Background: The main problem in nitrogen fertilization for crop cultivated is the very low efficiency due to the leaching process. The purpose of this study was to the determination of the optimum levels of biochar amendment made from Melaleuca cajuputi biochar (MCB) and urea fertilizer (UF) for nitrogen use efficiency in upland rice under M. cajuputi stands.Methods: The study was conducted during dry season within March to June 2019 in Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The experimental design was laid out in a randomized complete block design factorial with three replications as the response surface methodology (RSM). The treatments consisted of MCB levels (0, 5, 10, 15 tons ha-1) and UF levels (0, 100, 200, 300 kg ha-1) as independent variables. The observation parameters were nitrate reductase activity (NRA), total chlorophyll (TC), leaf photosynthesis rate (LPR), nitrogen loss (NL), nitrogen use efficiency (NUE) and seed yield (SY). The data was analyzed using RSM approach and ridge regression.Result: The optimizing applications of 11.14 tons ha-1 of MCB and 281.13 kg ha-1 of UF resulted in NUE and SY by 2.14 kg grain kg Nfertilizer-1 and 5.83 tons ha-1 or increased by 19.07% and 13.02%, compared to a single application of UF by 300 kg ha-1.
Kayu putih (Melaleuca cajuputi) waste has the potential via in situ biochar briquettes to overcome the low availability of nitrogen in soil. This study evaluated the short-term effects of in situ biochar briquettes on nitrogen loss reduction and determined an optimum scenario for hybrid rice grown in an agroforestry system among kayu putih stands. This three-year experiment (2019–2021) was conducted using a randomised complete block design factorial with three blocks as replications. The treatments included biochar briquettes made from kayu putih waste (0-, 2-, 4-, and 6-grain plant−1 or 0, 5, 10, and 15 tonnes ha−1) and urea fertiliser (0, 100, 200, and 300 kg ha−1). The results demonstrated that the eco–environmental scenario was the most efficient strategy that improved the soil quality, the physiological characteristics, and the yield of the hybrid rice with the optimum application of the biochar briquettes at 5.54-grain plant−1 and the urea fertiliser at 230.08 kg ha−1. This alternative approach illustrated a reduction in both the usage of urea fertiliser and the loss of nitrogen by 23.31% and 26.28%, respectively, while increasing the yield of the hybrid rice by 24.73%, as compared to a single application of 300 kg urea ha−1 without biochar briquettes.
Abstract. Suryanto P, Faridah E, Nurjanto HH, Supriyanta, Kastono D, Putra ETS, Handayani S, Dewi AK, Alam T. 2020. Influence of siam weed compost on soybean varieties in an agroforestry system with kayu putih (Melaleuca cajuputi). Biodiversitas 21: 3062-3069. Siam weed (Chromolaena odorata (L.) R.M.King & H.Rob.) has grown wild in many kayu putih (Melaleuca cajuputi Powell) forest can be utilized as compost for complementary of inorganic fertilizers in annual crops. The experiment was conducted during November-February 2020 in Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The experiment was arranged in a randomized complete block design (RCBD) with three replications. The first factor was soybean varieties consisted of Anjasmoro, Dering I, and Grobogan. The second factor was siam weed compost (SWC) application consisted of 0, 5, 10, and 15 tons ha-1. The data were analyzed using Two-way ANOVA, ANCOVA, and stepwise regression. The SWC application of 10 tons ha-1 showed the highest yield of Anjasmoro, Dering I, and Grobogan were 1.42, 1.56, and 1.51 tons ha-1, respectively, or increased by118.46%, 102.60%, and 112.68%, respectively, compared to the without SWC application. The optimum dosage of SWC application for Anjasmoro, Dering I, and Grobogan were 13.05, 14.35, and 14.93 tons ha-1, respectively, with a maximum yield of 1.45, 1.59, and 1.52 tons ha-1, respectively. Soil quality and physiological parameters that had a significant influenced on the production of soybean varieties in agroforestry systems with M. cajuputi were SOM, K, LPR, TC, and PRO.
Macrofungi is one of bio-medicinal sources containing various bioactive compounds, such as β-glucans, which are scientifically proven as immunity booster against coronavirus, including Covid-19. Lawu Mountain Forest has been reported as one of the macro fungi-rich ecosystems in Java. Due to its unique geography, each side of the mountain has a different climate with the southern slope is typically more suitable for various species of mushroom to grow. The aims of this study were to assess fungal diversity in the southern slope of Lawu Mountain Forest, and to ascertain their potential uses for medicinal purpose, particularly for boosting immunity against Covid-19. Cruise method was used to identify macroscopic fungi collected along the hiking trail of Lawu Mountain Forest at the elevation ranges of 1800- 3100 m asl. Their morphological characteristics, including color, diameter, veil surface, lamella (ring and pore, type of lamella, and volva), stem shape, length and diameter, were observed. The study found 46 species from 15 families of macrofungi. Seven species potentially containing bioactive compounds as immunomodulator for boosting immunity were Auricularia auricula, Cerrena unicolor, Lentinus edodes, Pleuretus ostreatus, Stereum hirsutum, Schizophyllum commune, Trametes versicolor.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.