Katkı maddeleri, gıdaya güvenliği, tazeliği, tadı, dokuyu veya görünümü korumak ve geliştirmek amacıyla eklenen maddeler olarak tanımlanmaktadır. Katkı maddelerinin kullanımı, yasal düzenlemelere uygun olması halinde ve belirlenen konsantrasyonda kullanılması durumunda tüketiciler için tehlike oluşturmamaktadır.  Fakat gıda katkı maddelerine ilişkin endişeler, son 20 yılda artış göstermiştir. Son yıllarda gıda katkı maddesi olarak kullanılan kimyasallarla ilgili olarak giderek daha fazla çalışma sağlığa olumsuz etkilerini göstermektedir. Aslında sağlık sorunlarını daha iyi tanımlayabilmek için toksisite testleri geliştirilmelidir ve yaşam boyunca maruziyeti incelemek için geniş çaplı ve uzun araştırmalara ihtiyaç vardır. Bu çalışmada son gelişmeler ışığında gıda katkı maddelerinin insan sağlığına etkileri irdelenmektedir.

Bağların kontrolünün, takibinin ve bakımının zamanında doğru bir şekilde yapılması çok önemlidir. Bağ zararlılarıyla mücadelede aşırı pestisit kullanımı, insan sağlığını tehlikeye atmakta ve çevre kirliliğine yol açmaktadır. Ayrıca aşırı pestisit kullanımı ekonomik açıdan düşünüldüğünde işletme giderlerinin artmasına sebep olmaktadır. Bu nedenle bağdaki zararlıların ve hasarlarının zamanında teşhisi çok önemlidir. Zamanında tespiti sağlamaya yardımcı olan yöntemlerden biri derin öğrenmedir. Bu çalışmada, bir derin öğrenme nesne algılama algoritması olan YOLOv8x modeli ile bazı bağ zararlılarının (Salkım güvesi, Trips, Bağ yaprak uyuzu ve İki noktalı kırmızı örümcek) yaprak ve meyve kısmında oluşturduğu hasarın tespitine yönelik çalışma gerçekleştirilmiştir. 7 farklı sınıftan ve 3500 görüntüden meydana gelen veri seti oluşturulmuştur. Oluşturulan veri seti; YOLOv8(n/s/m/l/x) modelleri ile eğitilmiştir. Eğitim sonucunda, YOLOv8x modeli performans değerleri sırayla; mAP0,5, mAP0,5-0,95, Kesinlik (Precision), Duyarlılık (Recall), 0,926, 0,648, 0,892 ve 0,903 şeklinde sonuçlar vermiştir. Aynı veri seti, YOLOv7, DETR ve RTMDet modelleriyle de eğitilerek YOLOv8x modeliyle performans karşılaştırmaları yapılmıştır. Karşılaştırma sonucunda bağlarda belirtilen zararlıların oluşturduğu hasarı en iyi tespit eden YOLOv8x modeli olmuştur.

The aim of this study was to investigate food safety knowledge levels according to the socio-demographic profiles of young food handlers and to find out the determinants of the knowledge level. A cross-sectional survey was conducted in Türkiye; it consisted of sections including hygienic design, freezing and thawing, preparation, cooking and reheating, service, storage, and foodborne diseases sections. The food safety knowledge level differed according to gender, age, income, grade level, and intership status. Participants who coded 60% of the survey statements correctly were considered to have “good” food safety knowledge. Knowledge about cooking and reheating, foodborne diseases, and service was found to be at a poor level, but food safety knowledge (overall) was good (68%). The correct score ratio was found to be the highest for hygienic design. Binary logistic regression presented that gender, income, grade level, and internship status significantly affected knowledge level. The strongest predictors were found to be income of $638-$850 (exp (β)=12.9) and more than $850 (exp (β)=4.6), respectively. This study highlights that female students under the age of 25 with an income of more than $638, who have not yet completed an internship, have the highest level of food safety knowledge. This study presented a holistic approach to the food safety knowledge of young food handlers. These insights can contribute to the development of hygiene/sanitation and food safety course content for culinary and gastronomy students.

