Clove oil was emulsified in 1% w/w chitosan (CC emulsions) and 2.5% w/w sodium alginate matrix (CA emulsions) containing Tween 80 as the surfactant. Different homogenization speeds (5,000, 10,000, 15,000 and 20,000 rpm) were used to produce the emulsions, and the stability of the emulsions during storage (29 days) was determined. The stability of the emulsions containing clove oil prior to the solidification process was assessed when chitosan and sodium alginate were used as encapsulating materials. Different homogenization speeds resulted in polydisperse emulsions with a size of 2–3 μm and 90% of stability after 29 days of storage. Different homogenization speeds did not significantly affect the concentrations of the active compounds contained in the emulsions. However, these concentrations changed significantly after 29 days of storage when sodium alginate was used to make the emulsions and the homogenization speeds were ≥ 10,000 rpm. High temperature caused by the high viscosity of the solution and high energy dissipation during homogenization suggested that the emulsions composed of sodium alginate were unstable. Chitosan enabled a longer processing time during the clove oil encapsulation process compared to sodium alginate, when emulsification by homogenization was used. The stability of the emulsion of the clove oil-in-chitosan matrix prior to the solidification step was superior.

Proses penyangraian adalah salah satu proses sekunder dalam pengolahan kopi. Variabel yang digunakan pada saat proses penyangraian beragam diantaranya adalah suhu awal dan derajat penyangraian. Penelitian ini bertujuan untuk menganalisis sifat fisikomia dan melakukan uji citarasa terhadap kopi Arabika Solok dengan perlakuan suhu awal dan derajat penyangraian yang berbeda. Penelitian diawali dengan melakukan analisis sebelum sangrai, melakukan penyangraian dengan suhu awal 180oC, 200oC dan 220oC pada setiap derajat sangrai ringan (light), sedang (medium) dan gelap (dark) serta melakukan pengujian terhadap sifat fisikokimia dan citarasa kopi Arabika Solok. Analisis data yang dihasilkan menggunakan Analisis of Variance (ANOVA) dua arah dan jika menghasilkan pengaruh yang signifikan dilanjutkan dengan uji Duncan’ Multiple Range Test (DMRT). Hasil penelitian menunjukkan bahwa suhu awal penyangraian hanya mempengaruhi sifat rendemen, atribut flavour dan aftertaste, sedangkan derajat penyangraian berpengaruh signifikan terhadap beberapa sifat fisikokimia diantaranya rendemen, densitas kamba, kadar air, warna, keasaman (pH) dan beberapa atribut citarasa diantaranya fragrance, flavour, acidity, body, aftertaste, sweetness dan overall dan tidak ada interaksi antara kedua variabel terhadap semua sifat yang diuji. Sifat fisikokimia dan citarasa yang tidak terpengaruh suhu awal dan derajat penyangraian adalah kadar abu, aktivitas antioksidan, balance, uniformity, dan clean cup. Kopi dengan perlakuan derajat sangrai medium mendapatkan skor akhir tertinggi yaitu 82,3 (specialty

Soy protein isolate (SPI) was isolated from Indonesian soybean var. Grobogan and converted into protein nanofibrils. Their functionalities as a food thickener and building blocks for microcapsules were investigated and compared with those of commercial whey protein isolate (WPI). The isolation yield was about 58% with SPI’s protein content of about 90% on dry basis. Long, curved, and branched SPI fibrils with a few nanometers of diameter were obtained by heating SPI suspension at pH 2.0. The solution of SPI fibrils was shear thinning with much higher viscosity than the unheated SPI which was Newtonian. The fibrils showed a good potential as building blocks of microcapsules prepared by layer-by-layer adsorption method, which were similar to WPI fibrils.

Purpose: This paper aims to develop a coffee supply chain traceability system based on Blockchain (BC) and Machine Learning (ML) with the aim of ensuring the quality of coffee beans production. BC functions to ensure supply chain performance, while the ML model ensures product quality.Design/methodology/approach: Smart Contracts will be built on the Ethereum Virtual Machine BC network based on Ethereum. The ML model to identify good and bad green coffee beans will be built using different YOLO algorithms, which will go through training and validation stages, namely using the k-fold cross validation method. The ML model algorithm is based on Convolutional Neural Network (CNN) using YOLOv5m, YOLOv6m and YOLOv7. The best model will be chosen based on the results of cross-validation with test data in the form of coffee image data that the model has never seen (unseen data). The whole process of building the ML model is done on the Google Collab Pro+ Virtual Machine.Findings: YOLOv5m outperformed the other models in both non-augmented and augmented training datasets, highlighting the proficiency of YOLOv5m in managing compact datasets and its resilience in the face of data augmentation, positioning it as a prime selection for quality discernment tasks within the realm of green coffee beans. The smart contracts offer an all-encompassing approach for user management, monitoring product status, and presenting traceability data within the framework of coffee plantation administration.Originality/value: This research contributes to the development of blockchain network as a solution to implement traceability systems along coffee supply chains in Indonesia. Moreover, it shows that while blockchain can ensure the process of production along the coffee supply to follow certain guidelines, machine learning can verify whether the product that was produced by utilizing BC is of high quality/acceptable.

Beras merupakan hasil pertanian yang banyak dikonsumsi oleh seluruh masyarakat di dunia. Di Indonesia, manajemen transparansi rantai pasok masih menjadi masalah utama karena belum tersedianya informasi yang dapat diakses seluruh anggota rantai pasok. Sangat sulit untuk mendapatkan informasi pada setiap aktor untuk keperluan pengawasan dimana hal ini menimbulkan risiko dan ketidakpastian. Ketelusuran menjadi kebutuhan penting untuk memastikan kualitas dan keamanan produk. Paper ini bertujuan untuk mengidentifikasi rantai pasok beras di Indonesia dan mengusulkan pemodelan sistem ketelusuran menggunakan Unified Modeling Language (UML). Hasil penelitian menunjukkan bahwa rantai pasok beras terdiri dari lima aktor yang berperan. Transisi keadaan dalam proses produksi dan informasi ketelusuran telah diidendifikasi melalui Critical Traceability Point (CTP) yang menyajikan informasi produk, kualitas produk, dan semua transformasi. Lebih lanjut, persyaratan kebutuhan fungsional sistem dan kebutuhan informasi disajikan dalam sequence dan uml static diagram. Terakhir, arsitektur sistem diuraikan dalam paper ini untuk mewujudkan transparansi serta pengendalian kualitas dan keamanan produk.

Tomato (Lycopersicon esculentum L.) production contributes to food and nutrition security, and a lucrative business for many stakeholders. Major stakeholders in the tomato food value chain (TFVC) include farmers, middlemen, wholesalers, retailers, and consumers. Farmers contribute the highest in value addition of tomato but earn the lowest profit (8.8%) compared to retailers (53.0%) with the highest, while middlemen and wholesalers earn 19.2% and 19.9%, respectively. This review is aimed at improving TFVC in Fako Division, South West Region of Cameroon, by evaluating the causes of tomato postharvest losses (PHL) and proposing suitable innovative solutions and policies adapted from existing strategies across the globe. Smallholder farmers incur a lot of PHL of tomato due to mechanical injury from the use of raffia made baskets, overfilled basket, poor transportation and logistics facilities, and harvest maturity index. Perforated plastic crates could be used to reduce losses. The government of Cameroon needs to provide a legal framework on tomato marketing to help regulate the actions of the various actors in order to redistribute profit as per the value added by each actor. Management of PHL is a collective effort of all stakeholders working together to provide high quality and quantity of tomato fruits.