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JURNAL BUDIDAYA PERTANIAN
Published by Universitas Pattimura
ISSN : 18584322     EISSN : 2620892X     DOI : -
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
JURNAL BUDIDAYA PERTANIAN (Journal of Agriculture) first published in 2003 by the Department of Agriculture, Faculty of Agriculture, Pattimura University. Jurnal Budidaya Pertanian is an official publication of the Agriculture Faculty, Pattimura University, publishes primary research paper, review article, policy analysis, and research notes and preliminary results in all areas of agronomy. Manuscripts could be written either in English or in Indonesia.
Arjuna Subject : -
Articles 8 Documents
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Search results for , issue "Vol 19 No 2 (2023): Jurnal Budidaya Pertanian" : 8 Documents clear
Identification and Morphological Characterization of Sugar Palm Plants (Arenga pinnata Merr.) Growing on Different Altitudes Hasibuan, Halimatus Syahdia; Wisnubroto, Muhammad P; Edwin, Edwin; Rezki, Dewi; Yulistriani, Yulistriani
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.99

Abstract

Trees of sugar palm (Arenga pinnata Merr.) can grow at an altitude of 0-1400 m above sea level. The best growth of the trees is at an altitude of 500-700 m above sea level. Sugar palm trees also have a wide adaptability to various environmental conditions. The purpose of this research was to determine the morphological characteristicss of sugar palm plants grown at an altitude of 500, 650, and 900 m above sea level so that the kinship relationship can be known. This research was conducted at three altitudes in Lareh Sago Halaban District, Lima Puluh Kota Regency, West Sumatra, namely Nagari Labuah Gunung (altitude 900 m above sea level), Nagari Bukik Sikumpa (altitude 650 m above sea level), and Nagari Tanjung Gadang (altitude 500 m above sea level) from July to August 2023. The method used was a survey with a purposive sampling technique. Identification was carried out on 36 morphological characters, including stems, leaves, fibers, fruits, and seeds. The data obtained were analyzed for their diversity and similarity. The results of the identification and characterization of qualitative and quantitative morphological characters at three different altitudes showed a relatively narrow diversity value. The overall morphological characters of the sugar palm plants were divided into 2 large groups with a coefficient value of 0.72 or 72% similarity distance.
Aplikasi Pupuk Cair dari Limbah Organik dan Nano Nutrien pada Berbagai Varietas Ubi Kayu (Manihot esculenta Crantz) Iftitah, Siti N; Susilowati, Yulia E; Historiawati, Historiawati; Astiningrum, Murti; Novita, Woro A; Damayanti, Alfina R
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.137

Abstract

Increasing cassava production can be achieved among others by giving various forms of fertilizer to provide the nutrients needed by plants. This research aimed to determine the effect of applying liquid fertilizer from organic waste and nano nutrients on the growth of various cassava varieties. The research was carried out from March to November 2023, at the experimental field of the Faculty of Agriculture, Tidar University, in Sidorejo Village, Bandongan District, Magelang Regency. The experimental research was carried out using a factorial design in a Split Plot experiment with 3 replications as blocks. The first factor was the types of varieties consisting of Sticky Rice, Butter, Klenteng, and Rengganis. The second factor as a subplot is liquid fertilizer in the form of slaughterhouse waste and nano nutrients. The data were analyzed using analysis of variance and followed by a Least Significant Difference test at the a = 0.01 and 0.05 levels, as well as the orthogonal test. The results showed that the type of variety used did not have a significant effect on the variables of plant height increase, branch number, branch height, leaf number, root number, root fresh weight, and photosynthesis rate. Rengganis variety had a very significant effect on leaf chlorophyll levels. The application of liquid organic fertilizer, both from slaughterhouse waste and nano nutrients, did not have a significant effect on the variables of plant height increase, branch number, branch height, leaf number and root fresh weight. Liquid fertilizer from slaughterhouse waste hah a significant effect on root number, whereas nano nutrient fertilizer had a significant effect on the rate of photosynthesis and has a very significant effect on leaf chlorophyll content. There was an interaction between varieties and the provision of liquid fertilizer on leaf chlorophyll content.
Optimalisasi Citra Termal dalam Pertanian Presisi untuk Deteksi Dini Masalah Kesehatan Bibit Kelapa Sawit Melidawati, Melidawati; Sofi’i, Imam; Fauziah, Wahyu K
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.106