This study focused on evaluating the nutritional characteristics and in vitro true digestibility of apple pomace derived from three apple cultivars: Golden Delicious, Starking, and Granny Smith (Malus domestica Borkh). These apple cultivars were sourced from the local market in Nigde, Turkiye. Statistical analyses, including one-way analysis of variance (ANOVA) and Duncan's test, were employed to assess variations among the apple pomace samples. Results indicated that, except for in vitro true digestibility, there were no significant variations in the chemical composition and total phenolic matter contents among the apple pomaces (P>0.05). However, Granny Smith apple pomace exhibited distinct features, such as higher neutral detergent fiber content (29.80%), elevated crude protein levels (5.09%) and substantial acid detergent fiber (25.30%) values. In contrast, Starking apple pomace displayed superior air-dry matter (27.24%), while Golden Delicious showcased enhanced dry matter (95.3%) and ash content (2.00%). Regarding total phenolic matter contents, Granny Smith excelled with 112.4 mg GAE/100g, outperforming Starking (103 mg GAE/100g) and Golden Delicious (75.8 mg GAE/100g). Crucially, Starking demonstrated superior in vitro true digestibility, with values reaching 92.36% (as received) and 92.23% (dry matter). Granny Smith, in comparison to Golden Delicious and Starking, displayed significantly different neutral detergent fiber digestibility (P<0.05). Starking apple pomace exhibit the highest overall digestibility among the apple pomaces analysed in this study, hence recommended for use in ruminant nutrition. These findings have implications for the potential utilization of apple pomace in diverse applications, given the diverse nutritional profiles of these cultivars.

This study presents research on modelling the efficiency and flow rate of deep well pumping facilities using the response surface method, evaluating the models, and assessing optimization based on target flow rate. Regression and variance analysis techniques have been successfully employed to evaluate the relationship between input factors (input pressure and power drawn from the grid) and responses (system efficiency and flow rate). ANOVA analysis has been used to examine the effects of linear and quadratic terms, and the results have shown that pressure and power drawn from the grid have a significant effect on pump system efficiency. Additionally, the performance of the regression models has been evaluated using error metrics such as R2 value, RMSE, and MAPE. These values for the pumping facility system efficiency model were found to be 0.9993, 0.292%, and 0.71%, respectively, and for the flow rate model, they were 0.9997, 0.69 m3h-1, and 1.07%. The results obtained demonstrate that the model operates with high accuracy and explains a large part of the variance in the response variables. An optimization study was conducted to maximize pump system efficiency by maintaining the flow rate at a certain target value. According to the experimental results obtained, the target flow rate was predicted with an error rate of 1.49%, and the pump system efficiency was predicted with an error rate of 2.14%. This study highlights the effective use of various analytical and experimental methods to improve the efficiency of pump systems. Future researchers are encouraged to conduct similar analyses on a larger scale and under different operating conditions. Furthermore, evaluating different optimization strategies to improve the energy efficiency of pump systems, which can lead to significant energy savings in industrial applications, is recommended.

Araştırma Tokat Gaziosmanpaşa Üniversitesi Ziraat Fakültesi Bahçe Bitkileri Bölümü arazisinde, ‘Tokat-1’ Mürver genotipine uygulanan kontrol, PGPR bakterileri ve solucan gübresinin bitkisel özelliklerine etkilerinin belirlenmesi amacı ile yürütülmüştür. Uygulamalara göre, yazlık sürgün sayıları yaklaşık 14-20 adet/bitki olarak bulunmuş ve uygulamalar arasında istatistiki bir fark olmamıştır. Sürgün boyu en uzun, kontrol uygulamasından 89,39 cm, PGPR uygulamasına 86,48 cm ve solucan gübresi 77,03 cm olarak ölçülmüş ve uygulamalar arasındaki farklılık önemli bulunmuştur. Ağaç taç hacmi ortalaması 1,52-2,43 m3 olarak ölçülmüş ve en yüksek değer kontrol ve PGPR uygulamasından elde edilmiştir. Bitki gövde çapı ve yaprak alanı, uygulamalara göre değişmemiştir. Bitki kök sayısı (46-80 adet/bitki), kök çapı (7,88-10,45 mm) ve kök toplam kuru madde ağırlığına (%28,79-31,63) uygulamaların etkisi benzer bulunmuştur.

Arjinin, bitkilerde stres metabolizmasında yer alan çeşitli metabolitlerin öncülüğünü yapan bir aminoasit olmasının yanı sıra, bitkilerin çevresel streslere yanıtını modüle edebilen bir sinyal molekülüdür. Tuzluluk stresi, özellikle mısır (Zea mays) yetiştiriciliğinde, mahsul verimliliğini artırma açısından önemli bir zorluk oluşturmaktadır. Bu çalışma, L-argininin (L-arg) lipid peroksidasyonunu, bazı antioksidan enzim aktivitelerini ve bu enzimlerin gen ifade seviyelerini modüle ederek tuz stresinin neden olduğu oksidatif hasarı hafifletmedeki potansiyel rolünü araştırmaktadır. Bulgularımız, 200 mM tuz stresi uygulamasında H2O2 ve MDA seviyelerinin arttığını, ancak 1,5 ve 3 mM L-arg uygulamalarının bu seviyeleri azalttığını göstermektedir. Ayrıca çalışmamızda, süperoksit dismutaz (SOD), peroksidaz (POD) ve askorbat peroksidaz (APX) aktiviteleri ile ZmSOD, ZmPOD ve ZmAPX gen ifade seviyelerinin tuz stresi altında giderek arttığı, ancak L-arg’ın bu parametreleri arttırmada daha etkili olduğu belirlenmiştir. En yüksek artışlar SOD enzim aktivitesinde ve ZmSOD gen ifadesinde gözlemlenmiştir. Bu araştırma, tuz stresinde bazı moleküler ve biyokimyasal yanıtların anlaşılmasını derinleştirerek, L-arg uygulamasının bitkilerin çevresel zorluklara karşı direncini artırmada kritik bilgiler sunabileceği önemli bir literatür kaynağıdır.

