*5.1. Nitrogen Use Efficiency—Limiting Factors*

The most important task for a farmer is to establish a hierarchy of factors affecting the yield gap in a particular field and recognizing their depth. Irrespective of the climatic zone, the plant growth rate and development of yield components depend on the supply of N and its use efficiency [38]. Nitrogen use efficiency (NUE) defines the amount of the main product, for example, seeds, grain, roots, tubers, per unit of supplied N [123]. This N index is composed of two sub-units, i.e., nitrogen uptake efficiency (NUtE) and nitrogen utilization efficiency (NUtE), presented as

$$\text{NUE} = \text{NUPE} \times \text{NUE} \tag{19}$$

The simplified interpretation of the first part of this equation, frequently used by crop breeders, mainly focuses on the amount of soil available nitrogen, i.e., to the low- and high- N input growth environment [124]. In fact, the amount of available N is a strong factor discriminating plant crop genotypes [125]. Nitrogen uptake and its subsequent transformation into plant biomass, i.e., NUtE, depends both on the physiological potential of a plant to take up N from its soil resources, and on soil factors limiting the rate of its uptake and subsequent utilization by a plant [113]. The spatial variability of yield clearly indicates that the amount of N taken up by plants of the same cultivar, i.e., having an identical yielding potential, is also spatially variable. Plants suffering from an N shortage due to their lower supply during the cardinal stages of yield formation are not unable to capture the same amount of solar energy compared to those growing in conditions of ample water and N supply. As a result, these plants are not capable of achieving the rate of growth as determined by the supply of light energy [126]. The ex-post formulated questions are: (i) at what stage of crop plant growth does the yield formation become limited by a shortage of N? (ii) what is the reason for the insufficient N uptake? The first question has been thoroughly discussed in Part 4. of this review. The second question should focus the farmer's attention on factors pertaining to the plant potential at a particular stage of its growth to access water and nutrient resources.

#### *5.2. Diagnostic Tools for the In-Season and Spatial Yield Gap Control*

The recognition of the yield gap and its size requires an implementation of a set of analytical tools with a capacity to make a reliable diagnosis of factors that limit plant growth and yield. A significant improvement in NUE is possible provided there is a reliable quantification of soil characteristics limiting both N uptake and its utilization by the currently grown plant. Hence, a single field is considered a basic unit in any diagnostic procedure.

The key characteristic of the yield of a currently grown crop is its spatial variability (Figure 7). The hierarchy of factors decisive for NUE is well recognized, but not always taken into account by farmers and their advisors. The primary tasks, aimed at an improved strategy for spatial N management, are to polygonize the field based on:


It is necessary to create a broad set of zonation maps with respect to soil and crop characteristics to ge<sup>t</sup> an operational tool to establish homogenous field production units (HFPUs) [127,128]. Therefore, the soil water capacity and its availability to the currently grown crop determine the first criterion of the field zonation. The primary factor affecting the diffusion of ions toward the plant root in the soil is the content of available water [50,58]. This factor shows a strong spatial and vertical variability within the growing season, significantly affecting crop growth at cardinal stages of yield component formation [129]. As discussed in Part 3, the amount of available water is defined by the content of colloids and soil structure. Hence, the main reason for existing variabilities in the available water content is the content of mineral colloids. The primary data can be collected using the classic diagnostic procedures of soil analysis. The working out of zonation maps requires the implementation of geostatic methods [130,131]. The advantage of the classic methods of basic soil characteristic determination is the necessity to analyze water and nutrient resources present both in the topsoil and in the sub-soil which is rooted by a currently grown plant [80,120].

**Figure 7.** Spatial variability in winter oilseed rape yield expressed in cereal units (source: [128]).

The crop plant requirement for Nf is the key in-season nutritional factor, responsible for the development and status of yield components. The Nf dose can be calculated based on two characteristics of crop canopy:


A sequential determination of the N content along the growing season of a plant is a primary tool for its N status assessment. As a rule, during the vegetative growth of the seed crop, the proportion of active metabolic tissues (leaves) decreases stage-by-stage with respect to structural ones (stem). Consequently, the total N concentration in plant tissues decreases during vegetative growth, but its content in the plant progressively increases, reaching the highest value just before the onset of flowering (CK2). The temporal variability in relationships between crop dry matter biomass and N concentration is described by the following set of equations [132]:

(1) Nc—the critical N concentration, % or g N kg−<sup>1</sup> DM

$$\mathbf{N}\_{\mathbb{C}} = \mathbf{a} \mathbf{W}^{-\mathbf{b}} \tag{20}$$

(2) NNI—Nitrogen nutrition index,

$$\text{NNI} = \text{N}\_{\text{a}} / \text{N}\_{\text{c}} \tag{21}$$

where: W—crop biomass, t ha−1; a and b—estimated parameters.

The Nc curve is expressed as a power function, but its parameters are both crop and growth condition specific. As reported by Song et al. [133], an Nc based only on rice leaf dry matter was expressed as Nc = 1.96LDM−052. The in-season crop N nutritional status can be evaluated as proposed by Chen et al. [134] for winter wheat based on three classes:


As discussed in Part 4, the yield is the outcome of the efficiency of crop production factors. A major characteristic of a crop plant is its time variability in requirements for water, nitrogen, and nutrients responsible for the efficiency of both key growth factors. In-season evaluation of plant nutritional status relies on plant destructive sampling and nutrient concentration determination in the lab. The key disadvantages of classic diagnostic methods are:

	- (a) uniform N fertilizer rate application, hardly related to the real, i.e., spatial variability in plant requirements for N,
	- (b) low efficiency of applied nitrogen,

A significant increase in NUE requires the implementation of new diagnostic tools, capable of quantifying a crop plant requirement for N in real-time (a defined stage of plant development) and taking into account spatial differences in the productivity of field homogenous units. There has been considerable technological progress in developing different sorts of non-invasive instruments of potential use in plant nutritional status determination [135–137]. Remote sensing is a technique that offers a broad set of effective diagnostic tools to meet both production and environmental objectives. All spectral techniques rely on the plant's ability to absorb and simultaneously reflect solar radiation. Remote-sensing techniques can make a rapid assessment of plant biomass, leaf area index, nitrogen content, chlorophyll content, and finally yield [138]. The information capacity of hyper- and multi-spectral imagery is several times larger as compared to any classical diagnostic tool.

Based on the spectral imagery of a field, it is possible to create a zonal map of a temporary crop N status. The selection of the most reliable spectral indices depends on the sensitivity of spectral bands to both the total N course during plant growth (Nitrogen Dilution Curve—Nc) and canopy structure (biomass, density, N concentration). It has been confirmed that the intensity of solar radiation reflectance in visible light (waveband 400 to 720 nm) is negatively correlated with leaf N content, while NIR reflectance is positively correlated with leaf N content and/or crop biomass [139]. The Normalized Difference Vegetation Index (NDVI) is the most frequently used diagnostic tool for the N content and crop biomass determination [140–142]. In fact, NDVI allows a reliable diagnosis of N status in cereals only during the early stages of growth. This index reaches saturation status at dense canopies [143,144]. This weakness has been recently overcome by developing a new set of Vegetable Spectral Indices (VIs) worked out on bands lying in other spectral regions, including the red-edge region (700–740 nm). Scientific reports have published data on VIs which are capable of predicting an LAI extending from 0 to 6 [145].