Abstract

The palm oil industry plays a pivotal role in various sectors, including food and bioenergy. The success of oil palm cultivation relies heavily on the health of the plant's seedlings. Early detection of diseases and stress is crucial to prevent a decline in crop yields and financial losses. Infrared Thermography technology has been widely employed across various fields for non-destructive monitoring, including agriculture. This research focuses on optimizing the use of thermal imaging in precision agriculture to early detect health issues in oil palm seedlings. Thermal imaging enables the precise measurement of plant surface temperatures, facilitating the identification of plant health issues without the need for further visual intervention. This study has the potential to transform approaches to proactively monitoring and managing the health of oil palm plants. Infrared thermography technology is utilized to observe temperature distribution patterns in oil palm seedlings. The objective is to explore the correlation between thermal characteristics and potential health issues or symptoms in these seedlings. Samples used in the research involve Tenera variety oil palm seedlings aged between 5-9 months, a critical growth phase. The study employs the UNI-T UTi120 Mobile thermal camera capable of measuring temperatures ranging from -20°C to 400°C. Subsequently, thermal image processing is conducted to identify thermal characteristics that could serve as indicators of health issues in oil palm seedlings. Statistical analysis is then performed to test significant differences in thermal characteristics between healthy and unhealthy plant samples. The analysis results reveal significant temperature variations between healthy and unhealthy portions of the plant seedlings, with a significance value of 0,025. These findings can serve as a basis for identifying temperature changes as potential early indicators of health issues in oil palm seedlings. This provides a foundation for developing more effective precision agriculture approaches within the palm oil industry.
Optimasi Deteksi Dini Masalah Kesehatan Bibit Kelapa Sawit dengan JST MLP Berbasis Citra Termal Fauziah, Wahyu K; Sofi’i, Imam; Melidawati, Melidawati
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.111

Abstract

Palm oil has an important role in the palm oil industry, but health problems in the seeds threaten production results. This research advocates an innovative approach by combining thermal imaging technology and artificial intelligence, especially Multilayer Perceptron Artificial Neural Networks (MLP ANN), for early detection of health problems in oil palm seedlings. The use of thermal cameras makes it easier to measure the temperature of plants and the surrounding environment. Thermal image analysis helps in evaluating thermal characteristics, especially plant temperature, which may be associated with health problems. Temperature data is classified into normal plants and plants affected by health problems, using statistical analysis to strengthen the relationship. A predictive model using MLP ANN was formulated to correlate thermal characteristics with the health condition of oil palm seedlings. The research results show that this model has high validity, with R2 of 0.933 for calibration and 0.930 for validation. In essence, this method accurately predicts the health condition of oil palm seedlings based on thermal images. This approach has the potential to provide early detection of plant health problems quickly, accurately, and efficiently. Through the application of this method, it is hoped that it can reduce losses due to health problems in oil palm seedlings, thereby making a major contribution to increasing productivity and welfare in the palm oil industry.
Pertumbuhan Tanaman Padi Payo Kerinci Menggunakan System of Rice Intensification (SRI) Andesmora, Evan V; Aprianto, Riko; Novallyan, Devie; Aprisi, Fella
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.117

Abstract

Payo Kerinci Rice is one of the germplasms whose existence must be maintained. This rice is one of the local rice varieties, which is quite rare. Payo rice has a relatively high economic value compared to other rice varieties. This is due to the unique and fragrant taste of the rice, so it is very popular with the public. Increased growth is one of the initial stages in projecting success in rice plant productivity. The System of Rice Intensification (SRI) method is hoped to provide an alternative for farmers in cultivating Payo Kerinci rice. The research method was carried out experimentally using divided plots by comparing the SRI and Conventional methods. The growth parameters observed were plant fresh weight, plant dry weight, number of tillers, plant height, and root length. The research results show that the SRI method provides efficiency in the need for seeds in Payo Kerinci Rice cultivation. The Payo Kerinci rice plants using the SRI single seedling method grew more than the conventional method for all observed variables.
Pengembangan Sistem Prediksi Waktu Penyiraman Optimal pada Perkebunan: Pendekatan Machine Learning untuk Peningkatan Produktivitas Pertanian Anggarda, Mohammad F; Kustiawan, Iwan; Nurjanah, Deasy R; Hakim, Nurul F A
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.124

