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.

One of the most crucial elements influencing the efficacy of artificial insemination applications is semen quality. It is known that post-thaw semen quality was affected by thawing method. Errors made during the thawing process can compromise the motility, viability, morphology and DNA integrity of spermatozoa after thawing. This study was conducted to investigate the effects of four distinct thawing procedures on post-thaw semen quality in bulls. The first group was designated as 24°C (n=8); the straws in this group were thawed in a water bath at 24°C for 60 seconds. Second group was designated as 32°C (n=8); the straws in this group were thawed in a water bath at 32°C for 60 seconds. Third group was designated as 38°C (n=8); the straws in this group were thawed in a water bath at 38°C for 30 seconds. And the fourth group was designated as 70°C (n=8); the straws in this group were thawed in a water bath at 70°C for 7 seconds. Following the thawing process, motility, sperm morphology, viability, and DNA damage rate in spermatozoa were evaluated. Results showed that in 32°C group and 24°C group sperm motility significantly decreased when compared to 70°C and 38°C groups. Additionally, the 24°C group exhibited a significantly elevated DNA damage rate compared to the 70°C group, while no differences were observed in the other groups. In conclusion, the most ideal thawing procedures are at 70°C for 7 seconds and at 38°C for 30 seconds are recommended to get optimum sperm quality from frozen bull semen after thawing.

A screen printed gold electrode (SPGE) served as the foundation for directly depositing Vanadium pentoxide (V2O5), crafting an enzyme-free glucose sensor. Through cyclic voltammetry in an alkaline setting, the sensor's ability to drive glucose oxidation was explored. Utilizing V2O5 as an electrocatalyst, this non-enzymatic sensor exhibited an expansive linear detection range (1 mM–10 mM) and an impressively low detection limit of 0.9 μM. These results underscored V2O5's robust electrocatalytic process in facilitating glucose oxidation within alkaline solutions, unaffected notably by substances like ascorbic acid, fructose and maltose. This investigation highlights a direct and efficient method for glucose detection without reliance on enzymes.

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.

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.

Numerous in-depth studies have described the fertility traits, growth performance and milk yield traits of dairy animals, which are considered indicators of welfare, but there are limited studies examining these traits within the framework of cause-effect relationships, especially in buffaloes. The aim of this study was to determine the changes in some milk, growth and fertility traits of Anatolian buffaloes over the years in some dairy farms where the Buffalo Breeding Project in Public Conditions was implemented in Samsun province and, to investigate the effects of first calving age (FCA) and calving interval (CI) on milk and growth traits. The study was conducted in 27 buffalo farms (3295 buffalo cows and 3317 buffalo calves) located in Bafra district, the region with the highest buffalo population in Samsun province, Türkiye. The data was taken from records previously kept within the scope of the relevant project. The data such as growth characteristics [birth weight (BW), 6th and 12th-mo live weight (LW) values of calves born between 2013-2020] and lactation traits of cows [lactation milk yield (LMY) and lactation duration (LD)] and FCA and CI values were analyzed by analysis of variance. The effect of years on LMY of buffalo cows was found to be significant, and significant positive changes were determined from year to year. In addition, the BW, 6th-mo, and 12th-mo LW values of calves also varied from year to year. As the FCA value of buffaloes increased, the BW, 6th-mo, and 12th-mo LW values of calves and LMY of cows increased. Similarly, CI values affected the BW values of calves (P<0.01), and LMY and LD values increased in parallel with the increase in CI values. Consequently, determining the lactation and growth traits of buffaloes could benefit developing herd management practices that would optimize these performance indicators.

This study examined the nexus between cluster farming and household dietary diversity among smallholder wheat farmers in Oromia region, Ethiopia. Three-stage sampling procedures were employed to gather data from 384 household heads on a cross-sectional survey that was carried out in June 2022. Descriptive statistics and a binary logistic regression model were used for data analysis. The average, minimum, and maximum household dietary diversity scores were 7.10, 1, and 11, respectively. A significant difference was observed: participants in cluster farming had 14% more dietary diversity than their counterparts. Sex, marital status, participation in wheat cluster farming, home gardening, off-farm income, number of crops grown, cooperative membership, and access to training determined household dietary diversity. The study indicates that dietary diversity in households is influenced by a variety of factors. While wheat cluster-based farming is heavily promoted, household food and nutrition security also need to consider other elements like home gardening, off-farm income, cooperative membership, and training access.

