Production Practices and Quality Assessment of Food Crops. Vol. 1

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Improvement of Grain Legume Production in Semi-Arid Kenya 175 colorimetric method described by Anderson and Ingram (1993) was used for soil organic C. Total N was measured colorimetrically following Kjeldahl digestion (Bremner and Mulvaney, 1982). Soil P was determined following the method of Foster (1995). Analyses of soil N and P indicate a deficiency of both nutrients (0.7 mg N/g soil and 3.0 mg P/kg soil in 0–60 cm soil depth, respectively). These values are below the threshold values of 2.0 mg N/kg soil and 4.5 mg P/kg soil for optimum crop growth in tropical soils, respectively (Kapkiyai et al., 1999). The C/N ratio and CEC are 11.7 and 7.8 mmol/kg, respectively. 2.5. Greenhouse experiments Glass growth tubes were used as the growth containers while the growth medium was nutrient free vermiculite. Pre-germinated seeds (Somarsegaran and Hoben, 1985) were transferred into the glass growth tubes, one seedling per tube. Uninoculated control plants were used as material control to detect contamination over the growth period in the greenhouse experiment. The Rhizobia were routinely grown on yeast extract mannitol (YEMA). For inoculation purposes, the rhizobia were grown in yeast extract mannitol broth (YEMB). Isolation, presumptive and authentication tests were conducted according to the methods described by Somasegaran and Hoben (1985). The tests carried out were Gram staining, growth of isolates on YEMA, growth on YEMA plus Bromothymol blue (BTB) and growth of isolates YEMA plus Congo red media. The plates were incubated in darkness at 20 °C for 3–5 days. The commercial Rhizobia strains used, i.e. R446 and R3254 were obtained from Microbiological Resource Centre (MIRCEN), University of Nairobi, while strains R578 and R579 were obtained from the Radizin Institut, Iserlohn, Germany. A native strain RTB was isolated from Kiboko soils where tepary beans had been grown. For assessment of effectiveness of the various Rhizobia strains in nitrogen fixation, a total of seven treatments were used. The experimental design was a 7 × 7 Latin square with 7 treatments. This design was chosen because it eliminates row and column effects from the experimental error thus increasing the power of ANOVA (Steel and Torrie, 1981). Each treatment constituted 7 replications. The treatments were as follows: (1) Nitrogen (N) tepary bean grown in N rich medium (2) Control no inoculation of tepary bean and no N (3) R578 tepary bean inoculated with rhizobium strain R578 (4) R446 tepary bean inoculated with rhizobium strain R446 (5) R579 tepary bean inoculated with rhizobium strain R579 (6) R3254 tepary bean inoculated with rhizobium strain R3254 (7) RTB tepary bean inoculated with rhizobium strain RTB Nodule assessment was carried out in the greenhouse as described by Gitonga et al. (1999). The number of Rhizobia in the soil was determined using the MPN plant infection technique as described by Beck et al. (1993) (equation 3)
176 Chris A. Shisanya MPN = (m × d)/v (3) where: m is the most likely number, d is the lowest dilution, and v is the aliquot used for inoculation The plants in the glass growth tubes were harvested after 30 days. The plant material was separated into shoots, roots and nodules and dried to constant weight at 70 °C. The dry weights were determined using a high precision digital Sartorius weighing balance (U6100-D2, Sartorius, Göttingen). 2.7. Determination of nitrogen concentration in plant tissues Due to high cost of nitrogen analysis, final field harvest plant samples were analysed for nitrogen. The plants were dried to constant weight and the dry matter weights recorded. Thereafter, the dry matter was separated into above ground (shoot) and below ground (root) tissues. The shoot, root and seeds were ground into powder using a grinding mill type 1029-A (Yoshida Seishakusho Co. Ltd., Japan). Nitrogen was analysed in the shoot, root and seeds using the highly sensitive automatic nitrogen-carbon analyzer (SUMIGRAPH NC-90 A). 10 mg of each sample were weighed into a boat and inserted into the reaction tube of the analyzer that was then sealed. The analyzer completely combusted the sample in a circulating oxygen current with an oxidation catalyst, converting the component nitrogen and carbon to N2 and CO2 gases, respectively for detection by a TCD gas chromatograph and simultaneous quantification by the data processor. Nitrogen concentration of the sample was calculated as follows: a) Using equation (4) below, nitrogen coefficient FN was obtained per peak integral value of N2 for the known standard sample. b) The calculated coefficient FN was used in equation (5) to calculate the total nitrogen concentration, which was then recorded. The percentage N concentration was multiplied by the respective plant tissue dry weights to get the actual N concentrations as mg N/g dry matter. N ST F N = NPST – NP BL × 100 TN (% N) = FN × (NPSA – NPBL) SA where: N ST = Nitrogen content of the standard sample NP ST = N 2 peak integral value of the standard sample NP BL = N 2 peak integral value of the operating blank NP SA = N 2 peak integral value of the unknown sample SA = weight of the unknown sample in mg. (4) (5)
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Production Practices and Quality As
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Production Practices and Quality As
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CONTENTS Preface List of Authors Ef
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PREFACE Today, in a world with abun
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LIST OF AUTHORS Rufaro M. Madakadze
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EFFECT OF PREHARVEST FACTORS ON THE
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2.1. Temperature Effect of Preharve
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e beneficial to the water economy a
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Other responses that can also be ca
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06. Failure of fruits to ripen in t
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of more than 13 hours of night temp
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temperatures. Some show serious int
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Effect of Preharvest Factors 15 bet
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1) High rainfall conditions where B
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increase in the release of P i from
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however, more severe when foliage i
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temperatures and luxuriant growth a
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development of chilling injury symp
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conditions followed by sudden high
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season. The main environmental fact
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4.4.5.2. Water blisters Storage roo
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Effect of Preharvest Factors 33 REF
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Effect of Preharvest Factors 35 men
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EFFECTS OF AGRONOMIC PRACTICES AND
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Effects of Agronomic Practices 39 F
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Effects of Agronomic Practices 41 6
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Effects of Agronomic Practices 43 F
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Effects of Agronomic Practices 45 R
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MODELLING FRUIT QUALITY: ECOPHYSIOL
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Modelling Fruit Quality 49 the dens
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Is it the only level to be consider
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To calculate the hydrostatic pressu
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on an analysis of the biophysical p
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Modelling Fruit Quality 57 fructose
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Modelling Fruit Quality 59 Figure 4
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f(dd) = dd max - dd dd max - dd min
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which depends on climate and irriga
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distributed over the period during
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Modelling Fruit Quality 73 Pruning
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with Fo, Pe and Pr being local ‘d
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Modelling Fruit Quality 77 than in
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Modelling Fruit Quality 79 Dann, I.
