it is the knowledgeable thought about banana nutrient management

1. Sampurna Nand Singh
BAC/M/HORT-F/590/18-19

2. Introduction
Principles of Precision nutrient Management
Steps and approaches in Precision nutrient
Management
Research Findings
Challenges in Precision nutrient management
Conclusion
Outline

3. Introduction
 The precise nutrient management is the science of using advanced,
innovative, site-specific technologies of applying ‘right-input’ at ‘right
time’ in ‘right-amount’ at ‘right-place’ and in ‘right-manner’ to
manage spatial and temporal variability in inherent nutrient supply
from soil. (Jin and Jiang, 2002).
 To enhance productivity, and profitability of agricultural production
systems.
To conserving natural resources efficiency.
 To synchronization in plant demand and soil supply.
 In Indian context is still in infancy stage.
 Approach of sustainable Agriculture

4. Banana crop is heavy feeder of nutrients. It’s roots
spread superficially and absorb large amounts of
nutrients from the soil.
Proper management of nutrients in banana crops
leads to higher yield. The essential nutrients are
supplied through different fertilizer combinations
which vary with variety and climatic conditions.
Proper nutrient supply and management ensures
adequate nutrient to plants to avoid deficiency or
toxicity. It also stimulates proper shoot and root
growth in plants.

5. Deterioration of soil physical health
Low nutrient use efficiencies
Decline in soil organic matter
Emergence of multi-nutrient deficiencies
Water quality deteriorations
Fruit quality deterioration
About 60% of the world’s arable lands have mineral deficiencies or
elemental toxicity problems (Pathak and Nedwell, 2011).
Issues with traditional approaches

6.  Feeding banana crop needs
 Understanding nutrient dynamics
 Leaf and soil test based fertilizer recommendations in banana
 Balanced use of nutrients sources (indigenous nutrient sources)
 Locally-adapted nutrient best management practice tailored to the
field- and season-specific needs for a crop
 Apply optimum nutrient to overcome deficiency and replace nutrient
removed with crop harvest
Principles of Precision Nutrient Management in banana

7. • Estimation of spatial and temporal variability in soil
fertility
• Develop of semi- variogram
• Map generation using interpolation methods (kriging)
• Estimation of optimum nutrient requirement of
banana
• Software based decision supporting tools (GPS, GIS)
• Fertilizer application
Steps involved in precision nutrient management

8. Soil Sample
Analysis
Tissue Nutrient
Status
Remote sensing
and Sensor based
approach
Yield Map
based approach
Spatial variability in
Soil and crop behaviour
Nutrient requirement
Fertilizer Application

9. • Success depends on the assessment of spatial variability
• Mapping to identify the nutrient constraint
• Soil sample collected at regular interval with geo-
referencing using GPS
• Creation of spatial variability maps using interpolation
technique in GIS platform
Estimation of spatial variability in Soil Fertility
Location of grid sampling in banana orchard

10. Tissue analysis
• Nutrient content analysis of plant tissue generally leaf
• Comparison with reference values (critical concentrations)
• Allow to evaluate plants response to specific treatments
Difficulties
• Strongly influenced by leaf age
• Interactions involving nutrient absorption and translocation
Plant nutrient status diagnosis

11. Plant tissues sampling guideline for banana crops
Crop Index tissues Growth stage
Banana Petiole of 3rd open leaf
from apex
Bud differentiation stage

12. Nutrient Banana
(Robusta)
N (%) 1.67-3.43
P (%) 0.12-0.21
K (%) 2.28-4.14
Ca (%) 0.48-1.70
Mg (%) 0.33-0.58
S (%) 0.03-0.18
Fe (ppm) 53-196
Mn (ppm) 112-417
Zn (ppm) 8-38
Cu (ppm) 10-32
Optimum leaf nutrient concentration in Banana
Usha et al., 2015

13.  Use satellite- based sensors or cameras on
board small aircraft
 Detect light reflectance, hyperspectral
signature, ultra sound etc
Remote Sensing

14. • Application of hyperspectral analysis for nutrient
status diagnosis of crop based on reflectance or
fluorescence measurement.

