Crop Nitrogen Fertilization Research Articles

The hidden indirect environmental effect undercuts the contribution of crop nitrogen fertilizer application to the net ecosystem economic benefit

The current environmental and economic challenges of the application of nitrogen (N) fertilizer on crops are not only to provide an adequate food supply but also to reduce the resulting environmental pollution. A comprehensive understanding of the multiple effects of N fertilizer application on crops will help to more accurately guide the application of N fertilizer to meet current challenges, and to promote sustainable crop production. It is widely known that excessive N fertilizer applied to crops can lead to N-related direct environmental effects, including reactive N (Nr) losses, greenhouse gas emissions, and high environmental costs. However, few studies have revealed the hidden indirect environmental effect of crop N fertilizer application and its impact on the net ecosystem economic benefit (NEEB), which may be triggered by a N-crop-pest cascade pathway. In this study, we conducted three-year wheat field experiments at five N fertilizer application rates (0, 70, 140, 210, and 280 kg ha−1) in a city on the North China Plain. Excluding wheat yield and direct N-related environmental effects, the indirect effects of N fertilizer application, including the occurrence of cereal aphids (the most important wheat insect pests), the use of chemical pesticides for pest control, the impacts on the environmental and human health damage costs and NEEB were studied. Our results showed that the abundances of cereal aphids positively correlated with the N fertilizer application rates. At each N fertilizer application rate (70, 140, 210, 280 kg ha−1), 0.447 kg of active ingredients of chemical pesticides (0.222 kg insecticides and 0.225 g fungicides) per hectare per season were used to control insect pests and pathogens, while no pesticides were used at 0 kg ha−1(i.e., no N fertilizer was applied). The environmental and human health damage costs of pesticides for pest control increased $8 per hectare for wheat at four N fertilizer application rates and then reduced NEEB by the same amount. Our work extends previous studies and reveals the indirect negative environmental effect of N fertilizer application on crops triggered by a N-crop-pest cascade pathway. This effect undercuts the contribution of crop N fertilizer application on NEEB.

A Review on Soil Nitrogen Sensing Technologies: Challenges, Progress and Perspectives

Nitrogen is a vital ingredient for plant development and growth. It is one of the most crucial indicators of soil fertility and crop growth conditions. For the monitoring of nitrogen loss patterns and the development of crop nitrogen fertilizer application strategies, an accurate determination of soil nitrogen concentration can be a valuable source of information. For the advancement of precision agriculture and the preservation of the natural ecological environment, an accurate, quick, and low-cost determination of soil nitrogen content and its variations is essential. This paper systematically analyzes and summarizes soil nitrogen detection methods by compiling and analyzing the relevant literature, comparing the advantages and disadvantages of various methods, and concluding with a discussion of the most significant challenges and future research trends in this field. This study provides a helpful resource for understanding the current status, application constraints, and future developments of nitrogen-sensing technologies in precision agriculture.

Crop Nitrogen Fertilization Schedule in Bread Wheat Affects the Mechanical Performances of Thermoplastic Films Obtained by Plasticization of Flours

Recent research has investigated the plasticization of wheat flour as a non-food alternative application. In this work, we analyzed the performances of thermoplastic films obtained using flours of two bread wheat cultivars (Bologna and Bora) grown in fall–spring under four nitrogen (N) fertilization treatments: (1) continuously well-N-fed (N300 = 300 kg N ha−1, split throughout the growth cycle); (2) N-fed only very early (N60-0 = 60 kg N ha−1, just one month after sowing); (3) N-fed only extremely late (N0-120 = 120 kg N ha−1 at pollination); (4) unfertilized control (N0). Flours were characterized for glutenin and gliadin fractions, Chopin’s alveograph parameters, Field Emission Scanning Electron Microscopy (FESEM) images, and thermogravimetric analysis (TGA), while films were evaluated for mechanical properties (tensile strength at break, σb; elongation at break, εb; Young’s modulus, E) and FESEM images. Differences among treatments for absolute and relative abundances of gluten fractions and alveographic parameters were extremely marked and gave rise to differences in tensile properties of thermoplastic films. Within each cultivar, the ranking of treatments for εb values was N0 > N60-0 > N0-120 > N300. Thus, εb was inversely correlated with crop N availability and total gluten content of the flour. The σb was less variable among N treatments; however, in both cultivars, it was high in N0 and N300 and appreciably lower in N0-120. Overall, the best mechanical performances were obtained with flours from crops not subjected to imbalances in N nutrition (N0, N300). Our work demonstrates that bioplastic engineering needs to take into consideration the variability of biological source material like that caused by different crop N availability.

