Climate Smart Agriculture (CSA) is an integrated approach that transforms the agri-food system and mitigates climate change. They connect the use of farming techniques in order to increase food productivity, Climate resilient practice, and decrease greenhouse gases. The main aim of this review is to demonstrate the typical interrelationship between climate and agriculture and get knowledge regarding this. In addition, focus on traditional agriculture along with its mitigating measures for climate agriculture. They approach collective development practices through the efforts of individuals in order to manage agriculture and the food system under climate change. Therefore, there is an increasing need for a strategic plan to balance agriculture and the food system.

This study was required to assess the existing tef market outlets and examine factors affecting market outlet choices among smallholder tef producers in western Ethiopia. For this study qualitative and quantitative data were collected from tef producers. Purposive and multi-stage sampling technique was used to determine sample households. The descriptive statistics and multivariate probit model were employed to analyze the collected data. The result shows that there are five alternative main market outlets available for the tef producers that are wholesalers, collectors, cooperatives, consumers, and retailers. These market outlets were affected by household’s demographic such as age, gender, education level, and household size), socio-economics (land allocated for tef, a variety used, livestock holding, and off/non-farm activities), institutional (credit, extension, and market information), and market (volume of tef produced, own transport facility, and nearest market) factors. Based on the findings strengthening farmers’ skills and knowledge through training, advising, and supervision; capacitate farmers by the additional work atmosphere and empowering women farmers by improved variety, working capital, and other recommendations are need attention by respective sectors.

Heavy metals are one of the factors that pollute the environment and significantly affect soil fertility, plant physiology, development, and productivity. The tolerance of plants to toxicity depends on the species and tissue, element type, and duration of exposure to stress. Some special signal molecules such as nitric oxide (NO), hydrogen peroxide (H2O2), beneficial ions, hyperaccumulating plants, stress hormones, nanoparticles, organic compounds, and microbial applications can be recommended to alleviate the stress effects caused by toxic heavy metals in plants. Induction of other promising techniques like seed priming, active involvement of plant growth regulator, use of osmoprotectants, successful plant microbes’ crosstalk and recent utilization of nanoparticles are worth using strategies in mitigation of heavy metal stress in plants. These practices effectively regulate the activities of antioxidant enzymes for the alleviation of stress in plants, creditably improving the plant tolerance via preserving cell homeostasis and amending the adversative effects of heavy metal stress in plants. These inventive strategies offer an enriched understanding of how to boost crop productivity under heavy metal stress in order to decrease the risk to global food security.

The detection of weeds with computer vision without the help of an expert is important for scientific studies and other purposes. The images used for the detection of weeds are recorded under controlled conditions and used in image processing-deep learning methods. In this study, the images of 3-4-leaf (true-leaf) periods of the wild mustard (Sinapis arvensis) plant, which is the critical process for chemical control, were recorded from its natural environment by a drone. The datasets were included 50-100-250-500 and 1 000 raw images and were augmented by image preprocessing methods. Totally 12 different augmentation methods used and datasets were examined for understand how to affects the numbers of images on training-validation performance. YOLOv5 was used as a deep learning method and results of the datasets were evaluated with the Confusion Matrix, Metrics-Precision, and Train-Object Loss. For results of Confusion Matrix where 1 000 images gave the highest results with TP (True Positive) 80% and FP (False Positive) 20%. The TP-FP ratios of 500, 250, 100 and 50 image numbers were respectively; 65%-35%, 43%-57%, 0%-100% and 0%-100%. With 100 and 50 images, the system did not show any TP success. The highest metrics-precision ratio was found 92.52% for 1 000 images set and for 500 and 250 image sets respectively; 88.34% and 79.87%. The 100 and 50 images datasets did not show any metrics-precision ratio. The minimum object loss ratio was 5% at 50th epochs in the 100 images dataset. This dataset was followed by other 50, 250, 500, and 1 000 images respectively; 5.4%, 6.14%, 6.16%, and 8.07%.

