الفهرس 
NTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Eleven samples; of rice (Oryza sativa L.) four seed samples, 3 samples of wheat seeds (Triticum aesativum L.) and 4 maize (Zea mays L.) seed samples were collectively obtained from different sources. Samples were carefully chosen concerning three separate and important seed-borne diseases. Rice blast caused by Pyricularia oryzae Cav. is the most dangerous disease on rice crop, the fungus can infect plants at any stage of growth. Loose smut disease of wheat caused byUstilago tritici (Pers.) Rostr. with relation between embryo infection and infected plants in field. And thirdly, Cephalosporium maydis Samra, Sabet and Hingorani causes late wilt disease, the major limiting factor in production in maize which transmitting by the soil as well as the seed. Some standard seed health procedures were applied for seed-borne fungi detection from the three seed crops.
1-Washing test, Blotter method, Washing after Incubation (modified), Deep Freezing method and Potato Dextrose Agar method (PDA) were used in case of rice seed samples.
2-Embryo Count method and Field experiment were carried out for loose smut detection.
3-Blotter mehtod, Deep Freezing mehtod and Potato Dextrose Yeast Agar method were implimented in inspecting whole seeds and broken one of maize seed samples.
4- Side by side, PCR detection and identification of the previously seeds-borne pathogen was comparabley applied to face the disadvantages of the common tests. Nano-particles of two metals were involved in to enhance of DNA extraction and focused to compare between some traditional detection methods and advanced PCR-based techniques for detection of seed-borne pathogens in the three major food crops; rice, wheat and maize. Regarding results obtained:
1-from rice seed samples (cv. Sakha 101) showed that:
a-The sum of total fungal counts in 2016 was much higher than those of 2015.Washing after Incubation method (modified from Washing and Blotter methods) gave the highest total fungal counts in 2015 and 2106 being 103 and 128, respectively.
In 2016, the highest total fungal count was Blotter followed b-by PDA, Deep Freezing and Washing tests gave 99.0, 90.5, 87.0 and 22.0, respectively.None of the fungi recorded in 2015 season exceeded frequency of 22.0 incubated on PDA or Deep Freezing method were applied.
Pyricularia oryzea was recorded only for three times with c-very low frequency values of 1.0 and 1.5 in 2015 season (Washing and Washing after Incubation) and 2.0 in 2016 season (Washing after Incubation). Existence of P. oryzea which did not exceed 1.6% relative to total fungal counts among other aggressive saprophytes or pathogenic fungi may finally overcome such serious pathogen.
d- Cultivar Sakha 104 collected from 2015 and 2016 seasons showed similar results. Generally, total fungal counts recorded in 2016 were less than those of 2015 total fungal count. Moreover, the total counts of fungal inocula recorded using the modified method (Washing after incubation method) in 2015 and 2106 were 103 and 97, respectively. When descending arrangement of total fungal count obtained using other standard seed health tests applied were 93, 88, 70 and 27 from PDA, Blotter, Deep Freezing and Washing Test in 2015, respectively.
e- While it could be arranged in 2016 as PDA, Blotter, Deep Freezing and Washing tests gave 91.0, 83.5, 73.0 and 17.0, respectively.
f- Almost Washing after Incubation was the only method that revealed the presence of Pyricularia oryzea with only 1.0 and 1.0 seed-borne infection percentages in 2015 and 2016 seasons, respectively.
2- Seeds of Wheat subsample obtained:
a- In 2014 season showed very low infection level when the Embryo count method was applied. The other two subsamples of 2015 and 2016 yields proved negative. Obtained results were unsatisfactory.
b- Additional field experiment was followed for confirmation. Wheat plants grew from seeds of 2014 season showed the highest infection percentage 18.1% loose smut. Loose smut infected spikes recorded from 2016 and 2015 recorded 17.2 and 15.2%, respectively.
3- In cv. Giza 2 maize seed sample:
a- Fusarium moniliforme was the most predominant in the two years of investigation recording the highest seed-borne infection percentage percentages.
b- The highest result value was obtained in 2016 season using PDYA method with whole maize seeds (29.5%). Regarding seed infection with C. maydis which noticeably recorded the least records when compared to other major fungi considered.
c- At the same time, broken maize seeds yielded higher percentages than those obtained from whole seeds using either method of detection.
d- In 2015, PDYA used in examining broken maize seeds yielded the highest percentage of C. maydis (6.0%), followed by equal records of 3.5% when blotter or deep freezing methods used to examine broken maize seeds.
e- It is also clear that none of the three methods succeeded to express satisfactorily C. maydis from whole maize seeds of cv. Giza 2.
f- Relatively to other major fungi recorded, the deep freezing method gave the least records of C. maydis in 2015 and 2016; 0.0 and 1.2%, respectively.
g- PDYA method gave the highest record in almost equal values during the two successive years of investigation; 11.1 and 11.2%, respectively, but it recorded a little higher than one tenth of the three fungi considered.
h- Broken maize seeds of S.c. 166 yielded higher percentages than those obtained from whole seeds using either method of detection. It is also clear that the late wilt fungus C. maydis was the weakest fungus comparing to F. moniliforme and F. oxysporum. The highest two values of C. maydis (6.5% and 6.0%) were obtained in 2016 and 2015 seasons, respectively.
i- Broken maize seeds were incubated on PDYA for 7 days. On the contrary, deep freezing method gave the minimum records of 0.0 and 0.5% from whole maize seeds collected in 2015 and 2016, respectively.
j- The highest infection percentage recorded during the entire study was 11% which obtained from broken seeds of hybrid S.c. 166 of season 2015 and incubated on PDYA. Exceptionally, one high relative value 18.2% was calculated in contrast to other lower relative values of the total fungal inocula.
k- All other relative values obtained proved that F. moniliforme and F. oxysporum grown vigorously and aggressively than the delicate fungus C. maydis, which may lead to false results and misleading interpretations.