The water erosion is a significant environmental issue in arid and semi-arid regions. It leads to soil degradation, reduced agricultural productivity, and desertification. This article used The WEPP, the USLE, and the MUSLE models to estimate the average soil loss in the Yozgat-Kadılı village. Also, The MUSLE model utilized the WEPP model-estimated runoff for soil loss estimation. The USLE model, which estimates soil erosion using six factors (R, K, L, S, P, and C), can be improved by incorporating the Modified Fournier Index (MFI). Results indicated that the MUSLE model (3.66 t/ha) performed well in estimating soil losses close to the observed value (3.15) in the wheat fields between 1986-1996. the MUSLE (5.31 t/ha) and WEPP (5.88 t/ha) models underestimated soil losses to the observed value (8.75 t/ha) in the fallow field for 1986-1996. The WEPP model estimated the highest average soil loss at 5.18 t/ha in a wheat field, while the USLE model yielded the lowest estimate at 1.28 t/ha between 1969 and 2020. The MUSLE model estimated the highest (4.94 t/ha) and The USLE model estimated the lowest (2.53 t/ha) soil loss in the fallow field between 1969-2020. Results also revealed that the WEPP model is needed to calibrate for estimating soil loss in arid and semi-arid regions.

This study aimed to evaluate the impact of varying doses of Zeatin, Kinetin, and Gibberellic Acid biostimulants on the growth and biochemical parameters of Mentha piperita L. Conducted in a greenhouse with three replications using a "Completely Randomized Experimental Design" design, the experiment assessed seedling and root lengths, fresh and dry weights of seedlings and roots, total phenolic content, and antioxidant activity (CUPRAC and FRAP). The results revealed that biostimulant applications significantly increased all growth and biochemical parameters compared to the control. Gibberellic acid at 200 mg/l produced the longest seedlings, while Kinetin at 50 mg/l resulted in the longest roots. The highest antioxidant activity (FRAP) and total phenolic content were observed with the 40 mg/l dose of Zeatin.

Tahin üretiminde en önemli aşama susamın fiziksel ve kimyasal özelliklerini etkilediği için kavurmadır. Bu çalışmada tahin üretiminde kullanılan kabuksuz susam tohumlarının sıcak hava fritözünde optimum kavurma koşullarının belirlenmesi ve özelliklerinin konvansiyonel yöntemle karşılaştırılması amaçlanmıştır. Çalışma kapsamında kabuğu soyulmuş susam tohumları farklı sıcaklık (160°C, 180°C ve 200°C) ve sürelerde (15-70 dakika) sıcak hava fritözünün haznesine 0,8 gr/cm3 olacak şekilde yayılarak kavrulmuştur. Kavurma işlemindeki sıcaklık ve süre parametreleri yanıt yüzey yöntemi kullanılarak optimize edilmiştir. Kavrulmuş örneklerin ΔE (toplam renk değişimi) ve su aktivitesi verilerine göre sıcak hava fritözünün optimum çalışma sıcaklığı ve süresi 181,1°C ve 36,7 dk olarak belirlenmiştir. Sıcak hava fritözünde kavurma neticesinde konvansiyonel kavurmaya göre yağ verimi %50’den %60’a çıkmıştır. En düşük peroksit değeri 1,69 meq O2/kg ile 180°C de 35 dk da sıcak hava fritözünde tespit edilmiştir. FTIR sonuçları da sıcak hava fritözü ile kavrulmuş susamların oksidasyona karşı daha dayanıklı olduğunu desteklemiştir. Sıcak hava fritözü ile 5 kat daha kısa sürede kavrulan susamların konvansiyonel kavurmaya göre asitlik değerleri ve yağ asidi kompozisyonları benzer bulunmuştur. HMF içeriğinde ise sağlık açısından riskli seviyede bir oluşum gözlenmemiştir.