Jurnal Pangan dan Agroindustri

Stress Tolerance and Organic Acid Productivity of Fungal Strains Isolated from Local Agricultural Sources

Christopher Osazuwa — 2025-04-30

Fungal diversity enhances industrial bioprocess efficiency and innovation. This study was aimed at isolating stress-tolerant fungal strains from local agricultural sources and evaluating their organic acid productivity. Fungal isolation and identification were performed using culture and molecular techniques. Agricultural sources such as cassava peels, palm wine, lignocellulosic waste, and fruit waste were utilized. Environmental stress tolerance and organic acid productivity were assessed using cultural methods. Aspergillus niger and Trichoderma viride showed highest tolerance to temperature and pH. Candida zeylanoides (2.80), Yarrowia lipolytica (2.94), Rhizopus arrhizus (2.58), and A. niger (3.12) were the most promising organic acid producers. Optimal conditions for organic acid production were found to be: 5-10% inoculum size, 30–35°C, pH 5.5–6.0, 144 hours fermentation time, 0.1–0.2%(w/v) nitrogen concentration. These findings indicate that stress tolerance significantly influences the organic acid productivity of these organisms, reinforcing the potential of these local isolates for sustainable bioprocess development.

Sensory Characteristics, Nutrient Content, and Microbial Load of Rice Eel (Monepterus albus) Tocino, Flavored With Fruit Extracts

Halem Karenez Y. Ladipe — 2025-04-30

This study aimed to evaluate the sensory characteristics, nutrient content, and microbial load levels of Rice eel tocino flavored with different fruit extracts. Four experimental fish tocino were formulated to contain O. niloticus + 0%fruit extract (C0), M. albus + 2.26% Philippine lime (T1), M. albus + 2.26% Lemon (T2), and M. albus + 2.26% Orange (T3). Sensory evaluation and descriptive analysis were used for sensory characteristics. FDA standards and aerobic plate count were used for nutrient content and microbial analysis. All treatments were done in triplicate and were subjected to ANOVA with a post hoc test. Results show that sensory attributes in all treatments were perceived as “liked very much”. Nutrient analysis in all formulated treatments has shown an acceptable protein content of 26%-30%. Total fat ranged from 0%-3%, while total carbohydrates ranged from 2%-4.7%. All treatment groups showed acceptable limits of microbial levels (<106 cfu/g) until 32 days of storage.

The Differences in Characteristics of Fruit Leather from Custard Apple with Variations in Hydrocolloid Types and Cooking Time

Syifa Nur Maulida — 2025-04-30

Custard apple has a short shelf life, so they need processing to extend their shelf life, one of which is processed into fruit leather products. The purpose of this study was to determine the influence of different types of hydrocolloids and cooking time on the physical, chemical, and sensory characteristics. This study used a Complete Random Design (RAL) using two treatment factors, including the addition of variations in hydrocolloid types (pectin, carrageenan, and carboxyl methylcellulose (CMC)) and cooking time (3, 5, and 10 minutes), each treatment is repeated 3 times. The results of the study had a real influence on physical and chemical characteristics, with the best treatment results reviewed from the values of L*79.1, a* 4.9 and b* 15, tensile strength 2.86 Mpa, pH 4.32, total dissolved solids 30.3 °Brix, moisture content 22.55%, ash content 5.55%, vitamin C 24.22 mg/100 grams, total sugar 54.54% and antioxidant activity 58%.

Evaluation of Peroxide Value and Free Fatty Acid Content in Coconut Oil and Palm Oil under Different Heating Temperature Treatments using Reflectance–Fluorescence-based computer vision

