutrients in the agricultural and biological sciences.

A global dataset to parametrize critical nitrogen dilution curves for major crop species

Precise management of crop nitrogen nutrition is essential to maximize yields while limiting pollution risks. For several decades, the critical nitrogen (N) dilution curve - relating plant biomass (W) to N concentration (%N) - has become a key tool for diagnosing plant nutritional status. Increasing number of studies are being conducted to parameterize critical N dilution curves of a wide range of crop species in different environments and N-fertilized conditions. A global synthesis of the resulting data is lacking on this topic. Here, we conduct a systematic review of the experimental data collected worldwide to parametrize critical N dilution curves. The dataset consists of 36 papers containing a total of 4454 observations for 19 major crop species distributed in 16 countries. The key variables of this dataset are the W and %N collected at three or more sampling times, containing three or more fertilizer N rate levels. This dataset can guide the development of generic critical N dilution curves, helps scientists to identify factors influencing plant N status, and leads to the formulation of more robust N recommendations for a broad range of environmental conditions.