4- Nano-characterization of AgNPs and Fe NPs showed that the biggest size was FeNPs which was in rang of 14.3- 44.3and AgNPs ranged between 14.2-29.5nm. Sizes of FeNPs and AgNPs which were scanned by TEM ranged between 8.53-44.3nm.
5- Using several buffers in extracting DNA from the two samples of rice dry seeds (cvs. Sakha 101 and Sakha 104) resulted in different obtainable DNA concentrations.
a- In case of Sakha 101, DNA extracted by Dell. + AgNPs yielded
(1489.2 ng/μl), followed by Dell. + FeNPs (553.9 ng/μl) and Dell. only (407.7 ng/μl).
b- The same trend was noticed in case of Sakha 104, DNA extracted by Dell. + AgNPs resulted the highest concentration of DNA (1216.0 ng/μl) followed by Dell. + FeNPs (1155.4 ng/μl) and Dell. only (622.0 ng/μl).
c- Regarding purity of samples, it is clearly observed that the most pure samples extracted by Dell. + AgNPs was Sakha 104 where the purity reached 2.09, followed by that of Sakha 101 with AgNPs and Dell. only (2.08).
d- DNA concentration from infected rice seeds (Sakha 101) with P. oryzea by Dellaporta buffer + AgNPs augmented significantly to (1489.2 ng/μl) while 452.7ng/μl in negative control.
e-Total concentration of extracted DNA by using Dellaporta+ FeNPs was 553.9 ng/μl. DNA concentration from infected rice seeds (Sakha 104) with P. oryzea by Dellaporta buffer + AgNPs recorded 1216.0 ng/μl compared to 618.1ng/μl in the negative control, while total concentration of extracted DNA by using Dellaporta+ FeNPs was 1155.4ng/μl.
g- specific primer pair Pfh2a/Pfh2b were Pyricularia oryzea used to detect the expected PCR product size (678bp). Distinctive strong sharp bands of DNA template extracted from fungus pure culture and infected seeds using (Dellaporta buffer and Dellaporta buffer + AgNPs) compared to very weak PCR product from extracted DNA template with Dellaporta buffer+ FeNPs.
h- The whole DNA extracted using Dellaporta buffer, when added to AgNPs gave the highest quantities. In case Sakha 69 harvested in 2014, DNA extracted by Dellaporta buffer + AgNPs yielded 3114.1 ng/μl.
i- While, Sakha 69 sample obtained from 2015 season, DNA extracted by Dellaporta buffer with FeNPs resulted the highest (2093.5ng/μ) followed by Dellaporta buffer with AgNPs (2023.5ng/μl).
j- In case of Sakha 69(2016), DNA was extracted by Dell. Buffer with AgNPs was the highest quantity (2897.1ng/μl).
k- Looking on the purity of samples, it is clearly noticeable that the most pure samples extracted by Dell. + AgNPs. In case of Sakha 69 (2015) extracted by AgNPs was the highest purity (1.98) followed by Sakha 69 collected in 2014 with AgNPs (1.97) and Sakha 69 (2016) by AgNPs (1.87).
6- DNA concentration from infected wheat seeds and healthy seeds (Sakha 69) collected 2014 with U. tritici by Dellaporta buffer + AgNPs gave the highest DNA concentration (3114.1ng/μl) compared to 1758.4 ng/μl in the negative control, while Total concentration of extracted DNA by using Dellaporta+ FeNPs was 2143.3ng/μl.
7- Giza 2,
a- DNA extracted by Dell. + AgNPs yielded (1269.3ng/μl), followed by Dell. + FeNPs (86.9ng/μl) and Dell. only (85.5ng/μl).
b- While, Sc.166 DNA extracted by Dell. + AgNPs resulted the highest concentration of DNA (901.5 ng/μl) followed by Dell. + FeNPs (152.9ng/μl) and Dell. only (152.9ng/μl). Results indicated that the extraction by Dell. + AgNPs the highest yield of DNA and Dell. only was the lowest result.
c- Looking on the purity of samples, it is clearly observed that the most pure samples extracted by Dell. + AgNPs.
d- Giza 2 by AgNPs was the highest purity (2.07) followed by Sc. 166 with AgNPs and Dell. only (2.04). Cephalosporium specific primer pair A200a/A200b were used to maydisdetect the expected PCR product size (200bp).
e- Bands of DNA template extracted by using (Dellaporta buffer and Dellaporta buffer + AgNPs) were strong bands compared to no PCR product in the extracted DNA template with Dellaporta buffer FeNPs and negative control.