Luluk Oktaviana — 2025-04-30

Abstract
This study aims to develop a rapid method for assessing the quality of coconut oil and palm oil based on peroxide value and free fatty acid (FFA) content, using a reflectance–fluorescence-based computer vision system. The background of this research lies in the need for a more efficient analytical method compared to conventional laboratory testing, which is often time-consuming and costly. In this study, oil samples were subjected to heating treatments at 180 and 200 °C to simulate frying conditions. The peroxide value and FFA were analyzed using standard laboratory methods, while the computer vision system acquired image data of the oil samples using a reflectance and fluorescence imaging setup. A classification model was developed using a Convolutional Neural Network (CNN) algorithm to automatically extract color features contributing to oil quality classification. The results showed that the *a* (redness) and *b* (yellowness) values increased in samples treated at 180 and 200 °C, indicating Maillard reactions and thermal degradation. Conversely, the *L* value (lightness) decreased due to prolonged exposure to high temperatures. The CNN model was able to classify coconut oil quality with accuracies of 57.07% and 57.41%, while for palm oil, the model achieved accuracies of 85.77% and 94.22%. These findings suggest that the reflectance–fluorescence computer vision approach holds potential as an alternative method for evaluating the quality of cooking oils.

Abstrak
Penelitian ini bertujuan mengembangkan metode cepat untuk penilaian kualitas minyak kelapa dan minyak sawit berdasarkan nilai bilangan peroksida dan kandungan asam lemak bebas (FFA), berbasis computer vision reflektansi-fluoresensi. Latar belakang penelitian ini didasari oleh kebutuhan akan metode analisis yang lebih efisien dibandingkan pengujian laboratorium konvensional, yang umumnya memerlukan waktu lama dan biaya tinggi. Dalam penelitian ini, sampel minyak diberikan perlakuan pemanasan pada suhu 180 dan 200 °C untuk mensimulasikan kondisi kualitas minyak yang berbeda. Nilai bilangan peroksida dan FFA dianalisis menggunakan metode laboratorium, sementara sistem computer vision memperoleh data dari citra minyak yang diambil menggunakan setup computer vision reflektansi dan fluoresensi. Model klasifikasi dikembangkan dengan menggunakan algoritma Convolutional Neural Network (CNN) yang akan mengekstrak fitur warna yang berkontribusi untuk klasifikasi secara otomatis. Hasil menunjukkan bahwa nilai a (kemerahan) dan b (kekuningan) meningkat pada sampel dengan perlakuan suhu 180 dan 200 °C, yang mengindikasikan reaksi Maillard dan degradasi termal. Sebaliknya, nilai L (kecerahan) menurun akibat lamanya waktu pemanasan pada suhu tinggi. Model CNN mampu mengklasifikasikan kualitas minyak kelapa dengan akurasi masing-masing sebesar 57,07% dan 57,41%, sedangkan akurasi pada minyak sawit mencapai 85,77% dan 94,22%. Temuan ini menunjukkan bahwa pendekatan computer vision reflektansi-fluoresensi berpotensi digunakan sebagai metode alternatif dalam evaluasi kualitas minyak goreng.

Manufacturing Chocolate Bar Using VCO as Cocoa Butter Substitute by Conching and Tempering (Reviewed from Conching Time and Variation of Substitute)

Raina Khoirunisa Zain — 2025-04-30

Abstract

One of the important components in making chocolate is cocoa butter because it affects the texture and melting point of the final product. The production process involves several stages, from fermentation to extraction. Therefore, cocoa butter has a high price with limited and fluctuating supply. Cocoa butter also has characteristics that are difficult to replace by other vegetable fats. However, cocoa butter substitutes can be used as an alternative as a more economical substitute. One of them is VCO, which has a high lauric acid content, can soften the texture and has the potential to be a substitute fat in chocolate products. In this study, VCO: Cocoa Butter substitution was carried out with a composition ratio of 0:100, 25:75, 50:50, 75:25, 100:0 (%wt). Chocolate making is processed by conching for 8 and 16 hours with an optimum temperature of 50 ℃ and processed by tempering. From the analysis results, a ratio of 25:75 (%wt) was obtained which produced chocolate characteristics in accordance with SNI 3749-2009, namely with a melting point of 33.2 ℃, water content of 1.20%, ash content of 1.16%, fat content of 43.66%, protein content of 4.89%, and carbohydrate content of 49.09%. VCO tends to lower the melting point of chocolate bars.

