E-ISSN 2667-6540
Volume : 5 Issue : 1 Year :


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INTERNATIONAL JOURNAL OF APPLIED BIOLOGY AND ENVIRONMENTAL SCIENCE (IJABES) - IJABES: 5 (1)
Volume: 5  Issue: 1 - 2023
1. Cover

Page I

2. Contents

Pages II - III

ORIGINAL RESEARCH
3. Statistical Examination of Yield And Quality Components in Wheat (T.Aestivum L.)
ZEKIYE BUDAK BASÇIFTÇI, Murat OLGUN, Nazife GOZDE Ayter Arpacıoğlu, Arman Atalar, Metin Turan
doi: 10.5505/ijabes.2023.80774  Pages 1 - 17
The aim of this study was to determine certain characters, having significant effect in seed yield and protein content by statistical analyze methods, conditional formatting, correlation and path, multiple linear stepwise regression, factor, biplot, decision tree and phyton regression analyzes in bread wheat. This study was carried out under arid conditions in the experimental field of the Faculty of Agriculture of ESOGU during the cultivation period of 2019-2020 and 2020-2021. In the study, seed yield, heading day, plant height, seed number and weight/spike, spike length, SPAD, chlorophyll a and b, thousand seed weight, test weight, protein content, micro sedimentation were examined. The two-year averages of the results of the examined elements were taken into account and statistical analyzes were made on these results. As statistical analyzes; conditional formatting, correlation and path, multiple linear stepwise regression, factor, biplot, decision tree and phyton regression were used. It was determined that seed number/spike, seed weight/spike, micro sedimentation, SPAD, chlorophyll a and chlorophyll b were were found to be effective parameters on seed yield and protein content.

4. ADULT EMERGENCE PERFORMANCES OF Trissolcus semistriatus Nees (HYMENOPTERA: SCELIONIDAE) AND Telenomus turesis Walker (HYMENOPTERA: PLATYGASTRIDAE) ON SUNN PEST EGGS
Tolga Aysal, Çisem Nur Göven
doi: 10.5505/ijabes.2023.35744  Pages 18 - 29
Eurygaster integriceps Puton (Sunn pest) is the common pest that causes economic loss on wheat. Egg parasitoids have been used successfully in biological control studies against Sunn pest. The intraspecific or interspecies behavior of these parasitoids affects the success of biological control. Therefore, in this study, adult emergence rates were investigated in eggs parasitized by Trissolcus semistriatus Nees and Telenomus turesis Walker, which are egg parasitoids of sunn pest. The experiments were carried out in two different applications. In the first experiment; one T. semistriatus and one T. turesis female were given to different numbers of sunn eggs (2-4-8 packs) in the same conditions. In the second experiment; Three T. semistriatus and one T. turesis female were given to 8 packs of Sunn pest eggs in the same conditions. Then the experiment was repeated in the opposite way. Total adult emergence rate in experiments given one T. semistriatus and one T. turesis female; It was found to be higher in T. semistriatus in 2 and 4-pack egg applications. T. semistriatus constituted 72,40% of the total adult emergence rate in eggs given three T. semistriatus and one T. turesis female. The emergence rate of T. turesis was calculated as 55,65% among the total emergence rate in eggs given by three T. turesis and one T. semistriatus female. In conclusion; In the experiments where two parasitoids were compared, it was concluded that T. semistriatus was more successful in competition in terms of adult emergence rate.

5. Forecasting of Turkey's Grain Yield an Annual Basis By Using Multi-Layer Perceptron Neural Network: Wheat, Barley, Rye And Oat
ZEKIYE BUDAK BASÇIFTÇI, Nazıfe Gozde Ayter Arpacıoğlu, Eyyüp Gülbandılar, Murat OLGUN
doi: 10.5505/ijabes.2023.61687  Pages 30 - 41
The objective of this study was to analyze acreage, production, and yield on cereals (wheat, barley, rye and oats), cereals in Turkey for long-term period, taking into account the changes occurred, forecasts in crop production for the future population was determined by used Multi-Layer Perceptron Neural Network Model (MLPNN). The model application was performed with software by using the time (year), population, wheat, barley, rye and oat production, croplands of wheat, barley rye and oat contents as the inputs/output variables for MLPNN, and yields of wheat yield, barley rye and oat contents. The performance of the proposed MLPNN model is very high and its use for forecasts in crop production for the future population (between R2 = 0.97 and R2=0.99 for training model)

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