Soybean varieties suitability in agroforestry system with kayu putih under influence of soil quality parameters 1 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, NH 4 + , Mn and Ca.

<p>The existence of genotype and environment (G x E) interaction causes difficulty in selecting suitable varieties of soybean in an agroforestry system based on <em>kayu putih</em> stands. This study aimed to determine the suitability of adaptive, stable and high yield soybean varieties in an agroforestry system based on <em>kayu putih</em> stands by using GGE-Biplot analysis. The experiment was conducted from May to August 2018 at Menggoran Forest Resort, Playen District, Gunung Kidul Regency, Special Region of Yogyakarta, Indonesia. The experiment was conducted using a randomized complete block design (RCBD) with five block as replications. The first factor was soil type in Menggoran Forest Resort, consisting of Lithic Haplusterts, Vertic Haplustalfs and Ustic Endoaquerts. The second factor was soybean varieties, consisting of Anjasmoro, Argomulyo, Burangrang, Dering I, Devon I, Gema and Grobogan. The observation was carried out on seed dry weight of soybean per hectare. The data were analyzed using Combined Analysis of Variance (ANOVA) with α = 5% and GGE-Biplot. Dering I was the most suitable varieties in an agroforestry system based on <em>kayu putih</em> stands and showed the mean of highest yield of 1.22 tons ha^-1.</p>

Climate change also has an impact on agriculture, especially at Mediterranean red-yellow soil which is characterized with low fertility. The application of biochar is an alternative to increase soil fertility, as well as promoting the growth and yield of maize in red-yellow Mediterranean soil. The study aimed it determining the appropriate type and dose of biochar in red-yellow Mediterranean soil to support the growth of hybrid maize. The study used a factorial Randomized Completely Block Design (RCBD) with two factors. The first factor was the type of biochar which consisted of 3 levels, namely coconut shell biochar (B1), rice husk biochar (B2), and maize cob biochar (B3). The second factor was the dose of biochar which consists of 5 levels, namely 0 ton.ha−1 (D0), 5 ton.ha−1 (D1), 10 ton.ha−1 (D2), 15 ton.ha−1 ( D3), and 20 ton.ha−1 (D4). The analysis of variance (ANOVA) continued with the Duncan’s Multiple Range Test (DMRT) at level 5% were employed for data analysis. The results showed that the application of biochar had a significant effect on the growth of hybrid maize, especially on some observational variables. The application of biochar rice husks significantly affected the stem diameter, leaves number, and dry weight of 7 week after plant (WAP). The dose of 15 tons.ha−1 significantly affected the dry weight of 4 WAP, while the interaction of rice husk biochar with a dose of 15 tons.ha−1 significantly affected the leaves width.

The research aims to study the change of morphology root characters of eight hybrid oil palms under iron toxicity (Fe). Field experiment done in arranged in a Randomized Complete Block Design (RCBD) two factors and three blocks as replications. The first factor was Fe concentration. It consists of two levels which are concentration 0µ.g-1 and concentration 600 µg.g-1 Fe. The second factor is the hybrid of oil palms which consists of eight hybrid oil palms as Yangambi, Avros, Langkat, PPKS 239, Simalungun, PPKS 718, PPKS 540 and Dumpy. Fe was applied by pouring FeSO4 solvent for 600 µg.g-1 500 ml.-1plant.-1day-1 on two months of plants after transplanting in the main nursery. Data were collected on root morphology and plant dry weight The data were analysis of variance (ANOVA) at 5% significanly, followed by Duncan's multiple range test (DMRT). The relationships by among variables were determined by correlation analysis. The results showed that Fe concentration 600 µg.g-1 inhibits relatively root growth rate, narrows surface area, reduces the diameter, and shrinks root volume of all hybrid oil palms tested. The slowing relatively root growth rate, narrowing of root surface area and root diameter also root volume shrinkage due to Fe stress. It was also shown that the dry weight of plants was inhibit by existing of Fe toxicity.

Evironmental indicators are the elements required to plan sustainable forest management practices. This assessment was carried out based on indicators that are sensitive to management and changes in the soil, climate, and associated functions. This study aims at determining soil quality and climate that affect the production of signalgrass silvopasture system in mountain ecosystems. The survey-based study was conducted during dry and wet seasons in 2017-2018. We used stratified random sampling method. Stratification was based on site (agroforestry phase) and environment (season and year). Site nested on environment. Agroforestry phases consisted of initial phase (<50% of the shade intensity of the sun), intermediate phase (50-70% of the shade intensity of the sun), and advanced phase (>70% of the shade intensity of the sun). Seasons were divided into two, dry season (rainfall < 60 mm.month-1) and wet season (rainfall > 100 mm.month-1) and years were limited from 2017 to 2018. The observation was conducted on 30 environmental parameters and signalgrass productions. The data was analyzed using linear mixed models, analysis of variance (ANOVA), structural equation modelling (SEM), and stepwise regression. The study results indicate that the highest signalgrass production at the initial agroforestry phase was 4.50 tons.ha-1. There is a very significant decrease in signalgrass production at the intermediate agroforestry phase by 36.64 % and at the advanced agroforestry phase by 280.80 %, compared to the initial agroforestry phase. The signalgrass production was increased very significantly influenced by the increase in cation exchange capacity (CEC), soil organic carbon (SOC), air temperature (Tair), and wind speed (U2). In addition, it was also significantly influenced by available nitrate (NO3-). Signalgrass production can be improved by the assessment tools by improving CEC, NO3-, SOC, U2 , and Tair with routine organic matters application and annual pruning.