Opportunities beyond CO2 for climate mitigation

Opportunities beyond CO2 for climate mitigation

Effect of Wheat Crop Nitrogen Fertilization Schedule on the Phenolic Content and Antioxidant Activity of Sprouts and Wheatgrass Obtained from Offspring Grains.

This work was aimed at investigating the effects of rate and timing of nitrogen fertilization applied to a maternal wheat crop on phytochemical content and antioxidant activity of edible sprouts and wheatgrass obtained from offspring grains. We hypothesized that imbalance in N nutrition experienced by the mother plants translates into transgenerational responses on seedlings obtained from the offspring seeds. To this purpose, we sprouted grains of two bread wheat cultivars (Bologna and Bora) grown in the field under four N fertilization schedules: constantly well N fed with a total of 300 kg N ha−1; N fed only very early, i.e., one month after sowing, with 60 kg N ha−1; N fed only late, i.e., at initial shoot elongation, with 120 kg N ha−1; and unfertilized control. We measured percent germination, seedling growth, vegetation indices (by reflectance spectroscopy), the phytochemical content (total phenols, phenolic acids, carotenoids, chlorophylls), and the antioxidant activity (by gold nanoparticles photometric assay) of extracts in sprout and wheatgrass obtained from the harvested seeds. Our main finding is that grains obtained from crops subjected to late N deficiency produced wheatgrass with much higher phenolic content (as compared to the other N treatments), and this was observed in both cultivars. Thus, we conclude that late N deficiency is a stressing condition which elicits the production of phenols. This may help counterbalance the loss of income related to lower grain yield in crops subjected to such an imbalance in N nutrition.

Nécessité d’un changement de paradigme pour étudier la nutrition et la fertilisation azotée des cultures / Need for a paradigm shift to study crop nutrition and nitrogen fertilization

Nitrogen fertilization of crops has long been based on a statistical analysis of the response of their yield to increasing doses of fertilizers. This prognosis has led to an insurance practice applying excessive doses of nitrogen so as not to penalize yields. A method for predicting the nitrogen balance of a crop has been developed to correct this trend but remains too highly imprecise. Diagnosis of the nitrogen nutrition status of a crop has recently emerged, reducing the uncertainty linked to the variability of local conditions. This diagnosis, integrated into decision support algorithms, makes it possible to apply fertilizers only “where” and “when” the nutritional status of the crops requires it. This precision must make it possible to achieve the targeted yields while minimizing the environmental impacts.

