Management of rice production systems to increase productivity

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when it was wetter. The default NUE of 50% is too high during wetter than normal years, but it is perfect in drier years. N Fert Need Kg/Ha N Fert Need Kg/Ha N Fert Need Kg/Ha 180 160 140 120 100 80 60 40 20 2002 cropping season Rainfall below normal 0 591 mm precipitation 0 500 1000 1500 Grain Yield 2000 2500 3000 180 160 140 120 100 80 60 40 20 2001 cropping season Normal rainfall 0 867 mm 0 500 1000 1500 2000 180 160 140 120 100 80 60 40 Grain Yield Kg/Ha 20 2000 cropping season Rainfall above normal 0 970 mm precipitation 0 1000 2000 3000 4000 5000 Grain Yield Kg/Ha 10% NUE 30% NUE 50% NUE WAB56-50 WAB56-125 WAB377-B Peking 69
Figure 10. Grain Yield at Different N Application Rates and NuMass Predicted Yields at Different NUE Values, 2000, 2001, and 2002 Cropping Seasons in Brikama, The Gambia The predicting N for upland rice, NuMaSS should use yields from the drier year; 591 mm rainfall. The amount of precipitation should have a more dominant role in predicting N for upland rice in semi‐arid regions. The NUE appears to be high during drier years. Positively correlating predicted N amount and rainfall amount should be considered for NuMaSS N prediction for upland rice in the semi‐arid regions. Applied N also needs to be managed in a different way. 2.2.4. Conclusions All the low‐input varieties performed better than the local check (Peking); however WAB377‐B‐16‐L3‐LB and WAB56‐125 gave the highest most stable yields. The best NUE (65‐85g grain per gram N) was recorded with WAB56‐50 at low‐input (40‐40‐40 kg/ha NPK) fertilizer application rates. Increasing biomass production or harvest index, or both resulted in yield increases. However, grain filling did not necessarily depend on biomass accumulation, but the possibility for the plant to utilize N already accumulated in the biomass for grain production. This is indicative of the fact that research to increase rice yield potential in the upland should aim at increasing biomass production as well as carbohydrate translocation potential 70
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MANAGEMENT OF RICE PRODUCTION SYSTE
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MANAGEMENT OF RICE PRODUCTION SYSTE
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BIOGRAPHICAL SKETCH The author was
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ACKNOWLEDGMENTS The author is indeb
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TABLE OF CONTENTS CHAPTER ONE: RICE
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3.3.2. Effect of Seedling Age at Tr
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Table 10. Grain Yield from Low‐In
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Table 28. Soil Sample Analysis at T
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Table 46. Yield Parameter SRI Ferti
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Figure 10. Grain Yield at Different
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context of food security. As there
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management of soil nutrients and so
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enough fertilizer was available to
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the importation of agricultural inp
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12000 10000 8000 6000 4000 2000 0 4
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The reason for the decline in The G
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2.1. Introduction CHAPTER TWO: LOW
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tend to produce moderately higher y
Page 37 and 38: available nitrogen and phosphorus r
Page 39 and 40: Table 3. Soil Test Data from Upland
Page 41 and 42: flood/drought cycle, which is provi
Page 43 and 44: educed transpiration due to soil wa
Page 45 and 46: management practices (dry land/irri
Page 47 and 48: Sta Cruz et al. (1994) identified d
Page 49 and 50: 2.1.6. Nutrient Dynamics in Tropica
Page 51 and 52: efficiency (Cassman and Harwood, 19
Page 53 and 54: (1) Higher mineralization rate in t
Page 55 and 56: Translocation of N from the vegetat
Page 57 and 58: NUEp = TDM / NPLANT (3) From equati
Page 59 and 60: 4) The NuMaSS can be used to predic
Page 61 and 62: 1. Zero application (Control) 2. Lo
Page 63 and 64: are averages of duplicated assays a
Page 65 and 66: show any significant differences be
Page 67 and 68: Table 8. Low‐Input Upland Rice Tr
Page 69 and 70: stress conditions that prevailed du
Page 71 and 72: Fertilizer Level Variety Grain Yiel
Page 73 and 74: Harvest Index Harvest Index 0.6 0.5
Page 75 and 76: Tissue N (%) Tissue N (%) Tissue N
Page 77 and 78: According to Fukai et al. (1999) hi
Page 79 and 80: NUE(grain) g per g (N) NUE(grain) g
Page 81 and 82: Necessary inputs for the nitrogen m
Page 83 and 84: Determining Crop N: The first step
Page 85 and 86: Hierarchy for NSoil: 1. You will en
Page 87: e able to access a value from the d
Page 91 and 92: season, but in the event that major
Page 93 and 94: In many cases, results did not meet
Page 95 and 96: 1995 worked with Malagasy farmers a
Page 97 and 98: 3.1.3. Water Management Water contr
Page 99 and 100: diffusion from the soil‐water int
Page 101 and 102: and rewetting of soils as practiced
Page 103 and 104: 2. SRI will increase rice yields be
Page 105 and 106: Three sets of rice nurseries were p
Page 107 and 108: Two rice varieties, IET 3137 and IT
Page 109 and 110: tillering variety, with plant heigh
Page 111 and 112: Gambia prefer bigger seedlings beca
Page 113 and 114: Figure 12. Number of New Roots Re
Page 115 and 116: Seedling Age 5‐Days 5‐Days 10
Page 117 and 118: Table 14. SRI vs. Conventional Prac
Page 119 and 120: The difference in 1000‐grain weig
Page 121 and 122: Variety Inter Space (cm) ITA 306 IE
Page 123 and 124: 104 SRI management practice using 3
Page 125 and 126: fertilizer, but no better panicle f
Page 127 and 128: increase in fertilizer application.
Page 129 and 130: transplanting urea fertilizer was a
Page 131 and 132: 112 Applying just compost alone gav
Page 133 and 134: submerging the 7‐day old seedling
Page 135 and 136: 116 An increase in SRI yields in su
Page 137 and 138: 4.1. General conclusions CHAPTER FO
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practices are 2 to 3 times higher t
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application. This study has proven
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APPENDIX 1: FIELD LAYOUT V. High‐
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Table 26. Soil Sample Analysis at H
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Low‐Input 40‐40‐40 APPENDIX 3
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Table 32. Low‐Input Upland Rice T
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Low‐Input 40‐40‐40 Table 34.
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Table 36. Nitrogen‐Use Efficiency
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Table 38. SRI vs Conventional Pract
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Table 40. Grain Yield from SRI Prac
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Fertilizer Level Table 42. SRI Fert
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Table 44. SRI Fertilizer Management
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Table 46. Yield Parameters SRI Fert
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Cabrera, M.L. 1993. Modeling the fl
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148 Dunsmore, J.R., A.B. Rains, G.D
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150 Hassink, J., Lebbink, G. and Va
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152 management in agricultural syst
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154 Root traits to increase drought
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156 emission from rice fields: The
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158 on ammonia volatilization losse
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Management of rice production systems to increase productivity

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