Abstrak
Salah satu komponen penting dalam pembuatan cokelat adalah cocoa butter karena berpengaruh terhadap tekstur dan titik leleh produk akhir. Proses produksinya melibatkan beberapa tahap, mulai dari fermentasi hingga ekstraksi. Maka dari itu, cocoa butter memiliki harga tinggi dengan pasokan terbatas dan fluktuatif. Cocoa butter juga memiliki karakteristik yang sulit digantikan oleh lemak nabati lainnya. Namun demikian, cocoa butter substitute dapat digunakan sebagai alternatif sebagai pengganti yang lebih ekonomis. Salah satunya adalah VCO, yang memiliki kandungan asam laurat yang tinggi, dapat melembutkan tekstur dan berprotensi menjadi lemak pengganti pada produk cokelat. Dalam penelitian ini, dilakukan substitusi VCO : Cocoa Butter dengan perbandingan komposisi yaitu 0:100, 25:75, 50:50, 75:25, 100:0 (%wt). Pembuatan cokelat diproses secara conching selama 8 dan 16 jam dengan suhu optimum 50 ℃ serta diproses secara tempering. Dari hasil analisis, diperoleh perbandingan 25:75(%wt) yang menghasilkan karakteristik cokelat sesuai dengan SNI 3749-2009, yaitu dengan titik leleh 33,2 ℃, kadar air 1.20%, kadar abu 1,16%, kadar lemak 43,66%, kadar protein 4,8928%, dan kadar karbohidrat 49,0872%. VCO cenderung menurunkan titik leleh pada cokelat bar.

Chemical and Sensory Characteristics of Sugar-Free Lemon Flavored Ready to Drink Tea with Different Carboxymethyl Cellulose Concentrations

Naufal Saputra Utama — 2025-04-30

Abstract
Ready to drink (RTD) beverages like lemon-flavored tea can be consumed without preparation. This study analyzed the effect of Carboxymethyl Cellulose (CMC) concentrations on sugar-free lemon tea's pH, dissolved solids, polyphenol, sensory attributes and hedonic ratings. A Completely Randomized Design (CRD) with one factor, namely the concentration of CMC used as the variable. The CMC concentration factor was divided into 5 levels: 0.10%, 0.15%, 0.20%, 0.25%, and 0.30%. The results of the study indicated that the concentration of CMC affected pH levels, hedonic taste testing, sensory taste testing and organoleptic testing. However, total dissolved solids were not significantly affected. The optimal formulation was the lemon-flavored tea with 0.25% CMC concentration, which had a pH value of 3.34, total dissolved solids of 0.11, and a polyphenol content of 334 mg/kg. This research is beneficial for the beverage industry in developing sugar-free RTD tea with good taste and sensory stability.

Abstrak
Minuman ready to drink (RTD) adalah minuman yang sudah siap untuk dikonsumsi tanpa memerlukan persiapan tambahan. Penelitian ini bertujuan untuk mengetahui karakteristik nilai pH, total padatan terlarut, kadar polifenol, dan sifat sensori pada minuman teh berperisa lemon bebas gula dengan penambahan konsentrasi Carboxymethyl Cellulose (CMC) yang berbeda. Metode yang digunakan adalah Rancangan Acak Lengkap (RAL) 1 faktor, yaitu konsentrasi CMC yang digunakan sebagai faktornya. Faktor konsentrasi CMC dibagi menjadi 5 taraf, yaitu: 0,10%, 0,15%, 0,20%, 0,25% dan 0,30%. Hasil penelitian menunjukkan bahwa konsentrasi CMC berpengaruh terhadap nilai pH, uji hedonik dan uji organoleptik. Sementara, dari segi total padatan terlarut tidak berpengaruh. Formula terpilih adalah minuman teh berperisa lemon dengan konsentrasi CMC 0,25% yang memiliki nilai pH 3,34, total padatan terlarut 0,11 dan nilai kadar polifenol 334 mg/kg. Penelitian ini bermanfaat bagi industri minuman dalam mengembangkan minuman RTD teh bebas gula dengan cita rasa dan stabilitas sensori yang baik.