Simplifying residual nitrogen (Nmin) sampling strategies and crop response

Globally, important nitrogen fertilizer decisions are often made at the early stages of plant development, when plants are not yet sufficiently indicative of their needs. Optimizing nitrogen fertilization of crops requires assessing the available soil mineral nitrogen content (Nmin) at the beginning of the season and was assessed exemplarily for wheat and maize. Since 2020 a mandatory soil Nmin analysis for each crop on a representative field is required in Germany in zones characterized by increased nitrate concentrations in the groundwater, encompassing approximately 28 % of the arable land. However, soil analysis is time-consuming, costly, and labor-intensive and requires further optimization beyond the current practice.In this study, wheat fields in 2018 and 2019 and maize fields in 2018 were sampled in a grid pattern in spring, and the soil nitrate-N content was determined in 30 cm layers down to 60 cm soil depth in 11 fields and further down to 90 cm soil depth in two of the fields. For each single and the combined soil depths, all fields could be sampled with a deviation of less than 10 kg nitrate-N ha−1 with only two soil samples. Overall, the reduced field-specific soil sampling strategy proved advantageous compared to crop-specific, regionally representative Nmin values offered by the official advisory authorities based on multiple averaged field investigations with an increased sampling intensity of 16 samples per field. Further, the reduced field-specific soil sampling strategy delivered more precise Nmin values by 11.2 kg nitrate-N ha−1 for wheat fields and slightly less precise values by 4.8 kg nitrate-N ha−1 for maize fields. The reduced field-specific soil sampling has great potential to reduce analysis and soil sampling costs. Nitrogen fertilization experiments supported the usefulness of the new simplified Nmin strategy. Multispectral in-season satellite imagery from Sentinel-2 could not adequately capture the spatial nitrate-N level differences and confirms soil samplings needs early in the season.Because most farmers base their fertilization strategy on regionally crop-specific aggregated Nmin values delivered by the official advisory system, we consider a simplified strategy to be more indicative of the field-specific soil Nmin status, which is eased by a markedly reduced sampling frequency and further simplifies the analysis by aggregating the separately analyzed soil depths to only one single depth. Further, currently available simplified on-farm analyses of the soil nitrate content allow for conducting more intensive field-specific soil Nmin analysis, thus contributing to improved nitrogen demand management and decreasing adverse environmental effects.

A Computer-Vision-Based Approach for Nitrogen Content Estimation in Plant Leaves

Nitrogen is an essential nutrient element required for optimum crop growth and yield. If a specific amount of nitrogen is not applied to crops, their yield is affected. Estimation of nitrogen level in crops is momentous to decide the nitrogen fertilization in crops. The amount of nitrogen in crops is measured through different techniques, including visual inspection of leaf color and texture and by laboratory analysis of plant leaves. Laboratory analysis-based techniques are more accurate than visual inspection, but they are costly, time-consuming, and require skilled laboratorian and precise equipment. Therefore, computer-based systems are required to estimate the amount of nitrogen in field crops. In this paper, a computer vision-based solution is introduced to solve this problem as well as to help farmers by providing an easier, cheaper, and faster approach for measuring nitrogen deficiency in crops. The system takes an image of the crop leaf as input and estimates the amount of nitrogen in it. The image is captured by placing the leaf on a specially designed slate that contains the reference green and yellow colors for that crop. The proposed algorithm automatically extracts the leaf from the image and computes its color similarity with the reference colors. In particular, we define a green color value (GCV) index from this analysis, which serves as a nitrogen indicator. We also present an evaluation of different color distance models to find a model able to accurately capture the color differences. The performance of the proposed system is evaluated on a Spinacia oleracea dataset. The results of the proposed system and laboratory analysis are highly correlated, which shows the effectiveness of the proposed system.

YIELD OF WINTER BARLEY DEPENDING ON THE FERTILIZER SYSTEM

The highest and most stable grain yields of winter barley depend on the possibility of using the variety of soil and climatic conditions of cultivation at the maximum level, as well as the ability to overcome adverse meteorological factors that impair plant growth and development. Therefore, new varieties must be characterized by a complex system of biochemical, physiological and economically valuable traits and properties that ensure adaptability to specific growing conditions. In recent years, climate change has become apparent in the central forest-steppe of Ukraine. Autumn and spring periods are often accompanied by drought, air storms. Precipitation is uneven, which is typical for the zone of unstable moistu. Winter barley can give high grain yields only on fertile soils and for the application of a sufficient amount of fertilizers. Therefore, in modern intensive technologies, the use of mineral fertilizers has an important place. It is especially important to carry out nitrogen fertilization of crops, which should be moderate in autumn and during tillering and the formation of elements of the yield structure. Plants assimilate nitrogen most intensively during the period of active growth - from the spring tillering phase to the heading phase. Introduction of diammofosk N10P26K26 + N34 for top dressing in the phase of the beginning of tillering + N46 the beginning of the emergence of plants into the tube under pre-sowing cultivation for growing winter barley winter barley plants and foliar feeding with urea at a dose of N8 + microfertilizer Ecolist at a rate of 4,0 l/ha contributed to the opportunity to obtain grain yield of winter barley varieties Atlant Mironovsky at the level of 6,81 t/ha, Paso variety – 7,29 t/ha, which is more for the control plots without fertilization, by 4,97-5,23 t/ha.

