Effects of winter wheat N status on assimilate and N partitioning in the mechanistic agroecosystem model DAISY

The accurate estimation and timely diagnosis of crop nitrogen (N) status can facilitate in-season fertilizer management. In order to evaluate the performance of three leaf and canopy optical sensors in non-destructively diagnosing winter wheat N status, three experiments using seven wheat cultivars and multi-N-treatments (0–360 kg N ha−1) were conducted in the Jiangsu province of China from 2015 to 2018. Two leaf sensors (SPAD 502, Dualex 4 Scientific+) and one canopy sensor (RapidSCAN CS-45) were used to obtain leaf and canopy spectral data, respectively, during the main growth period. Five N indicators (leaf N concentration (LNC), leaf N accumulation (LNA), plant N concentration (PNC), plant N accumulation (PNA), and N nutrition index (NNI)) were measured synchronously. The relationships between the six sensor-based indices (leaf level: SPAD, Chl, Flav, NBI, canopy level: NDRE, NDVI) and five N parameters were established at each growth stages. The results showed that the Dualex-based NBI performed relatively well among four leaf-sensor indices, while NDRE of RS sensor achieved a best performance due to larger sampling area of canopy sensor for five N indicators estimation across different growth stages. The areal agreement of the NNI diagnosis models ranged from 0.54 to 0.71 for SPAD, 0.66 to 0.84 for NBI, and 0.72 to 0.86 for NDRE, and the kappa coefficient ranged from 0.30 to 0.52 for SPAD, 0.42 to 0.72 for NBI, and 0.53 to 0.75 for NDRE across all growth stages. Overall, these results reveal the potential of sensor-based diagnosis models for the rapid and non-destructive diagnosis of N status.

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Sensitivity of sensor-based nitrogen rates to selection of within-field calibration strips in winter wheat

Crop and Pasture Science ◽

10.1071/cp16380 ◽

2017 ◽

Vol 68 (2) ◽

pp. 101 ◽

Cited By ~ 3

Author(s):

Stanisław M. Samborski ◽

Dariusz Gozdowski ◽

Olga S. Walsh ◽

Peter Kyveryga ◽

Michał Stłpieł

Keyword(s):

Winter Wheat ◽

Optical Sensors ◽

Representative Sample ◽

Stem Elongation ◽

Triticum Aestivum L ◽

Canopy Reflectance ◽

Sample Strip ◽

Vegetative Indices ◽

N Status ◽

Selection Of

Active optical sensors (AOSs) are used for in-season variable-rate application of nitrogen (N). The sensors measure crop reflectance expressed as vegetative indices (VIs). These are transformed into N recommendations during on-site calibration of AOSs—‘familiarising’ the sensors with the crop N status of the representative part of a field. The ‘drive-first’ method is often used by growers to calibrate AOSs. Due to large spatial variation of crop N status within fields, it is difficult to identify the most representative sample strip for AOS calibration. Seven site-years were used to evaluate the sensitivity of sensor-based N prescriptions for winter wheat (Triticum aestivum L.) to selection of sample strips for AOS calibration that fall into extreme, very low or very high values of 95th percentiles of amber normalised difference VI (NDVI) values. A Crop Circle ACS-210 sensor was used to collect canopy reflectance values, expressed as amber NDVI, at the beginning of wheat stem elongation. Our study showed that the sample-strip selection significantly affected sensor-based N prescriptions. The drive-first method may result in under- or over-applications of N and in lower N-use efficiency. One way to overcome this problem is to collect whole field NDVI values during pesticide application before sensor-based N application. The NDVI values from the entire field then can be used to choose the most representative sample strips for AOS calibration.

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Does the Organ-Based N Dilution Curve Improve the Predictions of N Status in Winter Wheat?

Agriculture ◽

10.3390/agriculture10110500 ◽

2020 ◽

Vol 10 (11) ◽

pp. 500

Author(s):

Ke Zhang ◽

Xue Wang ◽

Xiaoling Wang ◽

Syed Tahir Ata-Ul-Karim ◽

Yongchao Tian ◽

...