15. Yield map based approach
 Amount of nutrient taken up by crop is directly related to yield
 Yields are location and season specific-depends on climate, cultivar
and management
 Geo-referencing of obtained yield using GPS
 Spatial variability maps created by combining the location
information of the specific block or grid

16.  Based on crop removal
 Considering spatial variability of soil status
 Only based on soil testing, has limited applicability owing to
large root distribution, perennial habit, rootstock effect and
differential fruiting behaviour
 Both soil and leaf analysis should be use
 Computer based decision support tools or interactive
software for site-specific fertilizer prescriptions
Establishment of fertilizer requirement

17. Source
• Chemical fertilizer alone negatively impact soil fertility by affecting soil
microbial balance
• Combination of both chemical and organic fertilizers to improve soil
fertility and increase nutrient-use efficiency
Method
• Fertigation: Fertilizers application with irrigation water (drip irrigation)
directly in the root zone
• It may improve nutrient efficiency by applying them closer to when
the plant needs them
• it could conceivably reduce leaching or denitrification (gaseous)
losses of nitrogen and lower the luxury uptake of nutrients by plants.
 Foliar spray: Foliar application of nutrients provides quick and
effective augmentation of nutrients and may prevent hidden hunger
when properly timed.
Application of fertilizers

18. Soil Application Fertigation
Nitrogen 30-50 95
Phosphorus 20 45
Potassium 50 80
• Secondary and micro-nutrients are more amenable to foliar
feeding owing to smaller crop requirement, but sprays of N,P and
K have also been known to boost fruit bearing stage.
Fertilizer use efficiency

19. International Journal of Agriculture and Environmental Research
ISSN: 2455-6939
Volume:03, Issue:03 "May-June 2017"
NUTRIENT USE EFFICIENCY AS INFLUENCED BY IRRIGATION AND
NUTRIENT MANAGEMENT IN BANANA UNDER PRECISION FARMING
1*G. J. SHIMI, 2K. R. SHEELA
1Ph.D. Scholar, Department of Agronomy, College of Agriculture, Vellayani, Thiruvananthapuram-695522, Kerala, India
2 Professor, Department of Agronomy, College of Agriculture, Vellayani, Thiruvananthapuram-695522, Kerala, India
Case Study 1
Shimi et al. (2017)
Objective
 To study the effect of irrigation and nutrient management through
fertigation and foliar nutrition on nutrient use efficiency (NUE) in
banana under precision farming.

20.  Requirement of water through drip (volume in litres /plant/day) was
computed using the following relationship based on the pan evaporation data.
Measuring of water requirement of banana through drip
irrigation

21. Nutrient Use Efficiency

22. Treatment detail Nitrogen
I Year II Year
Nutrient sources & irrigation
N1- Soil application of full dose of nutrients with basin irrigation 13.50 14.20
N2- Soil application of full dose of nutrients with drip irrigation 13.70 13.26
N4- Soil application of 100 % P as rock phosphate + fertigation with 60 % N and K
as urea and MOP
18.38 19.71
N5- Fertigation of 60 % RDN as 10-10-10, urea and Sulphate of Potash (SOP) 18.04 18.36
N6- Fertigation of 60 % RDN as 13-0-45, 0-0-50 and DAP 13.15 16.19
SEm 0.862 0.832
CD (0.05) 2.814 2.713
Foliar nutrition
S1- Water spray 13.26 13.85
S2- Foliar application of 19-19-19 @ 0.50 % (2, 4 and 6 MAP) 16.29 16.92
S3- Bunch spray + 2 % SOP (after complete bunch emergence and 3 weeks AFA) 16.51 18.26
SEm 0.510 0.296
CD (0.05) 1.507 0.875
Effect of nutrient sources, irrigation and foliar nutrition on nitrogen
use efficiency of major nutrients, kg kg-1