: Global climate change is a threat to Turkiye, especially in the agricultural sector. In recent years, the impact of climate change has been felt seriously in Çorum Province. The present study was carried out after it was observed that the average temperature in Çorum province, which was 10.8 °C in 1929-2019 period, rose up to 13.15 °C in 2020. The aim of the present study was to determine the factors that affect the climate change adaptation behavior of the farmers in Çorum, where 37% of the land is devoted to wheat production. A survey was conducted with 385 farmers in January and February, 2021. It was revealed that personal experience had a positive effect of 54% on adaptation behavior, 50% on risk perception and 81% on climate change beliefs. In addition, although belief in climate change had a 45% positive effect on risk perception, risk perception and beliefs had no significant effect on the adaptation behavior. As a result, raising the awareness of farmers about adaptation using agricultural extension services and personal experience teaching method before incurring economic loss is critical to reduce climate risks and to better adapt to climate change.

The purpose of the study is to determine the effects of pre-starter feed prepared using different sugar sources on the performance, carcass parameters, internal organs and intestinal development, microbial load in broilers. In total, 360 newly hatched chicks divided into 4 treatment groups with 5 replicates. 18 chicks with similar live weights (9 male, 9 female) were used for each replicate. Control or pre-starter feeds (containing %14 saccharose, %14 dextrose, or %7 saccharose+ %7 dextrose) were used for the feeding of the groups. For the feeding of the control group, standard chick starter feed was used for the first 5 days; for the treatment groups, the pre-starter feeds prepared were used. For the rest of the trial period, all groups were subjected to standard feeding. A significant difference was observed among groups with regards to live weight gain and feed conversion rate during the first four weeks of the study; however, this effect disappeared over the last week. In addition, it was determined that any differences observed with regards to carcass parameters other than hot and cold carcass weights, internal organ development aside from proventriculus, intestinal development and microbial load were not significant. It was concluded that the pre-starter feed prepared with saccharose and/or dextrose did not show the expected effect

This study evaluates the chemical properties of mistletoe leaves powder from moringa trees (MLPM) and mistletoe leaves powder from kola nut trees (MLPK). The MLPM and MLPK were subjected to phytochemical analysis, vitamin A determination, lipid peroxidation inhibition activity, 2, 2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) analysis, proximate and mineral composition analysis, alpha-amylase inhibitory activity and alpha-glucosidase inhibitory activity. Total phenol, steroids, and tannins concentrations were higher in MLPK than in MLPM; steroids was higher in MLPK than in MLPM; whereas total flavonoids and saponins concentrations, were equivalents. MLPK had greater vitamin A concentrations and DPPH than MLPM. The lipid peroxidation inhibition of MLPM and MLPK did not differ significantly. MLPM had higher moisture, crude fibre, and ash content than MLPK. Furthermore, MLPK had larger fat, crude protein, and nitrogen-free extract contents than MLPM. The MLPM and MLPK have similar Zn (0.9 vs. 1.3 mg/kg), Ca (20.1 vs. 13.1 mg/kg), Mg (66.1 vs. 70.2 mg/kg), and P (185.8 vs. 183.5 mg/kg) contents. The alpha-amylase inhibitory action of MLPM (40.40%) and MLPK (35.07%) were similar. MLPK (44.37%), on the other hand, has a stronger alpha-glucose inhibitory action than MLPM (32.47%). Finally, phenol, steroids, tannins, and steroids varied between MLPM and MLPK, with phenol, steroids, and tannins being greater in MLPK. The MLPM had higher vitamin A concentrations and antioxidant activity than MLPK. The MLPM and MLPK inhibited alpha-amylase and alpha-glucosidase activity.

In the study carried out, obtaining environmentally friendly biopolymers from sustainable sources and their usability as biomaterials were investigated. For this purpose, collagen from bovine achilles tendon, fibroin from silkworm cocoon, sodium alginate from brown sea algae and bioactive components from gel of aloe vera were isolated and purified. Product efficiency were calculated as 79.8% (w/w), 69,49% (w/w from cocoons), 35.1% (w/w) and 1% (w/v dry weight in gel) for collagen, fibroin, sodium alginate and aloe vera, respectively. Tissue scaffolds were prepared from these biomolecules by freeze drying method. However, aloe vera gel could not maintain the structural integrity in solid form and could not form a 3-dimensional scaffold. FTIR analyzes of fibroin, collagen and sodium alginate scaffolds showed that the products were obtained pure and the chemical structure was preserved during lyophilization. Surface analyzes with SEM, on the other hand, supported that the scaffolds are suitable for tissue engineering applications. As a result, it was determined that bioactive polymers were obtained from sustainable sources, generally at room conditions, with high yield, instead of petroleum-derived polymers, and they could be used as biomaterials. Obtaining biomolecules from sustainable sources in this way has significant potential in solving both the raw material problem and the environmental pollution caused by polymers.