Abstract

Modern agriculture relies heavily on technology, especially in irrigation management and crop watering. Several previous studies have applied field data-based predictive techniques to improve crop yields. This research aims to develop a prediction system for optimal watering time in plantations and agriculture using a machine learning approach. The rigorous methodology includes data capture, pre-processing, model evaluation and testing, validation, and visualization. High accuracy demonstrates the system's reliability in determining optimal watering needs to improve resource efficiency and crop yields in agriculture. The data obtained from the automatic weather station (AWS) via thingsboard is processed sequentially, starting from data retrieval in json format using postman to transformation into csv files with proper timestamp adjustment. The pre-processing stage includes data cleaning, variable selection, data integration, and generating a clean dataset. In the evaluation stage, the dataset is divided into training data and test data, with the application and comparison of logistic regression, random forest and decision tree models applied as classifiers. Furthermore, the validation and results stage includes prediction, performance testing using the confusion matrix, and visualization of prediction results in the form of text and icons that aim to increase interpetability for users through Google Collaboratory. The results of this research provide an overview of the optimal watering time based on the dataset from the automatic weather station. Further analysis shows that the implementation of machine learning models significantly improves the prediction accuracy, proving the effectiveness of the system in providing more precise watering time recommendations to increase agricultural productivity. The main objective is to develop a machine learning-based watering time prediction system using data from the automatic weather station and evaluate various classifier algorithms to select the best model.
Pengaruh Pupuk Organik Cair dan Urea Terhadap Kemasaman, N-total, Serapan N, Serta Produksi Tanaman Selada (Lactuca sativa L) Pada Regosol Darso, Widya A S P; Kaya, Elizabeth; La Habi, Maimuna
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.142

Abstract

The growth and yield of lettuce can be increased by improving soil fertility, both physical, chemical and biological conditions of soil, through fertilization. The fertilizer given can be organic fertilizer or non-organic fertilizer. Indirectly, soil type also influences vegetable growth and yield. This study aimed to explain the effect of a combination of liquid organic fertilizer and urea on Regosol soil pH, total N, plant N content and red lettuce (Latcuca sativa L) yield. The experiment used a factorial Randomized Block Design with 2 factors and 3 replications. The treatments tried consisted of liquid organic fertilizer with concentrations of 0 mL/L, 2 mL/L, 4 mL/L, and 6 mL/L, combined with Urea fertilizer at a dose of 0 g per pot, 0.3 g per pot, 0.6 g per pot, and 0.9 g per pot. The research results showed that applying liquid organic fertilizer at 6 mL/L of water combined with urea fertilizer at 0.6 g per pot was the best doses that could increase the pH and total N of Regosol soil, respectively with values of 6.03 and 0.27%, as well as increasing N uptake, number of leaves, and freshg weight of red lettuce plants, with respective values of 3.48%, 26.33 leaves, and 40 g.
Diversity of Morphology and Reproduction Phenology of Clove Germplasm on Manipa Island, Western Seram, Maluku Ulath, Yohana; Mahulette, Asri S; Raharjo, Simon H T
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.149

Abstract

Manipa Island, in Western Seram Regency, Maluku Province, Indonesia, is one of the cloves-producing centers in Maluku. So far, the study of clove germplasm on Manipa Island is still minimal, especially studies on morphological diversity and flowering phenology. The study aimed to (1) obtain data and information on morphological characteristics of various clove germplasm on Manipa Island and (2) obtain data and information on reproductive phenology of various clove germplasm on Manipa Island. The study was carried out in two clove distribution areas on Manipa Island, namely West Tomalehu Village (altitude >600 m asl) and East Tomalehu Village (<600 m asl), from March-December 2021. Morphological investigation in this study used survey methods, whereas observations of reproductive phenology were carried out through interviewing representative farmers. The results showed three types of cloves on Manipa Island, namely Tuni, Red Zanzibar, and White Zanzibar. Based on Hierarchical Cluster Analysis (HCA), cloves in Manipa Island were divided into two large groups with a coefficient of dissimilarity of 33%, namely the Tuni clove group as the first group and the Red Zanzibar and White Zanzibar cloves as the second group. The main characterizing character based on Principle Component Analysis (PCA) indicated that the characterizing character in the Red Zanzibar and White Zanzibar cloves was the color of the shoots. In contrast, in Tuni cloves, characterizing characters were the color of the old leaves and the color of petiole tips. The phenology of clove reproduction on Manipa Island consisted of 7 stages, namely: flower induction, flower initiation, pre-anthesis, anthesis, pollination and fertilization, as well as fruit and seed formation, fruit and seed enlargement, and fruit and seed ripening. The timing of the occurrence of each of these phenological stages throughout the year in Manipa Island was determined in this study.

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