Water stress is one of the most important growth limiting factors in crop production. Several methods have been used to detect and evaluate the effect of water stress on plants. The use of remote sensing is deemed particularly and practically suitable for assessing water stress and implementing appropriate management strategies because it presents unique advantages of repeatability, accuracy, and cost-effectiveness over the ground-based surveys for water stress detection. The objectives of this study were to 1) determine the effect of water stress on sweet corn (Zea mays L.) using spectral indices and chlorophyll readings and 2) evaluate the reflectance spectra using the classification tree (CT) method for distinguishing water stress levels/severity. Spectral measurements and chlorophyll readings were taken on sweet corn exposed to four levels of water stress with 0, 33, 66 and 100 % of pot capacity (PC) before and after each watering time. The results demonstrated that reflectance in the red portion (600-700 nm) of the electromagnetic spectrum decreased and increased in the near infrared (NIR) region (700-900 nm) with the increasing field capacity of water level. Reflectance measured before the irrigation was generally higher than after irrigation in the NIR region and lower in the red region. However, when the four levels of PC and before or after irrigation only were compared, reflectance spectra indicated that water stressed corn plants absorbed less light in the visible and more light in the NIR regions of the spectrum than the less water stressed and unstressed plants. There was a similar trend to reflectance behaviour of water stress levels using chlorophyll readings that decreased over time. The CT analysis revealed that water stress can be assessed and differentiated using chlorophyll readings and reflectance data when transformed into spectral vegetation indices.
Abstract. The purpose of this study was to establish the growth curves parameters of American Bronze turkeys. The weekly body weight changes of male and female turkeys were recorded during 11 to 24 weeks of age. The Richards' growth model fitted the turkey weight and age (week) data. Profile analysis was also applied to weight-age data in order to get more detailed information about the differences in the live weights of male and female turkeys in consecutive weeks. Estimates for mature body weight were found as 9720.40 ± 971.33 g and higher for males than for females as 6029.96 ± 316.55 g. Based on Richards’ model, male turkeys matured more slowly and it was needed that a more time to reach mature body weight than female turkeys. Results of profile analysis supported those results. Estimates for the absolute growth rate, absolute maturing rate and relative growth rate values were higher for females when compared to males. Male turkeys reached the maximum growth rate at 16.30 weeks of age whereas female ones reached the maximum growth rate at 12.85 weeks of age. Live weights of male and female turkeys, when both reached the maximum growth rate, were 3475.61 g and 2156.06 g, respectively. Male turkeys reached 80 % of their mature weights at 24 weeks of age, whereas female ones reached 92% of their mature weight.
In this study, Regression Tree Analysis (RTA) was used to predict and to determine the most important variables in predicting the slaughter weight of Ross 308 broiler chickens. Data for this study came from 224 chickens raised during three different seasons, namely spring (n=66), summer (n=66), winter (n=92). Second week body weight, shank length, shank width, breast bone length, breast width, breast circumference and body length were used to predict the slaughter weight. Results of RTA showed that among the seven independent variables only four were selected, namely; body weight, breast bone length, shank width, and breast circumference. These selected independent variables were more efficient than the others in predicting the slaughter weight. RTA indicated that the birds which had values of second week body weight >295.95 g, breast bone length >55.82 mm and breast circumference >14.18 cm or that of body weight ≤295.95 g, breast bone length >60.26 mm and shank width >8.32 mm could be expected to have higher slaughter weights.
A simulation study was conducted to investigate the effect of non normality and unequal variances on Type I error rates and test power of the classical factorial anova F‐test and different alternatives, namely rank transformation procedure (FR), winsorized mean (FW), modified mean (FM) and permutation test (FP) for testing interaction effects. Simulation results showed that as long as no significant deviation from normality and homogeneity of the variances exists, generally all of the tests displayed similar results. However, if there is significant deviation from the assumptions, the other tests are observed to be affected at considerably high levels except FR and FP tests. As a result, when the assumptions of factorial anova F‐test are not met or, in the case those assumptions are not tested whether met, it can be concluded that using FR and FP tests is more suitable than the classical factorial anova F‐test.
Ezine cheese is a white pickled cheese ripened in tinplate containers for at least 8 mo. A mixture of milk from goat, sheep, and cow is used to make Ezine cheese. Ezine cheese has geographical indication status. The purposes of this study were to determine and compare the changes in basic composition, aroma, and sensory characteristics, and proteolytic activity of Ezine cheese stored in tinplate containers and plastic vacuum packages during storage. Aroma-active compounds were determined by thermal desorption gas chromatography olfactometry. To evaluate the proteolytic activity, casein and nitrogen fractions were determined. The results indicated that compounds identified at high intensities were dimethyl sulfide, ethyl butyrate, hexanal, ethyl pentanoate, (Z)-4-heptenal, 1-octen-3-one, acetic acid, butyric acid, and p-cresol. Characteristic descriptive terms were cooked, whey, creamy, animal-like, sour, and salty. The level of proteolysis increased in Ezine cheese during storage. Ezine cheese can be ripened in small-size packaging after 3 mo of storage. Approximately 6 mo is sufficient to produce the characteristic properties of Ezine cheese.
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