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PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS Agriculture Extension View Point Dr. Muhammad Anjum Ali Director General Agriculture (Extension & AR) Punjab, Lahore

PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

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PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS. Agriculture Extension View Point. Dr. Muhammad Anjum Ali Director General Agriculture (Extension & AR) Punjab, Lahore. FERTILIZER OFFTAKE BY NUTRIENTS PAKISTAN (000 TONS). 79.68%. NFDC Reports. - PowerPoint PPT Presentation

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Page 1: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

PREDICTION MODELS FOR SITE SPECIFIC

RECOMMENDATIONS

Agriculture Extension View Point

Dr. Muhammad Anjum AliDirector General Agriculture

(Extension & AR) Punjab, Lahore

Page 2: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER OFFTAKE BY NUTRIENTS PAKISTAN (000 TONS)

Year N P2O5 K2O Total2010-11 3134 767 32 3933

79.68%

NFDC Reports

Page 3: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER OFFTAKE BY NUTRIENTS PUNJAB (000 TONS)

Year N P2O5 K2O Total2010-11 2231 548 24 2803

79.59

19.550. 85

Page 4: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

CROP USAGE OF FERTILIZER IN PAKISTAN

(000 NUTRIENT TONS)Year Wheat Cotton Sugarcane Rice Maize Others Total

2010-11 1966.5 983.25 314.64 235.98 59 373.64 3933.01

50 %

Page 5: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

TOTAL NITROGEN USE ALL SOURCES

FERTILIZER 000 TONS PERCENTAGE ON NUTRIENT BASISUREA 5765 84.26CAN 595 4.92DAP 1325 7.58NP 335 2.45

MAP 38 0.13NPK 70 0.67

84.26

2.45

Page 6: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

TOTAL PHOSPHORUS USE ALL SOURCES

FERTILIZER 000 TONS PERCENTAGE ON NUTRIENT BASISDAP 1325 78.55SSP 224 5.20TSP 18 1.07NPK 70 2.71MAP 38 2.55NP 335 9.93

78.55

Page 7: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

TOTAL POTASH USE ALL SOURCES

FERTILIZER 000 TONS PERCENTAGE ON NUTRIENT BASISSOP 27 56.02MOP 11 27.39NPK 10 16.60

56.02

Page 8: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER OFF TAKE (000 N/TONS)

Economic Survey of Pakistan 2011-12Economic Survey of Pakistan 2011-12

Page 9: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

USE EFFICIENCY OF DIFFERENT NUTRIENTS

MACRO-NUTRIENTS MICRO-NUTRIENTS

Parameter Use Efficiency (%)

Parameter Use Efficiency (%)

N 40 – 60 Zn 4 – 5

P 20 – 30 B 6 – 8

K 75 – 85 Fe 11 – 15

Page 10: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER USE EFFICIENCY

Long term study conducted by IFA for India, China and Pakistan revealed less grain yield due decline in N use efficiency because of imbalance use of fertilizer nutrients

IndiaChinaPakistan

Kg

Gra

ins

per

Kg

of

N u

sed

Page 11: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

BALANCED USE OF FERTILIZER (Ha)

Crop N Only NPK % Increase

Wheat 2,521 4,120 63

Rice 2,800 4,494 60

Maize 2,110 5,084 14

Sugarcane 56,515 126,334 123

Kg/ha

NFDC Reports

Page 12: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER VALUE

Fertilizer

Annual Consumption (000 Tons)

Value (US $ per Ton)

Total Cost Million US $

Fertilizer Use

efficiency (% age)

Deficit Million US

$

Urea 5,765 425 2,450.12 501,225.6

0

DAP 1,325 515 682.37 25 170.59

Potash 38 595 22.61 80 4.52

Page 13: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

COST OF PRODUCTION AND FERTILIZER SHARE (Rs. / acre)

YearsCOTTON SUGAR CANE MAIZE

Total Cost.

Fert. %AgeTotal Cost.

Fert. %AgeTotal Cost.

Fert. %Age

2003-04

14,336 1,823 12.72 23,636 3,825 16.18 9,249 1,442 15.59

2004-05

15,671 2,213 14.12 24,492 4,048 16.53 9,755 1,702 17.45

2005-06

17,319 2,289 13.22 25,008 3,630 14.52 11,010 1,777 16.14

2006-07

18,847 2,431 12.90 29,600 3,965 13.40 18,216 3,698 20.30

2007-08

19,505 2,620 13.43 30,428 3,675 12.08 18,827 3,571 18.97

2008-09

24,676 5,130 20.79 42,006 8,180 19.47 31,839 12,240 38.44

2009-10

27,509 4,065 14.78 43,549 8,227 18.89 33,547 11,025 32.86

2010-11

32,360 5,175 15.99 47,744 7,370 15.44 39,496 13,240 33.52

2011-12

43,850 7,888 17.99 57,282 9,446 16.49 49,093 19,305 39.32

2012-13

48,923 8,775 17.94 70,054 12,905 18.42 57,506 22,275 38.74

Page 14: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

COST OF PRODUCTION AND FERTILIZER SHARE (Rs. / acre)

YearsWHEAT RICE

Total Cost.

Fert. %AgeTotal Cost.

Fert. %Age

2003-04 9,028 1,316 14.58 11,741 1,463 12.46

2004-05 10,198 1,650 16.18 12,469 1,723 13.82

2005-06 11,524 1,847 16.03 13,716 1,779 12.97

2006-07 12,264 1,910 15.57 15,087 1,874 12.42

2007-08 15,626 3,614 23.13 16,154 2,005 12.41

2008-09 19,547 4,195 21.46 22,064 3,760 17.04

2009-10 24,187 3,332 13.78 24,898 3,110 12.49

2010-11 24,428 5,098 20.87 29,240 4,000 13.68

2011-12 29,149 6,280 21.54 36,351 5,992 16.48

2012-13 31,490 6,550 20.80 41,810 6,670 15.95

Page 15: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

FERTILIZER USE EFFECIENCY

Page 16: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

SOIL ANALYSIS

Page 17: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

SITE SPECIFIC FERTILIZER APPLICATION!

Page 18: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS
Page 19: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

BALANCED NUTRITION

Page 20: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

SITE-SPECIFIC NUTRIENT MANAGEMENT FOR CROPPING SYSTEMSSITE-SPECIFIC NUTRIENT MANAGEMENT FOR CROPPING SYSTEMS

Page 21: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

Nutrient Expert for Hybrid Maize Software

Page 22: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

Extension Viewpoint• Develop and deploy latest communication tools to raise

farmers’ awareness about the economic, social and environmental benefits of adoption of IPNM.

• Conduct field demonstrations applying locally-adapted IPNM techniques and prepare literature/media campaign with the results from the local demonstrations.

• Assist farmers in making the best decisions for managing crop nutrients at the field and farm levels.

• Provide farmers with all necessary products, services and information to successfully implement IPNM.

• Training of the extension agents for best use of modern gadgets and techniques to assist farmers

Page 23: PREDICTION MODELS FOR SITE SPECIFIC RECOMMENDATIONS

THANKS