23. Treatment detail Phosphorus
I Year II Year
Nutrient sources & irrigation
N1- Soil application of full dose of nutrients with basin irrigation 35.19 40.60
N2- Soil application of full dose of nutrients with drip irrigation 35.70 34.55
N4- Soil application of 100 % P as rock phosphate + fertigation with 60 % N and K
as urea and MOP
28.75 30.82
N5- Fertigation of 60 % RDN as 10-10-10, urea and Sulphate of Potash (SOP) 46.97 48.24
N6- Fertigation of 60 % RDN as 13-0-45, 0-0-50 and DAP 36.65 43.70
SEm 1.949 1.450
CD (0.05) 6.358 4.730
Foliar nutrition
S1- Water spray 31.36 33.90
S2- Foliar application of 19-19-19 @ 0.50 % (2, 4 and 6 MAP) 38.76 41.65
S3- Bunch spray + 2 % SOP (after complete bunch emergence and 3 weeks AFA) 39.84 43.20
SEm 1.424 1.482
CD (0.05) 4.201 4.373
Effect of nutrient sources, irrigation and foliar nutrition on phosphorus use
efficiency of major nutrients, kg kg-1

24. Treatment detail potash
I Year II Year
Nutrient sources & irrigation
N1- Soil application of full dose of nutrients with basin irrigation 8.99 9.46
N2- Soil application of full dose of nutrients with drip irrigation 9.13 8.83
N4- Soil application of 100 % P as rock phosphate + fertigation with 60 % N and K
as urea and MOP
12.24 13.12
N5- Fertigation of 60 % RDN as 10-10-10, urea and Sulphate of Potash (SOP) 12.02 12.23
N6- Fertigation of 60 % RDN as 13-0-45, 0-0-50 and DAP 8.76 10.78
SEm 0.574 0.554
CD (0.05) 1.872 1.807
Foliar nutrition
S1- Water spray 8.84 9.23
S2- Foliar application of 19-19-19 @ 0.50 % (2, 4 and 6 MAP) 10.87 11.29
S3- Bunch spray + 2 % SOP (after complete bunch emergence and 3 weeks AFA) 10.97 12.13
SEm 0.339 0.197
CD (0.05) 1.002 0.582
Effect of nutrient sources, irrigation and foliar nutrition on potash use
efficiency of major nutrients, kg kg-1

25. It could be concluded that application of
nutrients and irrigation water by drip fertigation
and foliar nutrition along with precise
management practices is beneficial for the
efficient use of nutrients by banana.
conclusion

26. International Journal of Chemical Study
Fruit quality of ‘Grand Naine’ (AAA) banana as
influenced by varied components of precision farming
system
Utpal Das and RK Bhattacharyya
P-ISSN: 2349–8528 E-
ISSN: 2321–4902 IJCS
2019; 7(3): 4475-4478
© 2019 IJCS Received:
04-03-2019 Accepted:
06-04-2019
Utpal Das Assam
Agricultural University,
Jorhat, Assam, India
International Journal of Chemical Studies 2019; 7(3): 4475-4478
To study the evaluate the efficacy of the varied
components of precision farming system comprising
drip irrigation, fertigation, micronutrient foliar spray,
at 2, 3, 5 months after planting,
Objective
Case Study 2

27. Treatments Total soluble
solids (oBrix)
Titrable
acidity (%)
Sugar-acid
ratio
Pulp-peel
ratio
T1- Drip irri.+ fert.+ micro. foliar
spray+ bunch spray of SOP + Black
poly. M
23.53 0.32 77.28 2.42
T2- Drip irri.+ fert.+ micro foliar spray+
bunch spray of SOP
22.55 0.31 75.75 2.21
T3- Drip irri.+ferti.+micro. Foliar spray 21.55 0.27 74.75 2.04
T4- drip irri.+ ferti.+ bunch spray of
SOP
21.43 0.28 74.96 2.03
T5- Soil application of region specific
RDF+ flood irri. (control)
20..37 0.26 74.08 1.95
S. Ed. (±) 0.07 0.01 _ 0.03
CD 0.05 0.016 0.2 NS 0.06
Total soluble solids (oBrix), Titrable acidity (%), Sugaracid
ratio, Pulp-peel ratio

