Effect of tree leaf N status and N application time on yield and fruit N partitioning of mango

2017 ◽  
pp. 161-166
Author(s):  
D. Hamilton ◽  
C. Martin ◽  
M. Bennet ◽  
M. Hearnden ◽  
C.A. Asis
Keyword(s):  
Application Time ◽  
N Application ◽  
N Partitioning ◽  
Tree Leaf ◽  
N Status ◽  
Leaf N

scholarly journals Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

2020 ◽  
Vol 12 (7) ◽  
pp. 1139
Author(s):  
Rui Dong ◽  
Yuxin Miao ◽  
Xinbing Wang ◽  
Zhichao Chen ◽  
Fei Yuan ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Fluorescence Sensor ◽  
Accurate Estimation ◽  
Growth Stages ◽  
Fluorescence Sensors ◽  
N Application ◽  
N Concentration ◽  
Leaf N Concentration ◽  
N Status ◽  
Leaf N

Nitrogen (N) is one of the most essential nutrients that can significantly affect crop grain yield and quality. The implementation of proximal and remote sensing technologies in precision agriculture has provided new opportunities for non-destructive and real-time diagnosis of crop N status and precision N management. Notably, leaf fluorescence sensors have shown high potential in the accurate estimation of plant N status. However, most studies using leaf fluorescence sensors have mainly focused on the estimation of leaf N concentration (LNC) rather than plant N concentration (PNC). The objectives of this study were to (1) determine the relationship of maize (Zea mays L.) LNC and PNC, (2) evaluate the main factors influencing the variations of leaf fluorescence sensor parameters, and (3) establish a general model to estimate PNC directly across growth stages. A leaf fluorescence sensor, Dualex 4, was used to test maize leaves with three different positions across four growth stages in two fields with different soil types, planting densities, and N application rates in Northeast China in 2016 and 2017. The results indicated that the total leaf N concentration (TLNC) and PNC had a strong correlation (R2 = 0.91 to 0.98) with the single leaf N concentration (SLNC). The TLNC and PNC were affected by maize growth stage and N application rate but not the soil type. When used in combination with the days after sowing (DAS) parameter, modified Dualex 4 indices showed strong relationships with TLNC and PNC across growth stages. Both modified chlorophyll concentration (mChl) and modified N balance index (mNBI) were reliable predictors of PNC. Good results could be achieved by using information obtained only from the newly fully expanded leaves before the tasseling stage (VT) and the leaves above panicle at the VT stage to estimate PNC. It is concluded that when used together with DAS, the leaf fluorescence sensor (Dualex 4) can be used to reliably estimate maize PNC across growth stages.

scholarly journals Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 314
Author(s):  
Andrew Revill ◽  
Vasileios Myrgiotis ◽  
Anna Florence ◽  
Stephen Hoad ◽  
Robert Rees ◽  
...  
Keyword(s):  
Field Experiments ◽  
Process Models ◽  
Agricultural Technologies ◽  
N Application ◽  
Area Index ◽  
Complex Process ◽  
C Cycle ◽  
The Mean ◽  
Leaf N Content ◽  
Leaf N

Climate, nitrogen (N) and leaf area index (LAI) are key determinants of crop yield. N additions can enhance yield but must be managed efficiently to reduce pollution. Complex process models estimate N status by simulating soil-crop N interactions, but such models require extensive inputs that are seldom available. Through model-data fusion (MDF), we combine climate and LAI time-series with an intermediate-complexity model to infer leaf N and yield. The DALEC-Crop model was calibrated for wheat leaf N and yields across field experiments covering N applications ranging from 0 to 200 kg N ha−1 in Scotland, UK. Requiring daily meteorological inputs, this model simulates crop C cycle responses to LAI, N and climate. The model, which includes a leaf N-dilution function, was calibrated across N treatments based on LAI observations, and tested at validation plots. We showed that a single parameterization varying only in leaf N could simulate LAI development and yield across all treatments—the mean normalized root-mean-square-error (NRMSE) for yield was 10%. Leaf N was accurately retrieved by the model (NRMSE = 6%). Yield could also be reasonably estimated (NRMSE = 14%) if LAI data are available for assimilation during periods of typical N application (April and May). Our MDF approach generated robust leaf N content estimates and timely yield predictions that could complement existing agricultural technologies. Moreover, EO-derived LAI products at high spatial and temporal resolutions provides a means to apply our approach regionally. Testing yield predictions from this approach over agricultural fields is a critical next step to determine broader utility.

