PENDUGAAN TINGGI TANAMAN KAYU PUTIH (Melaleuca Cajuputi) UNTUK EVALUASI PERTUMBUHAN TANAMAN REHABILITASI DAS

Intercropping kayu putih ( Melaleuca cajuputi ) has more advantage than other tree crops, such as teak, pine or acacia due to the beneficial intercropping season length. Soybean was intercropped with kayu putih because soybean has higher commercial value than other field crops. The survey-based research was conducted during March until May, 2014 in Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District. Stratified random sampling method was used during the research by stratifying the types of soil stratification (alfisol and vertisol), rainfall and declivity then was made into 7 land mapping unit (LMU) with map overlay technique. Agronomic characters of soybean were observed on 12 weeks after planting (wap) and the physiological data were observed during the maximum vegetative phase (8 wap). Agronomic and physiological characters of soybean in each LMU were grouped and statistically tested with analysis of variance (ANOVA) then continued with orthogonal contrasts (alpha 5%). The results showed that some characters of soybean planted in alfisol had higher value than in vertisol, especially on leaf area, photosynthetic rate, root and canopy weight, 100 grain weight and grain weight per plant. The agronomic and physiological characters of soybean which had significant effects on yield in the intercropping with kayu putih system were stomatal density, stomatal conductivity, photosynthetic rate, and leaf area. Soybean intercropped with kayu putih produced 1.007 tons/ha in alfisol and 0.996 tons/ha in vertisol. Soybean development in intercropping system of kayu putih can be conducted by using soybean varieties superior effort.

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.

Abstract. 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.

Abstract. Taryono, Supriyanta, Wulandari RA, Nurmansyah, Ambarwati E, Arsana IGKD, Aristya VE, Purba AE, Aisya AW, Alam T. 2023. Selection of drought-tolerant rice genotypes under cajuput (Melaleuca cajuputi subsp. cajuputi) agroforestry system. Biodiversitas 24: 4791-4802. Rice production can be increased by expanding rice cultivation area on agroforestry land. However, planting rice in agroforestry system, which is generally rainfed, might cause drought stress and eventually can reduce rice yields. The study aimed to select rice genotypes under drought stress conditions in a rainfed agroforestry system with cajuput or kayu putih (Melaleuca cajuputi subsp. cajuputi Powell). Ten promising rice lines and four control cultivars were grown during the dry season from March-July 2022 at the Menggoran Forest Management Resort, Playen Forest Section, Yogyakarta Forest Management, Indonesia. The observation was conducted on drought stress tolerance (sensitivity and recovery), molecular identification, and yield of rice cultivars. The results showed that G5 was the genotype with drought tolerance and had the best recovery compared to the other promising rice lines and control cultivars. The molecular identification of the 14 rice genotypes using 20 SSR markers detected 108 alleles with a PIC value of 0.707. The G5, G4, and G9 had higher yields than the control cultivars. The BLUE showed that the yield of G5, G4, and G9 were 6.59, 5.93 and 5.50 tons ha-1, respectively, while for BLUP by 6.45, 5.87 and 5.43 tons ha-1, respectively. Furthermore, there were four clusters consisting of cluster 1 (G9), cluster 2 (G7), cluster 3 (G5 and Inpago 12), and cluster 4 (Inpari 42, G6, Inpari 30 Ciherang Sub 1, Situ Bagendit, G3, G4, G10, G2, G1, and G8). The findings of this study recommend G4, G5, and G9 as promising rice lines which tolerant to drought stress under M. cajuputi agroforestry system and can be utilized in future plant breeding programs.

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 [...]