28. Treatments Reducing
sugar (%)
Non-reducing
sugar (%)
Total
sugar (%)
T1- Drip irri.+ fert.+ micro. foliar spray+ bunch
spray of SOP + Black poly. M
9.06 15.68 24.73
T2- Drip irri.+ fert.+ micro foliar spray+ bunch spray
of SOP
7.60 15.58 23.48
T3- Drip irri.+ferti.+micro. Foliar spray 7.66 13.87 21.53
T4- drip irri.+ ferti.+ bunch spray of SOP 7.66 13.89 21.55
T5- Soil application of region specific RDF+ flood
irri. (control)
7.43 11.83 19.26
S. Ed. (±) 0.05 0.003 0.15
CD 0.05 0.11 0.006 0.32
Table 2: Reducing sugar (%), Non-reducing sugar (%),
Total sugar (%)
Conclusion: The results of the present experiment revealed that treatment with drip
irrigation, fertigation, micronutrient foliar spray, bunch spray of SOP and black
polyethylene mulching proved to be highly effective in improving the finger quality in
‘Grand Naine’ banana.

29. To studied investigate the response of banana (Musa acuminata L.) cv.
Grand Naine at different levels of nitrogen, phosphorous and
potassium nutrients applications through drip fertigation and black
plastic mulch.
Objective
Case Study 3

30. Treat- ments Bunch weight
(kg)
No of hands
/bunch
Number of
fingers/ hand
Finger length
(cm)
Yield (t ha-1)
FC RC FC RC FC RC FC RC FC RC
T1 (120% RDF
+M)
15.32 16.80 8.00 6.33 18.00 12.67 19.02 11.85 38.30 40.67
T2 (120% RDF) 13.95 15.60 7.00 5.33 16.33 11.33 17.92 11.47 35.12 40.90
T3 (RDF + M) 24.62 19.60 9.33 7.33 23.67 14.00 20.84 14.37 62.66 47.50
T4 (RDF) 20.70 17.77 8.33 6.67 21.00 12.67 19.40 13.17 50.26 42.13
T5 (RDF) 25.43 20.20 9.67 7.67 22.00 15.00 21.55 15.85 64.49 50.07
T6 (80% RDF +M) 21.69 18.20 8.67 7.00 20.00 12.33 19.46 12.60 54.28 45.80
T7 (60% RDF +M) 11.64 16.03 7.33 5.67 17.33 12.00 18.59 11.82 23.83 39.83
T8 (60% RDF) 10.04 14.70 7.00 5.67 16.00 11.33 17.24 11.50 21.47 38.57
Sem ± 1.34 1.14 0.31 0.51 1.01 0.78 0.67 0.58 2.97 2.22
CD 4.48 3.46 0.96 NS 3.08 NS 2.06 1.74 9.03 6.73
Yield & yield attributing characteristics of banana under
different doses of fertigation and plastic mulch treatments

31. NPK content of banana leaf samples in
different treatments
NPK content of banana fruit in different treatments
T5T3
T5T3