Using Linear Regression, Random Forests, and Support Vector Machine with Unmanned Aerial Vehicle Multispectral Images to Predict Canopy Nitrogen Weight in Corn

The optimization of crop nitrogen fertilization to accurately predict and match the nitrogen (N) supply to the crop N demand is the subject of intense research due to the environmental and economic impact of N fertilization. Excess N could seep into the water supplies around the field and cause unnecessary spending by the farmer. The drawbacks of N deficiency on crops include poor plant growth, ultimately reducing the final yield potential. The objective of this study is to use Unmanned Aerial Vehicle (UAV) multispectral imagery to predict canopy nitrogen weight (g/m2) of corn fields in south-west Ontario, Canada. Simple/multiple linear regression, Random Forests, and support vector regression (SVR) were established to predict the canopy nitrogen weight from individual multispectral bands and associated vegetation indices (VI). Random Forests using the current techniques/methodologies performed the best out of all the models tested on the validation set with an R2 of 0.85 and Root Mean Square Error (RMSE) of 4.52 g/m2. Adding more spectral variables into the model provided a marginal improvement in the accuracy, while extending the overall processing time. Random Forests provided marginally better results than SVR, but the concepts and analysis are much easier to interpret on Random Forests. Both machine learning models provided a much better accuracy than linear regression. The best model was then applied to the UAV images acquired at different dates for producing maps that show the spatial variation of canopy nitrogen weight within each field at that date.

OPTIMIZATION OF NITROGEN MINERAL FERTILIZATION OF AGRICULTURAL CULTURES BY THE PARAMETERS OF THE INTENSITY OF THE NITROGEN FIXATION AND DENITRIFICATION PROCESSES

Objective. Investigate the performance of the nitrogen fixation and process of N-N2O loss un-der the cultivation of potatoes and peas on the leached chornozem under various mineral agrarian backgrounds and the use of microbial preparations and to determine the ecological compromise normal rate of mineral nitrogen, under which the emission losses of nitrogen compounds will not exceed the intake of “biological” nitrogen in agrocenoses. Methods. Field experiment, gas chroma-tographic. Results. Studies of the activity of nitrogen fixation and N2O emission in situ in potato and pea agrocenoses using different rates of mineral fertilizers and microbial preparations, with subsequent calculations of the parameters of intake of the “biological” nitrogen and emission loss-es of the element indicate the possibility of determining the conditions (doses of mineral nitrogen) for which equality between profit and non-productive expenditure of the nitrogen balance is achieved. This amount of mineral nitrogen can be considered environmentally permissible, its ex-cess is undesirable due to a decrease in the intake of “biological” nitrogen and increased activity of the denitrification process. For potatoes grown on leached chornozem, environmentally permis-sible nitrogen fertilizer rate should be considered as 80 kg/ha, for peas — 60 kg/ha. The use of mi-crobial preparations in the cultivation of crops promotes an increase in the range of environmen-tally permissible normal rates of mineral nitrogen due to the formation of conditions under which the bacterization of plants require more nitrogen compounds to ensure a constructive metabolism, which additionally to increased nitrogen fixation activity is accompanied by an increase in the level of consumption of mineral nitrogen in the soil. At the same time, the activity of biological denitrifi-cation becomes reduced. Based on the obtained parameters, a model of optimization of nitrogen mineral fertilization of agricultural cultures was developed. Conclusion. It is advisable to deter-mine the ecologically permissible normal rates of mineral nitrogen fertilization of crops by the per-formance indices of the nitrogen fixation process and N-N2O losses. In this case, the emission losses of nitrogen compounds should not exceed the levels of intake of biologically bound nitrogen in ag-rocenoses.