Keyword(s):

Winter Wheat ◽

High Efficiency ◽

Eastern China ◽

Relative Yield ◽

N Fertilizer ◽

Growth Stages ◽

Dilution Curve ◽

Area Index ◽

N Concentration ◽

N Status

Accurately summarizing Nitrogen (N) content as a prelude to optimal N fertilizer application is complicated during the vegetative growth period of all the crop species studied. The critical nitrogen (N) concentration (Nc) dilution curve is a stable diagnostic indicator, which performs plant critical N concentration trends as crop grows. This study developed efficient technologies for different organ-based (plant dry matters (PDM), leaf DM (LDM), stem DM (SDM), and leaf area index (LAI)) estimation of Nc curves to enrich the practical applications of precision N management strategies. Four winter wheat cultivars were planted with 10 different N treatments in Jiangsu province of eastern China. Results showed the SDM-based curve had a better performance than the PDM-based curve in N nutrition index (NNI) estimation, accumulated N deficit (AND) calculation, and N requirement (NR) determination. The regression coefficients ‘a’ and ‘b’ varied among the four critical N dilution models: Nc = 3.61 × LDM–0.19, R2 = 0.77; Nc = 2.50 × SDM–0.44, R2 = 0.89; Nc = 4.16 × PDM–0.41, R2 = 0.87; and Nc = 3.82 × LAI–0.36, R2 = 0.81. In later growth periods, the SDM-based curve was found to be a feasible indicator for calculating NNI, AND, and NR, relative to curves based on the other indicators. Meanwhile, the lower LAI-based curve coefficient variation values stated that leaf-related indicators were also a good choice for developing the N curve with high efficiency as compared to other biomass-based approaches. The SDM-based curve was the more reliable predictor of relative yield because of its low relative root mean square error in most of the growth stages. The curves developed in this study will provide diverse choices of indicators for establishing an integrated procedure of diagnosing wheat N status, and improving the accuracy and efficiency of wheat N fertilizer management.

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Effect and residual effect of N fertilisation on the N uptake of winter wheat in a long-term field experiment

Acta Agronomica Hungarica ◽

10.1556/aagr.50.2002.4.5 ◽

2002 ◽

Vol 50 (4) ◽

pp. 425-431 ◽

Cited By ~ 1

Author(s):

K. Berecz ◽

I. Németh

Keyword(s):

Winter Wheat ◽

N Uptake ◽

Residual Effect ◽

Brown Forest Soil ◽

Vegetative Organs ◽

Set Up ◽

Fertiliser Use ◽

N Status ◽

Term Field

In wheat production, N fertilisation is one of the most effective agro-technical devices to increase yield and N concentration. In Hungary, fertiliser use, particularly that of N, has dropped dramatically in the last decade. The aim of this experiment was to study the direct and residual effect of N fertilisation on the grain yield and N uptake of winter wheat after 30 years of intensive N fertilisation. A long-term fertilisation experiment was set up on brown forest soil (Eutric Cambisol) with medium N status at Keszthely (Hungary) in 1965. In 1995, the plots were halved. From that year on, half of the plots no longer received N fertiliser, while the other half of the plots was fertilised with increasing N doses. Two years after the treatment modification, no residual effect of long-term intensive N fertilisation (10.44 t N/30 years) could be detected. Under the investigated site conditions, the omission of yearly N fertilisation led to low wheat yields and low N concentrations both in the grains and in the vegetative organs above the uppermost internode.

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Using an Active Sensor to Develop New Critical Nitrogen Dilution Curve for Winter Wheat

Sensors ◽

10.3390/s20061577 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1577 ◽

Cited By ~ 1

Author(s):

Jie Jiang ◽

Cuicun Wang ◽

Yu Wang ◽

Qiang Cao ◽

Yongchao Tian ◽

...