Nitrogen fertiliser alleviates the disorder straighthead in Australian rice

2006 ◽  
Vol 46 (8) ◽  
pp. 1077 ◽  
Author(s):  
B. W. Dunn ◽  
G. D. Batten ◽  
T. S. Dunn ◽  
R. Subasinghe ◽  
R. L. Williams
Keyword(s):  
Plant Growth ◽  
Growth And Yield ◽  
High Nitrogen ◽  
Physiological Disorder ◽  
N Application ◽  
Nitrogen Fertiliser ◽  
Eastern Australia ◽  
Growing Environment ◽  
Nitrogen Rates ◽  
N Status

Straighthead is a ‘physiological’ disorder of rice, the symptoms being floret sterility, deformed florets and panicles and reduced grain yield. Straighthead in rice is difficult to investigate because of its unpredictable occurrence under field conditions. An experiment was conducted in south-eastern Australia in 1996 to investigate the effect of rate and timing of N fertilisation on growth and yield of rice. The presence of straighthead at this location gave a unique opportunity to study the influence of crop N status. This paper reports the influence of N application on straighthead symptoms during this experiment. A significant reduction of straighthead occurred with higher rates of N application. Application of 250 kg N/ha pre-flood, improved plant growth and vigour with subsequent increased uptake and accumulation of S, P, K, Mg, Cu, Mn and Zn in the plant at panicle initiation. The reduction of straighthead at high nitrogen rates may be due to improved uptake of several essential nutrients, and Cu may be a critical nutrient. This study and earlier observations have shown the application of optimal levels of pre-flood nitrogen to achieve grain yields greater than 10 t/ha may reduce straighthead severity in the Australian rice-growing environment. The results in this paper are not presented as recommendations to growers but a contribution to the currently limited literature on straighthead in Australia.

scholarly journals Optimizing Nitrogen Application for Growth and Productivity of Pomegranates

Agronomy ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 366
Author(s):  
Silit Lazare ◽  
Yang Lyu ◽  
Uri Yermiyahu ◽  
Yehuda Heler ◽  
Alon Ben-Gal ◽  
...  
Keyword(s):  
N Uptake ◽  
N Fertilization ◽  
Field Conditions ◽  
Nitrogen Application ◽  
N Application ◽  
Environmentally Responsible ◽  
Irrigation Solution ◽  
Vegetative Indices ◽  
Leaf N ◽  
Usage Efficiency

Quantification of actual plant consumption of nitrogen (N) is necessary to optimize fertilization efficiency and minimize contamination of earth resources. We examined the performance of fruit-bearing pomegranate trees grown in soilless media and exposed to eight N-fertigation treatments, from 5 to 200 mg N L−1. Reproductive and vegetative indices were found to be optimal when 20 to 70 mg N L−1 was supplied. Nitrogen application levels over 70 mg L−1 reduced pomegranate development and reproduction. N uptake in low-level treatments was almost 100% and decreased gradually, down to 13% in 200 mg N L−1 treatment. N usage efficiency was maximized under 20 mg N L−1, in which case 80% to 90% of added N was taken up by the trees. At high N application, its efficiency was reduced with less than 50% utilized by the trees. Leaf N increased to a plateau as a function of increasing irrigation solution N, maximizing at ~15 to 20 mg N g−1. Therefore, analysis of diagnostic leaves is not a valid method to identify excessive detrimental N. The results should be valuable in the development of efficient, sustainable, environmentally responsible protocols for N fertilization in commercial pomegranate orchards, following adaptation and validation to real soil field conditions.

Monitoring leaf nitrogen in wheat using canopy reflectance spectra

2006 ◽  
Vol 86 (4) ◽  
pp. 1037-1046 ◽  
Author(s):  
Yan Zhu ◽  
Yingxue Li ◽  
Wei Feng ◽  
Yongchao Tian ◽  
Xia Yao ◽  
...  
Keyword(s):  
Nitrogen Concentration ◽  
Leaf Nitrogen ◽  
Reflectance Spectra ◽  
Nutrition Status ◽  
Nitrogen Accumulation ◽  
Canopy Reflectance ◽  
Leaf Nitrogen Concentration ◽  
Non Destructive ◽  
N Status ◽  
Leaf N