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Modelling Fruit Quality 81 Huguet,
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SPRAY TECHNOLOGY IN PERENNIAL TREE
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Spray Technology in Perennial Tree
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With centrifugal energy systems dro
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fruit orchards is described as 1000
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According to Furness (2000), the nu
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sprayers which were developed prima
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air-blast sprayers in an attempt to
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Most agricultural chemicals have be
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educing dosage rates to one quarter
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CHESTNUT, AN ANCIENT CROP WITH FUTU
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2. WORLD AREA OF CHESTNUT AND PRODU
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Table 2. Chestnut production in the
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vineyards and north facing to chest
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Chestnut, an Ancient Crop with Futu
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Table 5. Continued. Chestnut, an An
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Table 6. Continued. Chestnut, an An
Page 136 and 137: Chestnut, an Ancient Crop with Futu
Page 146 and 147: size. When the trees develop too mu
Page 152 and 153: 6.5. Management of old orchards Che
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Page 158 and 159: where ink disease is rampant, disea
Page 160 and 161: 8.4. Micropropagation Several in vi
Page 162 and 163: 9.3. Hybrids Chestnut breeding in E
Page 174 and 175: IMPROVEMENT OF GRAIN LEGUME PRODUCT
Page 176 and 177: Improvement of Grain Legume Product
Page 188 and 189: 2.8. Field experiments The greenhou
Page 200 and 201: IMPACT OF OZONE ON CROPS S. DEL VAL
Page 202 and 203: Impact of Ozone on Crops 191 observ
Page 204 and 205: Impact of Ozone on Crops 193 1996).
Page 206 and 207: Impact of Ozone on Crops 195 Figure
Page 208 and 209: Impact of Ozone on Crops 197 al., 1
Page 210 and 211: Impact of Ozone on Crops 199 techni
Page 212 and 213: species show a progressive decline
Page 214 and 215: Impact of Ozone on Crops 203 Chaime
Page 216 and 217: Impact of Ozone on Crops 205 Junge,
Page 218 and 219: Impact of Ozone on Crops 207 Polle,
Page 220 and 221: SAFFRON QUALITY: EFFECT OF AGRICULT
Page 222 and 223: 1.2. Commercial interest Saffron Qu
Page 224 and 225: 1.3. Uses Saffron Quality 213 There
Page 226 and 227: oriental-type perfumes (Sampathu et
Page 228 and 229: Saffron Quality 217 Figure 5. Chemi
Page 230 and 231: Straubinger et al., 1997; Straubing
Page 232 and 233: and Micheli, 1979; Curro et al., 19
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(1984) gives the following data: δ
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Saffron Quality 227 Table 3. HPLC a
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Saffron Quality 229 464/2001, OJ L6
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Saffron Quality 231 Saffron in fila
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Saffron Quality 233 sium were the q
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Saffron Quality 235 Figure 11. The
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Saffron Quality 237 Figure 12. Harv
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Morocco. Ait-Oubahou and El-Otmani
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and Micheli, 1979a; Sampathu et al.
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Saffron Quality 243 Table 8. Drying
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Saffron Quality 245 space for sorti
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unpleasant sensory characteristics
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Saffron Quality 249 The effect of
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Saffron Quality 251 Table 10. Effec
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Saffron Quality 253 Alonso, G. L.,
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Saffron Quality 255 Escribano, J.,
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Saffron Quality 257 tion combined w
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Saffron Quality 259 Selim, K., M. T
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FRUIT AND VEGETABLES HARVESTING SYS
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3. PRINCIPLES AND DEVICES FOR THE D
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exert a vertical pulling force to t
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Fruit and Vegetables Harvesting Sys
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- fingers or spikes; - oscillatory
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- frequency and - amplitude of vibr
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To calculate the number of directio
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For the cleaning and separation of
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