Orientation of processes of biological nitrogen transformation in winter rye agroecosystems under different levels of fertilization background

Aim. To determine physiologically expedient rates of mineral nitrogen in winter rye production on sod-podzol- ic soils based on the orientation of the processes of biological nitrogen transformation in the plants rhizosphere. Methods. Field studies, gas chromatography determination of potential nitrogen fi xation activity and potential emissions of N 2 O. Results. The results obtained have demonstrated that the rates of mineral nitrogen, not ex- ceeding 60 kg/ha, can be considered physiologically expedient for winter rye production on sod-podzolic soils. Under the application of microbial preparation Diazobakteryn, there is a higher physiological need of plants for nitrogen, which allows increasing the rates of nitrogen fertilizers up to 90 kg/ha. Conclusions. The orienta- tion of the processes of biological nitrogen transformation in the root zone of plants is a reliable indicator of determining the appropriateness of nitrogen fertilization of crops.

Interrelationships among oilseed rape (Brassica napus L.) grain yield and weed growth under different nitrogen levels

Management of nitrogen fertilization in crops is one of the most impor- tant components of integrated weed management. A two-year field experiment was con- ducted to determine the direct effects of wild mustard aboveground biomass and N con- tent of wild mustard on oilseed rape yield. A set of factorial treatments was arranged in a randomized complete block design with four replications. Treatments were various wild mustard densities (0, 10, 20, 30, and 40 plant m -2 ) and nitrogen (N) rates (0, 50, 100, 150, and 200 kg N ha -1 ). Increased wild mustard densities from 10 wild mustard m -2 caused a decrease of 27% in oilseed rape N content of shoot. Increase in nitrogen fertilizer caused an increase in N content of oilseed rape shoot up to 150 kg N ha -1 , but no significant difference was found between 150 (0.88%) and 200 (0.89%) kg N ha -1 . Correlation analysis showed that there was a negative significant correlation between oilseed rape grain yield and weed biomass (r=-0.60, p:0.05) and weed nitrogen content (r=-0.81, p:0.01). Path analysis showed a highly negative significant direct effect (direct path: - 0.88, p:0.01) between weed biomass and oilseed rape grain yield. Correlation and path analyses indicated that the main factor which could cause oilseed rape yield loss was weed biomass and the second factor was N content in wild mustard. Article history:

Comparison of crop canopy reflectance sensors used to identify sugarcane biomass and nitrogen status

Canopy reflectance sensors are useful tools for guiding nitrogen fertilization in crops. However, studies of sugarcane comparing the efficiency of different devices for determining crop parameters are scarce. The objective of this study was to compare the performance of canopy sensors in detecting sugarcane variability. Four nitrogen (N) rate experiments were conducted (plots), along with biomass sampling, chlorophyll meter readings and leaf N concentration determination in another four fields by canopy sensor readings guided samplings. The examined canopy sensors were GreenSeeker and two Crop Circle models (ACS-210 and ACS-430), which allowed the calculation of different normalized difference vegetation index (NDVI) configurations. Neither of the canopy sensors showed a correlation with the obtained chlorophyll meter readings (SPAD) or leaf N content within the fields, while high correlations with above-ground biomass were found, indicating that the plant population and vigor interfered with the canopy sensor readings. The devices showed similar suitability in terms of N rate differentiation and correlations with crop parameters. However, the NDVI calculated from the Crop Circle ACS-430 sensor using a red-edge waveband (NDRE) showed the best results, displaying the greatest range of measured values and the highest sensitivity as a biomass predictor. Regardless of the canopy sensor and wavebands used, all of the analyzed sensors proved to be good tools for identifying the variability of crop development in sugarcane fields.