Measurements of the body structure in sheep are worthy of judging the quantitative features of meat and useful in developing appropriate selection requirements. The current study was aimed to predict live weight and hot carcass weight from linear body measurements of yearling male local sheep. 84 days feeding period fortnightly taken data on 24 local sheep for body weight, body length, heart girth, wither height, sub-sternal height, tail length, tail width, scrotal circumference, and scrotal length were analyzed to study the relationship between linear body measurements and body weight. At the end of the trial all sheep were slaughtered to measure the relationship between body measurements, and hot carcass weight. Microsoft Excel 2010 was used for data analysis. The relationships between the various body measurements were calculated using pearson's correlation coefficient. The backward stepwise multiple regression procedure was used for the determination of the most suitable model for the prediction of the live weight and hot carcass weight. Hot carcass weight was highly correlated (P<0.01) with body weight and scrotal circumference. Besides, it was significantly (P<0.05) correlated with tail width. Body weight was significantly (P<0.05) correlated with all body measurements except tail length and scrotal length. It is concluded that the body weight of the local sheep can be predicted with heart girth, sub-sternal height and tail width; the equation is LW= -97.2 + 0.36HG + 2.1SBSH + 0.57TW with a better coefficient of determination; R2 = 0.55 and the hot carcass weight can be predicted with sub-sternal height and tail width; the equation is HCW= -75.66 + 1.75SBSH + 0.85TW with a coefficient of determination; R2 = 0.33. But, hot carcass can be predicted with body weight, the equation is HCW= -9.39+0.85BWT when weighing scales are affordable with a better coefficient of determination; R2= 0.557.

Potatoes for use in industrial processing must have a low reducing sugar concentration. This study investigates the impact of organic and synthetic fertilizers on the composition of Irish potato cultivars’ reducing sugar, specific gravity, dry matter, and starch. The research was conducted at Busogo Farm in Rwanda, using randomized complete block designs in seasons 2021 B and 2022 A with rate of ten tones per hectare under the doses of 100%, 50%, and 0% and three hundred kilograms per hector under the dose of 100%, 50% and 0% respectively for farmyard manure and NPK 17.17.17. Results showed significant effects of season and treatment on reducing sugar levels in potatoes. Twihaze and Kirundo varieties recorded high glucose (0.09%), while Gisubizo variety in control, recorded low glucose (0.01%). Additionally, the analysis of variance showed that Irish potato varieties with low to moderate and moderate to high glucose contents, respectively, experienced extremely significant (p 0.001) effects of farmyard manure and NPK on glucose content for the seasons 2021 B and 2022 A. The application of inorganic and organic fertilizers had a significant impact (p 0.05) on dry matter in seasons B and A, according to the analysis of variance. Additionally, the results demonstrated extremely significant (p<0.01) differences in specific gravity and starch in both seasons, with Kinigi variety having higher values of dry matter, specific gravity, and starch content in season B and A, respectively, of 24.58, 1.10, and 18.59%. Season 2022 A’s high decreasing sugar levels were caused by meteorological conditions brought on by the soil’s high moisture content as well as the maturity of the tubers. Due to its low level of reducing sugar, Gikungu, Kirundo, and Kinigi are excellent for chips whereas Twihaze variety is advised for boiling cooking methods.

Innovative farming techniques are essential for food security and sustainable farming practices. Innovative agricultural approaches utilize modern technologies and the latest inventions, as well as traditional agricultural practices. The main purpose of this study is to address the relationship between sustainable agriculture and bioeconomy and to examine innovative approaches that are expected to have a significant impact on the agricultural sector in the near future. The study was carried out in compilation format. Bioeconomy is an economic model or methodology based on the economic evaluation of biological resources and processes. Abiotic resources such as microbes, vegetation, animals, and biodiversity are all included in this strategy. On the other hand, sustainable agriculture, which aims to protect natural resources and take into account ecosystem benefits while maintaining food production, is an agricultural paradigm. The primary goals of bioeconomy and sustainable agriculture are economic evaluation, efficient use of natural resources and reduction of environmental impacts. Considered from these perspectives, it can be said that both concepts have common purposes and are closely related. It is possible to say that with the increasing use of sustainable agricultural methods and bioeconomy, the agricultural sector can move towards a more environmentally friendly, efficiently managed and sustainable structure in the future.