Keyword(s):

Winter Wheat ◽

Field Experiments ◽

Wheat Varieties ◽

Active Sensor ◽

Alternative Approach ◽

Nitrogen Dilution ◽

N Management ◽

N Rates ◽

Non Destructive ◽

N Status

Critical nitrogen (N) dilution curves (CNDCs) have been developed to describe the dilution dynamic of N and to diagnose N status in plants. In this study, to develop a convenient alternative CNDC determination method, four field experiments involving different N rates (0–360 kg N ha-1) and six wheat varieties were performed at different eco-sites from 2014 to 2019. The normalised difference red-edge (NDRE) index extracted from the RapidSCAN CS-45 (Holland Scientific Inc., Lincoln, NE, USA) sensor was used as a driving factor instead of plant dry matter (PDM) to establish a new alternative winter wheat CNDC. The newly developed CNDC was described by the equation Nc = 0.90NDRE−0.88, when NDRE values were ≤ 0.19 and constant Nc = 3.81%, which was independent of the NDRE values. Compared to PDM-derived CNDC (R2 = 0.73) developed with the same dataset, a comparable precision was obtained using NDRE-derived CNDC (R2 = 0.76) and both CNDCs could accurately discriminate wheat N status. Moreover, the NDRE could be inexpensively and rapidly measured using the active sensor. The relationship between NDRE-derived CNDC and grain yield was also analysed to facilitate in-season N management, and the R2 value reached 0.79 and 0.87 at jointing and booting stages, respectively. The NDRE-based CNDC can be used to effectively diagnose wheat N status and as an alternative approach for non-destructive determination of crop N levels.

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In-Season Diagnosis of Winter Wheat Nitrogen Status in Smallholder Farmer Fields Across a Village Using Unmanned Aerial Vehicle-Based Remote Sensing

Agronomy ◽

10.3390/agronomy9100619 ◽

2019 ◽

Vol 9 (10) ◽

pp. 619 ◽

Cited By ~ 4

Author(s):

Zhichao Chen ◽

Yuxin Miao ◽

Junjun Lu ◽

Lan Zhou ◽

Yue Li ◽

...

Keyword(s):

Remote Sensing ◽

Winter Wheat ◽

Unmanned Aerial Vehicle ◽

Farming Systems ◽

Soil Conditions ◽

Small Scale ◽

Smallholder Farmer ◽

Aerial Vehicle ◽

N Management ◽

N Status

Improving nitrogen (N) management of small-scale farming systems in developing countries is crucially important for food security and sustainable development of world agriculture, but it is also very challenging. The N Nutrition Index (NNI) is a reliable indicator for crop N status, and there is an urgent need to develop an effective method to non-destructively estimate crop NNI in different smallholder farmer fields to guide in-season N management. The eBee fixed-wing unmanned aerial vehicle (UAV)-based remote sensing system, a ready-to-deploy aircraft with a Parrot Sequoia+ multispectral camera onboard, has been used for applications in precision agriculture. The objectives of this study were to (i) determine the potential of using fixed-wing UAV-based multispectral remote sensing for non-destructive estimation of winter wheat NNI in different smallholder farmer fields across the study village in the North China Plain (NCP) and (ii) develop a practical strategy for village-scale winter wheat N status diagnosis in small scale farming systems. Four plot experiments were conducted within farmer fields in 2016 and 2017 in a village of Laoling County, Shandong Province in the NCP for evaluation of a published critical N dilution curve and for serving as reference plots. UAV remote sensing images were collected from all the fields across the village in 2017 and 2018. About 150 plant samples were collected from farmer fields and plot experiments each year for ground truthing. Two indirect and two direct approaches were evaluated for estimating NNI using vegetation indices (VIs). To facilitate practical applications, the performance of three commonly used normalized difference VIs were compared with the top performing VIs selected from 59 tested indices. The most practical and stable method was using VIs to calculate N sufficiency index (NSI) and then to estimate NNI non-destructively (R2 = 0.53–0.56). Using NSI thresholds to diagnose N status directly was quite stable, with a 57–59% diagnostic accuracy rate. This strategy is practical and least affected by the choice of VIs across fields, varieties, and years. This study demonstrates that fixed-wing UAV–based remote sensing is a promising technology for in-season diagnosis of winter wheat N status in smallholder farmer fields at village scale. The considerable variability in local soil conditions and crop management practices influenced the overall accuracy of N diagnosis, so more studies are needed to further validate and optimize the reported strategy and consecutively develop practical UAV remote sensing–based in-season N recommendation methods.