Non-destructive monitoring of leaf nitrogen (N) status can assist in growth diagnosis, N management and productivity forecast in field crops. The objectives of this study were to determine the relationships of leaf nitrogen concentration on a leaf dry weight basis (LNC) and leaf nitrogen accumulation per unit soil area (LNA) to ground-based canopy reflectance spectra, and to derive regression equations for monitoring N nutrition status in wheat (Triticum aestivum L.). Four field experiments were conducted with different N application rates and wheat cultivars across four growing seasons, and time-course measurements were taken on canopy spectral reflectance, LNC and leaf dry weights under the various treatments. In these studies, LNC and LNA in wheat increased with increasing N fertilization rates. The canopy reflectance differed significantly under varied N rates, and the pattern of response was consistent across the different cultivars and years. Overall, an integrated regression equation of LNC to normalized difference index (NDI) of 1220 and 710 nm of canopy reflectance spectra described the dynamic pattern of change in LNC in wheat. The ratios of several near infrared (NIR) bands to visible light were linearly related to LNA, with the ratio index (RI) of the average reflectance over 760, 810, 870, 950 and 1100 nm to 660 nm having the best index for quantitative estimation of LNA in wheat. When independent data were fit to the derived equations, the average root mean square error (RMSE) values for the predicted LNC and LNA relative to the observed values were no more than 15.1 and 15.2%, respectively, indicating a good fit. Our relationships of leaf N status to spectral indices of canopy reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in wheat. Key words: Wheat, leaf nitrogen concentration, leaf nitrogen accumulation, canopy reflectance, spectral index, nitrogen monitoring

scholarly journals Inoculation and N Fertilization Affect the Dry Matter, N Fixation, and Bioactive Compounds in Sulla Leaves

Agronomy ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 289 ◽  
Author(s):  
Leonardo Sulas ◽  
Giuseppe Campesi ◽  
Giovanna Piluzza ◽  
Giovanni A. Re ◽  
Paola A. Deligios ◽  
...  
Keyword(s):  
Bioactive Compounds ◽  
Dry Matter ◽  
Seed Set ◽  
Natural Habitat ◽  
N Fertilization ◽  
N Fixation ◽  
N Application ◽  
Uninoculated Control ◽  
The Relationship ◽  
Leaf N

Sulla (Sulla coronaria [L.] Medik), a Mediterranean short-lived legume with tolerance to drought-prone environments, requires inoculation outside its natural habitat. Its leaves are appreciated for the bromatological composition and content of bioactive compounds. However, no information is available regarding the distinct effects of inoculation and nitrogen (N) applications on leaf dry matter (DM), fixed N, and bioactive compounds. Sulla leaves were sampled from the vegetative stage to seed set in Sardinia (Italy) during 2013–2014 and leaf DM, N content, and fixed N were determined. Compared to the best performing inoculated treatments, DM yield and fixed N values of the control only represented 8% to 20% and 2% to 9%, respectively. A significant relationship between fixed N and leaf DM yield was established, reaching 30 kg fixed N t–1 at seed set. Significant variations in leaf atom% 15N excess and %Ndfa quantified decreases in leaf N fixation coupled with N application. Moreover, the petiole content of phenolic compounds markedly increased in the uninoculated control, suggesting deeper investigations on the relationship between bioactive compounds and inoculation treatments. Results highlighted substantial variation in DM, N yields, N-fixation ability, and content of bioactive compounds of sulla leaves caused by inoculation and N fertilization.

scholarly journals LEAF TOTAL NITROGEN CONCENTRATION AS AN INDICATOR OF NITROGEN STATUS FOR PLANTLETS AND YOUNG PLANTS OF EUCALYPTUS CLONES

2015 ◽  
Vol 39 (4) ◽  
pp. 1127-1140 ◽  
Author(s):  
Eric Victor de Oliveira Ferreira ◽  
Roberto Ferreira Novais ◽  
Bruna Maximiano Médice ◽  
Nairam Félix de Barros ◽  
Ivo Ribeiro Silva
Keyword(s):  
Total Nitrogen ◽  
Block Design ◽  
Nitrogen Concentration ◽  
Soil N ◽  
Total N ◽  
Chlorophyll Meter ◽  
N Concentration ◽  
Total Nitrogen Concentration ◽  
N Status ◽  
Leaf N