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, Taryono, Supriyanta, Kastono D, Putra ETS, Widyawan MH, Alam T. 2020. Assessment of soil quality parameters and yield of rice cultivars in Melaleuca cajuputi agroforestry system. Biodiversitas 21: 3463-3470. Interactions between rice cultivars and soil quality parameters rises problems in the attempt of increasing rice yield. The objective of this study was to assess soil quality parameters that affect the yield of 15 rice cultivars in an agroforestry system of ‘kayu putih’ (Melaleuca cajuputi) situated in Menggoran forest, Yogyakarta, Indonesia which have three soil types namely Lithic Haplusterts, Ustic Epiaquerts, and Vertic Haplustalfs. The observation was conducted on 21 soil quality parameters and yield of rice cultivars. The data were analyzed by using ANOVA, factor analysis, and stepwise regression. The highest yield of rice per hectare was attained by GM 28 in Ustic Epiaquerts with 6.493 tons ha-1, while Situ Patenggang and GM 28 in Vertic Haplustalfs as high as5.549 and 5.401 tons ha-1, respectively, and Situ Patenggang in Lithic Haplusterts as high as 4.893 tons ha-1. Soil quality parameters that had significant effect on the yield of rice cultivars were Clay, SMC, pH, SOC, N, Mg, Fe, Fg, and Bae. We suggested that rice cultivars recommendations for Lithic Haplusterts, Ustic Epiaquerts, and Vertic Haplustalfs are Situ Patenggang, Situ Patenggang or GM 28, and GM 28, respectively, in addition to fertilization based on limiting factors of each rice cultivars.

The intracranial pressure (ICP) is usually continuously monitored in the management of patients with increased ICP. The aim of this study was to discover a mathematic equation to express the intracranial pressure-volume (P-V) curve and a single indicator to reflect the status of the curve. Patients with severe brain damage who had bilateral external ventricular drainage (EVD) from December 2008 to February 2010 were included in this study. The EVD was used as drainage of CSF and ICP monitor. The successive volume pressure response [6] values were obtained by successive drainage of CSF from ICP 20-25 to 10 mmHg. Parabolic, exponential, and linear regression models were designed to have a single parameter as the indicator to determine the P-V curves. The mean of parameter "a" in the exponential equation is 1.473 ± 0.054; in the parabolic equation, it is 0.332 ± 0.061; and in the linear equation, it is 1.717 ± 0.209. All regression equations of P-V curves had statistical significance (p < 0.005). Parabolic and exponential equations are closer to the original ICP curve than linear equation (p < 0.005). There is no statistically significant difference between parabolic and exponential regressions. The P-V curve can be expressed with linear, parabolic, and exponential regression models in increased ICP patients. The parabolic and exponential equations are more accurate methods to represent the P-V curve. The single parameter in the three regression equations can be compared in different conditions of one patient in clinical practice.

A study was carried out at the University of Zimbabwe Farm, to assess and quantify the correlation between plant canopy height and biomass in the rangelands of Zimbabwe. Two range sites, bush grassland and grassland, were selected and three paddocks within each range site were sampled. Four 25 m long transects were drawn in the four cardinal directions from the paddock center. Five 0.25 m2 quadrants were located at 5 m intervals on each transect line. Common plant species in both bush grassland and grassland range sites were Sporobolus pyramidalis, Hyparrhenia filipendula, Cynodon dactylon, and Eragrostis curvula. There was a significant (P<0.05) linear relationship between plant height and biomass for both range sites. There was a significant (P>0.05) quadratic relationship between plant height and biomass for grassland but not for the bush grassland. Pearson Correlation Coefficient (r) was 0.929 for grassland and 0.717 for bush grassland. The regression equation was y = 15.82x – 0.02x2 for bush grassland and y = 15.88x – 0.27x2 for grassland. The coefficient of determination (r2) for grassland was 0.863 and 0.514 for bush grassland. Variation in plant height explained 86.3% of the variation in biomass for grassland and 51.4% for bush grassland accordingly.