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Estimating the Growth Indices and Nitrogen Status Based on Color Digital Image Analysis During Early Growth Period of Winter Wheat

Frontiers in Plant Science ◽

10.3389/fpls.2021.619522 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ben Zhao ◽

Yonghui Zhang ◽

Aiwang Duan ◽

Zhandong Liu ◽

Junfu Xiao ◽

...

Keyword(s):

Winter Wheat ◽

Growth Period ◽

Early Growth ◽

Individual Growth ◽

Growth Stages ◽

Growth Indices ◽

Indirect Methods ◽

N Nutrition ◽

Direct And Indirect Methods ◽

N Status

The non-destructive estimation of plant nitrogen (N) status is imperative for timely and in-season crop N management. The objectives of this study were to use canopy cover (CC) to establish the empirical relations between plant growth indices [shoot dry matter (SDM), leaf area index (LAI), shoot N accumulation (SNA), shoot nitrogen concentration (SNC)], and CC as well as to test the feasibility of using CC to assess N nutrition index (NNI) from Feekes 3 to Feekes 6 stages of winter wheat. Four multi-locational (2 sites), multi-cultivars (four cultivars), and multi-N rates (0–300 kg N ha–1) field experiments were carried out during 2016 to 2018 seasons. The digital images of the canopy were captured by a digital camera from Feekes 3 to Feekes 6 stages of winter wheat, while SDM, LAI, SNA, and SNC were measured by destructive plant sampling. CC was calculated from digital images developed by self-programmed software. CC showed significant correlations with growth indices (SDM, LAI, and SNA) across the different cultivars and N treatments, except for SNC. However, the stability of these empirical models was affected by cultivar characteristics and N application rates. Plant N status of winter wheat was assessed using CC through two methods (direct and indirect methods). The direct and indirect methods failed to develop a unified linear regression to estimate NNI owing to the high dispersion of winter wheat SNC during its early growth stages. The relationships of CC with SDM, SNC and NNI developed at individual growth stages of winter wheat using both methods were highly significant. The relationships developed at individual growth stages did not need to consider the effect of N dilution process, yet their stability is influenced by cultivar characteristics. This study revealed that CC has larger limitation to be used as a proxy to manage the crop growth and N nutrition during the early growth period of winter wheat despite it is an easily measured index.

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Evaluating Two Crop Circle Active Canopy Sensors for In-Season Diagnosis of Winter Wheat Nitrogen Status

Agronomy ◽

10.3390/agronomy8100201 ◽

2018 ◽

Vol 8 (10) ◽

pp. 201 ◽

Cited By ~ 10

Author(s):

Qiang Cao ◽

Yuxin Miao ◽

Jianning Shen ◽

Fei Yuan ◽

Shanshan Cheng ◽

...

Keyword(s):

Winter Wheat ◽

Vegetation Indices ◽

Field Measurements ◽

Triticum Aestivum L ◽

Coefficient Of Determination ◽

Growth Stages ◽

Canopy Reflectance ◽

Red Edge ◽

N Management ◽

N Status

Active crop canopy sensors can be used for non-destructive real-time diagnosis of crop nitrogen (N) status and guiding in-season N management. However, limited studies have compared the performances of two commercially available sensors with three different wavebands: Crop Circle ACS-470 (CC-470) and Crop Circle ACS-430 (CC-430). The objective of this study was to evaluate the performances of CC-470 and CC-430 sensors for estimating winter wheat (Triticum aestivum L.) N status at different measurement heights (40 cm, 70 cm and 100 cm) and growth stages. Results indicated that the canopy reflectance values of CC-470 were more affected by height compared to the CC-430 sensor. The normalized difference red edge (NDRE) and red edge chlorophyll index (CIRE) of CC-430 were stable at the three different measuring heights. The relationships between these indices and the N status indicators were stronger at the Feekes 9–10 stages than the Feekes 6–7 stages for both sensors; however, the CC-430 sensor-based vegetation indices had higher coefficient of determination (R2) values for both stages. It is concluded that the CC-430 sensor is more reliable than CC-470 for winter wheat N status estimation due to its capability of making height-independent measurements. These results demonstrated the importance of considering the influences of height when using active canopy sensors in field measurements.

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