This study focused on the determination of secondary metabolites to an evaluation of the biological activity of Elaeocarpus variabilis Zmarzty fruit extract, an endemic medicinal plant. Their total Phenolic, tannin, flavonoids, alkaloids and saponins contents were quantified and their antioxidant activity, determined by DPPH, total antioxidant, ABTS, FRAP and Fe2+ chelating activity. The ethyl acetate extract exhibited the highest radical scavenging activity. The most relevant contents in total phenolics (Gallic Acid Equivalent mg/g), tannin (Gallic Acid Equivalent mg/g), total flavonoids (Rutin equivalent mg/g), total alkaloids (Quinine equivalent mg/g), and total saponin (Diosgenin equivalent mg/g) were observed. Significant correlations were established between antioxidant activity and secondary metabolites. Though the in vitro anti-diabetic activity was carried out using -amylase and -glucosidase inhibition, this indicates that the absorption and digestion of carbohydrates would probably reduce the blood glucose levels and hence help the management of type-2 diabetes. The ethyl acetate extract exhibited the potential of anticancer activity on human HT-29 colon cancer cell line IC50 values (30.0 ± 1.0) the valuable activity that compared to doxorubicin (17.0 ± 0.5). While this is the first study concerning extract from E. variabilis, our findings highlighted the richness’ in flavonoids of those extracts and their amazing potential as a source of antioxidant, anti-inflammatory, anti-diabetic, and anticancer agents.

Türkiye’nin su kaynakları her geçen gün giderek kirlenmekte ve kişi başına düşen su miktarı ihtiyacı nüfus artışı ile yıldan yıla hızla artmaktadır. Artan nüfusla beraber gıdaya duyulan ihtiyacın artması buna bağlı olarak su tüketiminin artması, atık suların uygun yöntemlerle arıtılarak çeşitli alanlarda özellikle sulama suyu olarak yeniden kullanımının sağlanması günümüzde ön plana çıkmaktadır. Bu kapsamda, Kırklareli il merkezinin kanalizasyon suları mevcut evsel ve endüstriyel arıtma tesislerinde arıtılarak Kırklareli deresine deşarj edilmektedir. Bu çalışma derenin suları ve arıtma tesislerinden salınan suların, sulama suyu kalitesi ve kirlilik durumunun belirlenerek tarımsal amaçlı kullanıma uygunluğunu ortaya koymak amacıyla gerçekleştirilmiştir. Kırklareli Deresi üzerinde belirlenen istasyonlardan alınan atık su örnekleri mevsimsel olarak alınmıştır. Örnekler üzerinde fiziksel ve inorganik-kimyasal parametreler incelenmiştir. Çalışmadan elde edilen sonuçları değerlendirmek için, Su Kirliliği Kontrol Yönetmeliğinde yer alan Kıta İçi Yerüstü Su Kaynaklarının Sınıfları (KYSKK) kullanılmıştır. Buna göre; Kırklareli deresi su örneklerinin fiziksel ve inorganik-kimyasal parametreleri açısından mevsimsel olarak kalite sınıfının IV. sınıf olduğu belirlenmiştir. Ayrıca, elektriksel iletkenlik (EC) ve sodyum adsorpsiyon oranı (SAR) değerlerini temel alan ABD tuzluluk laboratuvarı sınıflandırma sistemine göre C3S1 sınıfına girdiği, fazla tuzlu olmasından dolayı dikkatle kullanılması gerektiği tespit edilmiştir. Su örnekleri ölçüm değerleri üzerinde yapılan tekrarlanan ölçümlü deneme düzeninde varyans analizi, tek yönlü varyans analizi (ANOVA) ve korelasyon analizi yapılmıştır. İstatiksel açıdan parametreler arasındaki belirgin farklar ve ilişkiler belirlenmiştir.