The results of a two-year study (2013–2014) of the variation in plant height of spring common wheat hybrid forms (F4 and F5) in three geographical localities in Russia (Tyumen oblast) and Germany (Baden-Wurttemberg and Lower Saxony) considerably differing in soil and climatic conditions are described. These three localities are characterized according to temperature and water availability during the growth seasons of the spring wheat. The differences between the geographical localities in water supply and aridity during two growth seasons (2013–2014) were assessed using Selyaninov’s hydrothermal coefficient (HTC). The plant height of different hybrids differently responded to changing environmental factors. A moderate degree of height variation (CV = 11–25%) was prevalent among the tested hybrids. The hybrid forms displaying the largest range in plant height within a locality were identified. The morphotypes of the hybrids were represented by undersized and medium-sized plants. The hybrids formed higher plants under conditions of sufficient moisture. The contributions of the major factors (site, year, and genotype) to the formation of plant height were assessed by three-way ANOVA. The results of this analysis demonstrate that environmental conditions of particular localities are responsible for the largest part of the explained variation in the studied variable (plant height). Two hybrid forms (♀ Hybrid × ♂Lutescens 70 and ♀ Cara × ♂Skent 3) with the least expressed variation in plant height and the highest lodging resistance were identified. Plant height is regarded as one of the indicators characterizing the environmental plasticity of genotypes under different soil and climatic conditions.

The relationship between migration and fertility has vexed demographers for years. One issue missing in the literature is the lack of careful temporal consideration of when women migrate and specifically, the extent to which they do either before or after live births. Here, we opt for a more appropriate methodological approach to help remedy the complexity of the temporal aspect of migration and childbirth processes: regression models using the episode-splitting method. This paper applies a rarely used methodological approach (episode-splitting) in the literature of migration-fertility relationship to investigate how internal in-migration is associated with inter-birth intervals among women in Cotonou, the largest city of Benin. Data comes from the 2017-2018 Benin Demographic and Health Survey (DHS) of women aged 15-49. Estimates from exponential regression models with episode-splitting were compared to estimates from exponential regression models without episode-splitting approach. Sensitivity analysis was also conducted to determine the robustness of the comparison between the two methods. Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were used to identify the method that provides models with best fit. The results from (standard) exponential regression models without episode-splitting show that there is no significant association between migration and interbirth transition rate. However, significant associations between migration and interbirth transition rate emerge after applying the episode splitting method. The hazard ratios (HR) of the transition to the next live birth are higher among migrant women than among nonmigrant women. This trend is persistent even after 10 years spent in Cotonou by migrant women. Exponential regression models with episode-splitting were of better fit than exponential regression models without episode-splitting. Sensitivity analysis conducted seems to confirm that models with episode-splitting produce estimates that are accurate, reliable and superior to models without episode-splitting. The results suggest a long-run process adaptation of migrants to lower fertility behaviours in Cotonou and are therefore consistent with the socialization hypothesis.

The time series of synthetic aperture radar (SAR) data are commonly and successfully used to monitor the biophysical parameters of agricultural fields. Because, until now, mainly backscatter coefficients have been analysed, this study examines the potentials of entropy, anisotropy, and alpha angle derived from a dual-polarimetric decomposition of Sentinel-1 data to monitor crop development. The temporal profiles of these parameters are analysed for wheat and barley in the vegetation periods 2017 and 2018 for 13 fields in two test sites in Northeast Germany. The relation between polarimetric parameters and biophysical parameters observed in the field is investigated using linear and exponential regression models that are evaluated using the coefficient of determination (R2) and the root mean square error (RMSE). The performance of single regression models is furthermore compared to those of multiple regression models, including backscatter coefficients in VV and VH polarisation as well as polarimetric decomposition parameters entropy and alpha. Characteristic temporal profiles of entropy, anisotropy, and alpha reflecting the main phenological changes in plants as well as the meteorological differences between the two years are observed for both crop types. The regression models perform best for data from the phenological growth stages tillering to booting. The highest R2 values of the single regression models are reached for the plant height of wheat related to entropy and anisotropy with R2 values of 0.64 and 0.61, respectively. The multiple regression models of VH, VV, entropy, and alpha outperform single regression models in most cases. R2 values of multiple regression models of plant height (0.76), wet biomass (0.7), dry biomass (0.7), and vegetation water content (0.69) improve those of single regression models slightly by up to 0.05. Additionally, the RMSE values of the multiple regression models are around 10% lower compared to those of single regression models. The results indicate the capability of dual-polarimetric decomposition parameters in serving as meaningful input parameters for multiple regression models to improve the prediction of biophysical parameters. Additionally, their temporal profiles indicate phenological development dependent on meteorological conditions. Knowledge about biophysical parameter development and phenology is important for farmers to monitor crop growth variability during the vegetation period to adapt and to optimize field management.

