Waste resulted from the distillation of kayu putih leaves is a problem in almost all kayu putih refineries throughout Indonesia due to its enormous availability and un-utilization. It has potential to be used as an organic fertilizer source due to its nutrient content (macro and micro) which is higher than organic fertilizer from animals. The use of kayu putih waste is useful to complement and increase the efficiency of nitrogen fertilizer in soybean intercropping with kayu putih . This [...] ABSTRACT Waste resulted from the distillation of kayu putih leaves is a problem in almost all kayu putih refineries throughout Indonesia due to its enormous availability and un-utilization. It has potential to be used as an organic fertilizer source due to its nutrient content (macro and micro) which is higher than organic fertilizer from animals. The use of kayu putih waste is useful to complement and increase the efficiency of nitrogen fertilizer in soybean intercropping with kayu putih . This

Suryanto P, Kurniasih B, Faridah E, Nurjanto HH, Rogomulyo R, Handayani S, Kastono D, Muttaqien AS, Alam T. 2020. Influence of furrow with organic material and Chromolaena odorata compost on upland rice productivity in an agroforestry system with Melaleuca cajuputi. Biodiversitas 21: 780-791. The main problems of rainfed areas for upland rice cultivation in agroforestry system with Melaleuca cajuputi (kayu putih) were limited to soil moisture availability and low fertility of the soil. The experiment was conducted from March to August 2018 in Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The experiment was arranged in strip plot design with three blocks as replications. The vertical plots were rainwater harvesting technique (RHT) consist of without furrow (WF) and furrow with organic material (FWOM). The horizontal plot was Chromolaena odorata (siam weed) compost (SWC) applications consist of 0, 5, 10, and 15 tons ha-1. The data analyzed by ANCOVA, ANOVA, SEM, and stepwise regression. The results of the study informed that the FWOM with SWC of 10 tons ha-1 showed the highest yield of upland rice per hectare was 2.97 tons ha-1 and yields increased by 91.75% compared to the WF without SWC. The environmental variables that significantly affected the yield of upland rice were WUE and Tsoil. The growth variables that significantly affected the yield of upland rice were SDW, RSA, and RDW. The yield component that had a very significant affected on the yield of upland rice was NP.

A family of Sigmoidal non-linear models is commonly used to determine the critical period of weed control (CPWC) and acceptable yield loss (AYL) in annual crops. We tried to prove another non-linear model to determine CPWC and AYL in a soybean agroforestry system with kayu putih. The three-year experiment (from 2019–2021) was conducted using a randomised complete block design factorial with five blocks as replications. The treatments comprised weedy and weed-free periods. Non-linear models comprised 45 functions. The results show that the Sigmoidal and Dose-Response Curve (DRC) families were the most suitable for estimating CPWC and AYL. The best fitted non-linear model for weedy and weed-free periods in the dry season used the Sigmoidal family consisting of the Weibull and Richards models, while in the wet season the best fit was obtained using the DRC and Sigmoidal families consisting of the DR-Hill and Richards models, respectively. The CPWC of soybean in the dry season for AYL was 5, 10, and 15%, beginning at 20, 22, and 24 days after emergence (DAE) and ended at 56, 54, and 52 DAE. The AYL in the wet season started at 20, 23, and 26 DAE and ended at 59, 53, and 49 DAE.

The existence of soybean varieties and soil type interaction causes differences in productivity of soybean varieties in agroforestry systems with kayu putih. Soil quality parameters (physical, chemical and biological characteristics) will affect the productivity of soybean varieties. The objective of this study was to reveal the relationship between soil quality parameters with soybean varieties suitability in agroforestry system with kayu putih over three locations in which their soil type were different, i.e. Lithic Haplusterts, Ustic Epiaquerts and Vertic Haplustalfs. The study was conducted from May to August, 2018 in Menggoran Forest Resort, Playen District, Gunungkidul Regency, Special Province of Yogyakarta, Indonesia. The highest yield of soybean per hectare on Dering I grown in Lithic Haplusterts and Ustic Epiaquerts was 1.38 and 1.27 tons.ha-1, respectively, while Grobogan in Ustic Epiaquerts 1.24 tons.ha-1. Dering I showed the mean of the highest yield and most suitable in all soil types, while Gema showed the mean of the lowest yield and not suitable in all soil types. Soil quality parameters that had a significant influenced on the production of soybean varieties in agroforestry systems with kayu putih were chemical characteristic consisting of availability of P, Mg, NH4 +, Mn and Ca.

The genotype–environment interaction causes difficulties in selecting stable and ideal soybean cultivars across crop rotation models. Thus, this study aimed to provide the best estimates of soybean yields in every crop rotation model for recommendations in the rainfed agroforestry system using GGE biplot and EBLUP. In this study, the productivity and stability of 15 soybean cultivars were evaluated using four crop rotation models, that is, soybean planting after fallow (F–S), soybean planting after maize (M–S), soybean planting after rice (R–S), and continuous soybean (S–S) in dry and wet seasons at Menggoran Forest Resort, Playen District, Gunungkidul Regency, Special Province of Yogyakarta, Indonesia. Results in the dry season revealed that the Dering I cultivar had the highest yield in F–S and R–S of 1.267 and 1.375 tons ha⁻¹ and the Grobogan cultivar in M–S and S–S of 1.200 and 1.349 tons ha⁻¹, respectively. During the wet season, the Grobogan cultivar showed the highest yields in F–S, M–S, and S–S of 2.187, 2.435, and 2.247 tons ha⁻¹, and the Dega I cultivar in R–S of 2.049 tons ha⁻¹. Based on the GGE biplot and Shukla model, Dering I and Grobogan cultivars were classified as fairly and relatively stable in dry and wet seasons. The cultivars that are well suited to the environment can maximize the yield potential of these cultivars and help to build a sustainable production system.

Silviculture agroforestry regime (SAR), which is a compatible management with forest rehabilitation and also renewal zoning system of the national park, was started to increase the agroforestry productivity surrounding Gunung Merapi National Park (GMNP). In addition, SAR also supported the basic information succession of Mount Merapi eruption in 2006 to strengthen Merapi lava tour. This is an innovative step in developing GMNP, in which its pro-poor conservation is not only based on land productivity, but also based tourism. This study was begun with the development of a permanent plot to study succession (May 2008-Novemper 2009), and the impact of community intervention on grass stock at GMNP, as well as to assess agroforestry typology and its implication on the areas surrounding GMNP. SAR was developed using landuse model based on limiting the factor of each agroforestry cluster. Choosing the treatment in SAR refers to the actual condition and opportunity every agroforestry cluster and sensitivity analysed until the intervention on the GMNP was minimal. The implementation of SAR was done with a software known as Stella 9.0. There are five SAR models which are appropriate for agroforestry cluster (AF); these are labelled as AF1-SAR1, AF2-SAR2, AF3-SAR3, AF4-SAR4 and AF5-SAR5. SAR is based on resources sharing whereby space is arranged through crown pruning and also rationalization number of dairy cows. In addition, SAR has a packet management for synergizing function of private lands (homegarden, dry field and land village as a unit management) and intensification by land tillage, renewal of grass and fertilization. In particular, SAR1-5 has the ability to balance agroforestry management with decreasing local community intervention and increasing biodiversity level on GMNP. The ratio for grass productivity outside GMNP with grass necessity and implementation of SAR was close to an optimum point (1). Meanwhile, the ratio values of SAR1-5 were 0.982, 1.010, 1.44, 1.047 and 1.253, respectively. Nonetheless, the implementation of SAR needs more technology of silviculture agroforestry and a full support from stakeholders.