32. Treat- ments Pulp Peel
Ratio
TSS (0brix) Reducing
Sugar (%)
Non Reducing
Sugar (%)
Acidity
(%)
T1 (120% RDF +M) FC RC FC RC FC RC FC RC FC RC
T2 (120% RDF) 1.9 1.96 23.10 22.18 13.00 12.48 2.20 2.11 0.25 0.25
T3 (RDF + M) 1.9 1083 22.37 21.47 12.73 12.22 2.35 2.26 0.26 0.30
T4 (RDF) 2.2 2.47 23.73 22.03 13.27 12.47 1.84 1.73 0.25 0.27
T5 (RDF) 2.1 2.24 23.20 21.85 13.10 12.51 1.94 1.86 0.25 0.25
T6 (80% RDF +M) 2.3 2.41 24.10 22.11 13.53 12.45 1.76 1.62 0.24 0.24
T7 (60% RDF +M) 2.1 2.20 23.43 21.56 13.13 12.08 2.12 1.87 0.25 024
T8 (60% RDF) 1.9 1.86 22.77 21.33 12.77 11.96 2.30 2.15 0.29 0.29
Sem ± 1.8 1.78 22.37 20.95 12.57 11.77 2.40 2.28 0.27 0.27
CD 0.93 0.07 0.27 0.26 0.15 0.14 0.03 0.04 0.01 0.02
T1 (120% RDF +M) 0.28 0.24 0.80 0.78 0.45 0.42 0.11 0.13 NS NS
Effect of different fertigation treatments on fruit quality
characteristics of banana crop
Conclusion: Results of the present study showed that both main and ratoon crops, 80
per cent of the recommended fertigation dose (160 N: 48 P: 240 kg plant-1 year-1)
covered with plastic mulch was found to be optimum and economical.

33. To evaluate the effect of Fertigation and Plastic Mulching on
biometrics of Banana crop.
To evaluate the effect of Fertigation and Plastic Mulching on yield
Banana crop.
Objective
Case Study 4

34. Treatments Plant
hight(m)
Plant
girth
(cm)
Plant
canopy(sqm)
Days
taken for
maturity
Number of
finger
/bunch
Weight
of finger
T1 (80% RDF+0.8V of water by drip irri.+ M) 2.40 53.69 4.15 306.85 131.51 215.64
T2 (80% RDF+0.6V of water by drip irri+ M) 1.93 50.90 3.51 321.08 95.46 172.96
T3 (80% RDF+0.8V of water by drip irri.) 1.96 52.14 3.76 313.02 124.30 206.64
T4 (80% RDF+0.6V of water by Drip irri.) 1.66 46.56 3.66 325.8 84.20 170.75
T5 (100%RDF+flood irri.) 1.45 43.83 3.55 336.02 109.50 187.26
CD 0.91 1.28 0.076 10.41 7.61 6.64
SEm 0.03 0.42 0.024 3.76 2.74 2.39
Effect of fertigation and mulch on biometrics of Banana
Treatments 2009-10 2010-11 2011-12 Average yield (t/ha)
T1 94.95 95.15 94.52 94.87
T2 55.69 56.10 55.03 55.61
T3 85.99 86.05 85.60 85.88
T4 49.04 49.70 47.93 48.90
T5 63.68 64.60 68.37 65.55
CD 3.08 3.62 4.41
Sem 1.03 1.21 1.46
C.V(%) 8.72 10.14 12.26
Effect fertigation and mulch on yield of banana (t/ha)

35. Small size of land holdings
Lack of success stories or cost-benefits
studied
Knowledge and technological gap
Heterogeneity of cropping system in India
Lack of local technical expertise
High initial investment
Challenges for precision nutrient management
in India

36.  Precision nutrient management provides an approach for feeding in banana
crops with nutrients as and when needed.
 Precision nutrient management exploits indigenously and spatially available
nutrients within banana orchards requiring differential fertilizer treatments in
patches and has potential to enhance orchard efficiency.
 Variable rate of fertilization using Geo-statistical analysis and GIS-based
mapping can save 38% to 40% fertilizer as compared to the uniform rate
application.
 Advance techniques such as remote sensing, UAV based sensor, mobile
based application has tremendous potential in precision nutrient
management.
Conclusion

37. 37
“In the landscape of extinction, precision is next to
godliness” - Samuel Beckett