Optical Sensor‐Based Algorithm for Crop Nitrogen Fertilization*

Nitrogen (N) fertilization for cereal crop production does not follow any kind of generalized methodology that guarantees maximum nitrogen use efficiency (NUE). The objective of this work was to amalgamate some of the current concepts for N management in cereal production into an applied algorithm. This work at Oklahoma State University from 1992 to present has focused primarily on the use of optical sensors in red and near infrared bands for predicting yield, and using that information in an algorithm to estimate fertilizer requirements. The current algorithm, “WheatN.1.0,” may be separated into several discreet components: 1) mid‐season prediction of grain yield, determined by dividing the normalized difference vegetative index (NDVI) by the number of days from planting to sensing (estimate of biomass produced per day on the specific date when sensor readings are collected); 2) estimating temporally dependent responsiveness to applied N by placing non‐N‐limiting strips in production fields each year, and comparing these to the farmer practice (response index); and 3) determining the spatial variability within each 0.4 m2 area using the coefficient of variation (CV) from NDVI readings. These components are then integrated into a functional algorithm to estimate application rate whereby N removal is estimated based on the predicted yield potential for each 0.4 m2 area and adjusted for the seasonally dependent responsiveness to applied N. This work shows that yield potential prediction equations for winter wheat can be reliably established with only 2 years of field data. Furthermore, basing mid‐season N fertilizer rates on predicted yield potential and a response index can increase NUE by over 15% in winter wheat when compared to conventional methods. Using our optical sensor‐based algorithm that employs yield prediction and N responsiveness by location (0.4 m2 resolution) can increase yields and decrease environmental contamination due to excessive N fertilization. *Contribution from the Oklahoma Agricultural Experiment Station.

A mathematical model for nitrogen demand quantification and a link to broccoli ( Brassica oleracea var. italica) glutamine synthetase activity

Determination of crop nitrogen requirement is at the basis of crop nitrogen fertilizer recommendation. This study aimed at determining the nitrogen demand of broccoli plants ( Brassica oleracea var. italica). A mathematical model predicting nitrogen demand was developed and successively tested in an experiment involving a broccoli cultivar at four stages of growth (15; 30; 45; and 60 days after transplanting), in six complete nutrient solutions differing only by their nitrogen rates. The daily critical nitrogen demand was bell-shaped with its maximum at 30 days after transplanting. This pattern paralleled the time course of broccoli growth rate. The critical nitrogen rates of supply were 100 mg l −1 N from the day of transplantation until 30 days, and 175 mg l −1 N from 30 days until 60 days. Any positive or negative deviation from these critical rates of supply led to excessive or deficient tissue nitrogen contents, respectively, which in turn resulted in significant reductions of growth rate. Unlike the cases where nitrogen was non-limiting, root glutamine synthetase activity was linearly correlated to nitrogen deficit rate ( R 2=0.99) under limiting nitrogen conditions, suggesting that under such conditions, glutamine synthetase activity is under the developmental control of nitrogen demand.

Genetic Structure of Acetobacter diazotrophicus Populations and Identification of a New Genetically Distant Group

A total of 55 isolates of Acetobacter diazotrophicus recovered from diverse sucrose-rich host plants and from mealybugs associated with sugarcane plants were characterized by the electrophoretic mobilities of 12 metabolic enzymes. We identified seven different electrophoretic types (ETs), six of which are closely related within a genetic distance of 0.195 and exhibit high DNA-DNA homology. The seventh ET was largely divergent, separated at a genetic distance of 0.53, and had only 54% DNA homology to the reference strain. Strains corresponding to ET 7 could represent a distinct nitrogen-fixing species of the genus Acetobacter. More genetic diversity was found in isolates from Brazil than in those from Mexico, probably due to the very different crop nitrogen fertilization levels used.