Background: Soybean cultivars grown on various crop rotation models in the agroforestry system with kayu putih (Melaleuca cajuputi) have shown different yields per hectare. However, no information related to morpho-physiological and biochemical fingerprints affecting soybean yield has been found. Thus, this study aimed to determine the morpho-physiological and biochemical fingerprints and their effect on the soybean agroforestry system in different crop rotation models through multivariate analysis. Methods: The study was conducted during the dry season (March-June 2021) and the wet season (November 2021-February 2022) in Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The morpho-physiological and biochemical variables of 15 soybean cultivars were evaluated using four crop rotation models. Observations included 22 morphological, physiological and biochemical variables of soybean. Data were analyzed using ANOVA, PCA-biplot, heatmap cluster, factor analysis, SEM-PLS and standardized stepwise regression. Result: Results showed four groups of soybean cultivars and three groups of crop rotation models based on morpho-physiological and biochemical fingerprints. Morpho-physiological and biochemical fingerprints of soybean can be differentiated based on root surface area, nitrogen content and superoxide dismutase.

Abstract. Alam T, Suryanto P, Supriyanta, Basunanda P, Wulandari RA, Kastono D, Widyawan MH, Nurmansyah, Taryono. 2021. Rice cultivar selection in an agroforestry system through GGE-biplot and EBLUP. Biodiversitas 22: 4750-4757. Genotype-by-environment interaction (GEI) causes differences in the productivity of rice cultivars in agroforestry systems. For this reason, the stability of rice cultivars is an important aspect that should be considered before a cultivar is recommended to farmers. Superior genotypes and ideal environments are commonly identified using two statistical models, namely, genotype–genotype-by-environment biplot (GGE-biplot) and empirical best linear unbiased prediction (EBLUP). In this study, 15 rice cultivars were evaluated in terms of their productivity and stability in three soil types (Lithic Haplusterts, Ustic Epiaquerts, and Vertic Haplustalfs) in an agroforestry system with kayu putih (Melaleuca cajuputi) in 2019 and 2020 at the Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The cultivars were treated as random effects to select and obtain the EBLUP of the best cultivars in each soil type. The EBLUP revealed that Situ Patenggang showed the highest yields of 4.887 and 5.456 tons ha?1 in Lithic Haplusterts and Vertic Haplustalfs, respectively. GM 28 exhibited the highest yield of 6.492 tons ha?1 in Ustic Epiaquerts. Ciherang, GM 2, GM 8, GM 11, GM 28, Inpari 6 Jete, Inpari 33, IR-64, and Way Apo Buru were classified as stable and fairly stable cultivars, whereas the other cultivars were unstable. Therefore, rice cultivars with high yields in specific soil types should be selected.

Abstract. Alam T, Suryanto P, Handayani S, Supriyanta, Wulandari RA, Anshari A, Aisya AW, Purba AE, Widowati R, Taryono. 2022. Soil quality measurement for sustainable soybean yield agroforestry system under different crop rotation models. Biodiversitas 23: 6155-6163. Soil quality is essential for sustaining the soybean yield in an agroforestry system. This study determined the soil quality variables that affect soybean yield under different crop rotation models in the agroforestry system with kayu putih (Melaleuca cajuputi). A 2-year experiment was conducted during the dry season (March-June 2021) and the wet season (November 2021-February 2022) at Menggoran Forest Resort, Playen District, Gunungkidul Regency, Special Province of Yogyakarta, Indonesia. All of the trials during each season were laid out in a randomized complete block design with three blocks as replication. The treatment crop rotation model consisted of soybean planting after fallow (FS), soybean planting after maize (MS), soybean planting after rice (RS), and continuous soybean planting (SS). The observations were soybean yield and 21 soil quality variables. The data were analyzed using analysis of variance, multiple factor analysis, heatmap cluster, generalized pair plot, and standardized stepwise regression. The increase in soybean yield during the dry season was affected by TB, Fe, and N in the soil, while it was affected by TF, Fe, and silt during the wet season. Soil quality and soybean yield can be improved by applying organic matter and soil amendment.