The use of leaf total nitrogen concentration as an indicator for nutritional diagnosis has some limitations. The objective of this study was to determine the reliability of total N concentration as an indicator of N status for eucalyptus clones, and to compare it with alternative indicators. A greenhouse experiment was carried out in a randomized complete block design in a 2 × 6 factorial arrangement with plantlets of two eucalyptus clones (140 days old) and six levels of N in the nutrient solution. In addition, a field experiment was carried out in a completely randomized design in a 2 × 2 × 2 × 3 factorial arrangement, consisting of two seasons, two regions, two young clones (approximately two years old), and three positions of crown leaf sampling. The field areas (regions) had contrasting soil physical and chemical properties, and their soil contents for total N, NH+4-N, and NO−3-N were determined in five soil layers, up to a depth of 1.0 m. We evaluated the following indicators of plant N status in roots and leaves: contents of total N, NH+4-N, NO−3-N, and chlorophyll; N/P ratio; and chlorophyll meter readings on the leaves. Ammonium (root) and NO−3-N (root and leaf) efficiently predicted N requirements for eucalyptus plantlets in the greenhouse. Similarly, leaf N/P, chlorophyll values, and chlorophyll meter readings provided good results in the greenhouse. However, leaf N/P did not reflect the soil N status, and the use of the chlorophyll meter could not be generalized for different genotypes. Leaf total N concentration is not an ideal indicator, but it and the chlorophyll levels best represent the soil N status for young eucalyptus clones under field conditions.

scholarly journals Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Visible Region ◽  
Machine Learning Algorithms ◽  
Hyperspectral Reflectance ◽  
N Content ◽  
Green Leaves ◽  
Leaf N Content ◽  
N Status ◽  
Leaf N

Abstract Nondestructive techniques for estimating nitrogen (N) status are essential tools for optimizing N fertilization input and reducing the environmental impact of agricultural N management, especially in green tea cultivation, which is notably problematic. Previously, hyperspectral indices for chlorophyll (Chl) estimation, namely a green peak and red edge in the visible region, have been identified and used for N estimation because leaf N content closely related to Chl content in green leaves. Herein, datasets of N and Chl contents, and visible and near-infrared hyperspectral reflectance, derived from green leaves under various N nutrient conditions and albino yellow leaves were obtained. A regression model was then constructed using several machine learning algorithms and preprocessing techniques. Machine learning algorithms achieved high-performance models for N and Chl content, ensuring an accuracy threshold of 1.4 or 2.0 based on the ratio of performance to deviation values. Data-based sensitivity analysis through integration of the green and yellow leaves datasets identified clear differences in reflectance to estimate N and Chl contents, especially at 1325–1575 nm, suggesting an N content-specific region. These findings will enable the nondestructive estimation of leaf N content in tea plants and contribute advanced indices for nondestructive tracking of N status in crops.

scholarly journals Response to fertilizer nitrogen and water of post-rainy season sorghum on a Vertisol. 1. Biomass and light interception

1998 ◽  
Vol 131 (4) ◽  
pp. 417-428 ◽  
Author(s):  
T. J. REGO ◽  
J. L. MONTEITH ◽  
PIARA SINGH ◽  
K. K. LEE ◽  
V. NAGESWARA RAO ◽  
...  
Keyword(s):  
Rainy Season ◽  
Andhra Pradesh ◽  
Root Zone ◽  
Growth Period ◽  
Peninsular India ◽  
N Application ◽  
Radiation Coefficient ◽  
Optimum Application ◽  
Main Growth ◽  
Leaf N

In parts of peninsular India, sorghum (Sorghum bicolor L.) is grown during the dry season using water stored in the root zone. The optimum application of nitrogen is difficult to assess because no comprehensive model exists for the interaction of water and N. To explore this system as a basis for modelling in the first instance and ultimately for better management, sorghum (cv. SPH–280) was grown in the post-rainy season at ICRISAT (Andhra Pradesh, India) with and without irrigation and at six rates of nitrogen from zero to 150 kg/ha applied before sowing. The biomass of top components was measured weekly and of roots every 2 weeks. Interception of solar radiation was monitored continuously in all treatments.Leaf expansion was strongly influenced both by water and by N, whereas specific leaf area was almost independent of treatment. In the irrigated treatment, the Biomass Radiation Coefficient (e) for the main growth period was almost independent of N application at 1·3–1·4 g/MJ and was also independent of leaf N. In consequence, the main source of differences in yield was a decrease in radiation interception with decreasing N. In contrast, without irrigation, biomass, yield, e and leaf N were all maximal at 60 kg/ha N.At 33 days after emergence (DAE), root mass was almost independent of N whether water had been applied or not, but was somewhat smaller with irrigation. Later, root, leaf, and panicle mass all responded to N and to water, but stem mass was unresponsive to N with irrigation. There was evidence of translocation from stem to grain in most treatments. With irrigation, a maximum grain yield of 4·8 t/ha was obtained at 150 kg/ha N and without irrigation the maximum was 3·2 t/ha at 90 kg/ha.

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