Nest refuse of Acromyrmex balzani (Hymenoptera: Formicidae) increases the plant vigor in Turnera subulata (Turneraceae)

Some studies report the positive effect of organic residues from ant nests on soil properties and on the structure of the adjacent plant community in field experiments, but there is a gap about the effect on individual species. The purpose of the present study was to compare the soil nutrient content and the development of Turnera subulata Smith, an ornamental species, in the presence of the nest refuse (basically composed of fragments of grass leaves and the symbiotic fungus) produced by the leaf-cutting ant Acromyrmex balzani (Emery, 1890) or in control soil through a greenhouse pot experiment. The experiment was carried out with two treatments: control soil and soil with 25% of nest refuse. The plants were kept in 1L pots for 90 days. We evaluated the parameters: plant height, stem diameter, root length, number of leaves, dry weight of the root, dry and fresh aboveground biomass. Additionally, the relative chlorophyll content and leaf nutrients were used as nutritional parameters. As a result, plants that grew in the soil with nest refuse showed significant higher values of all parameters evaluated when compared to the control treatment (p < 0.001). We conclude that this biofertilizer contributed to the production of more vigorous plants, being able to act on the local dynamics of nutrients in the ecosystems where A. balzani occurs. As it is relatively abundant and easy to collect, the refuse of A. balzani has the potential to be used as an alternative substrate in the production of shortlife cycle plants.

Germplasm Screening of Green Manure Rapeseed through the Effects of Short-Term Decomposition on Soil Nutrients and Microorganisms

The rapidly emerging fertilizer rapeseed used as green manure has wide applications for use. However, there have been few studies on its decomposition and effects on soil nutrients and microorganisms after its decay. In this study, 12 rapeseed lines to be screened were decomposed through a randomized block field design with two green-manure-specific varieties as the controls. The contents of nitrogen, phosphorus, and potassium from the plants, soil nutrients, and microbial changes after degradation were measured. There were substantial differences in the rates of decomposition and cumulative release of nutrients among the different lines after 30 days of rolling. The contents of phosphorus and potassium in the soil were 1.23–2.03 and 3.93–6.32 times those before decomposition, respectively. In addition, there was a significant difference in the relative content of soil microorganisms at the phylum level after the decomposition of different species of rapeseeds. Most of the top 20 bacterial groups significantly correlated with the characteristics of plant decomposition and soil nutrient content, including Proteobacteria, Actinomycetes, Armatimonadetes, Rokubacteria, and Planctomycetes. A principal component analysis showed that the soil microorganisms and nutrients are the leading factors that enable the evaluation of the decomposing characteristics of green manure rapeseed. Numbers 5 (purple leaf mustard) and 8 (Xiafang self-seeding) were more effective than two controls, which can be used as excellent types of germplasm to promote the breeding of green manure rapeseed.

Factors Driving Wetland Herbs Distribution Range of Lake-Terrestrial Ecotone in Tibet, China

Background: Lake is a critical part of Tibet's hydrological cycle, the lake-terrestrial ecotone is the most sensitive area in the water and terrestrial ecosystem. For the ecological protection and maintenance of the lakeside zone, defining the upper boundary of the lake-terrestrial ecotone is a key issue that needs to be solved urgently. However, the ecological characteristics of lake-terrestrial ecotone made it diffcult to delimit. Wetland herbs are characteristic plants of the radiant belt toward the land of the lake-terrestrial ecotone, and their distribution range can be used to reflect the upper boundary of the lake-terrestrial ecotone. We took Baksum Lake, Yambdroktso, Namtso, Siling Co as examples, based on the spatial structure of the lake-terrestrial ecotone, used the moving split-window technology (MSWT) delimited the range of wetland herbs.Results:The results of MSWT showed the distribution range of wetland herbs in each lake-terrestrial ecotone with the natural-wetland type sampling line of Baksum Lake, Yambdroktso, Namtso, Siling Co was 51m, 56m, 33~53m, 19~31m. DCA showed number of wetland herbs species,BK1＞YT1=NT1＞NT2＞SC1=SC2. PCA, RDA showed SMO, pH, SSC, and soil nutrient content had obvious correlation with distribution range. Conclusion:MSWT was a feasible method to delimit the distribution range of wetland herbs. SMO, pH, SSC, and soil nutrient content were all-important environmental factors affect the wetland herbs distribution range of the four lakes, however, the SMO was the most important factor. Besides, compare with the lakes in the lower Yangtze Plain,the high-density population distribution,high-intensitive human activity invaded the plants' growth area, resulting in a smaller distribution range.

Estimation of Soil Nutrient Content Using Hyperspectral Data

Soil nutrients play a vital role in plant growth and thus the rapid acquisition of soil nutrient content is of great significance for agricultural sustainable development. Hyperspectral remote-sensing techniques allow for the quick monitoring of soil nutrients. However, at present, obtaining accurate estimates proves to be difficult due to the weak spectral features of soil nutrients and the low accuracy of soil nutrient estimation models. This study proposed a new method to improve soil nutrient estimation. Firstly, for obtaining characteristic variables, we employed partial least squares regression (PLSR) fit degree to select an optimal screening algorithm from three algorithms (Pearson correlation coefficient, PCC; least absolute shrinkage and selection operator, LASSO; and gradient boosting decision tree, GBDT). Secondly, linear (multi-linear regression, MLR; ridge regression, RR) and nonlinear (support vector machine, SVM; and back propagation neural network with genetic algorithm optimization, GABP) algorithms with 10-fold cross-validation were implemented to determine the most accurate model for estimating soil total nitrogen (TN), total phosphorus (TP), and total potassium (TK) contents. Finally, the new method was used to map the soil TK content at a regional scale using the soil component spectral variables retrieved by the fully constrained least squares (FCLS) method based on an image from the HuanJing-1A Hyperspectral Imager (HJ-1A HSI) of the Conghua District of Guangzhou, China. The results identified the GBDT-GABP was observed as the most accurate estimation method of soil TN ( of 0.69, the root mean square error of cross-validation (RMSECV) of 0.35 g kg−1 and ratio of performance to interquartile range (RPIQ) of 2.03) and TP ( of 0.73, RMSECV of 0.30 g kg−1 and RPIQ = 2.10), and the LASSO-GABP proved to be optimal for soil TK estimations ( of 0.82, RMSECV of 3.39 g kg−1 and RPIQ = 3.57). Additionally, the highly accurate LASSO-GABP-estimated soil TK (R2 = 0.79) reveals the feasibility of the LASSO-GABP method to retrieve soil TK content at the regional scale.

Evaluating Calibration and Spectral Variable Selection Methods for Predicting Three Soil Nutrients Using Vis-NIR Spectroscopy

Soil nutrients, including soil available potassium (SAK), soil available phosphorous (SAP), and soil organic matter (SOM), play an important role in farmland soil productivity, food security, and agricultural management. Spectroscopic analysis has proven to be a rapid, nondestructive, and effective technique for predicting soil properties in general and potassium, phosphorous, and organic matter in particular. However, the successful estimation of soil nutrient content by visible and near-infrared (Vis-NIR) reflectance spectroscopy depends on proper calibration methods (including preprocessing transformation methods and multivariate methods for regression analysis) and the selection of appropriate variable selection techniques. In this study, raw spectrum and 13 preprocessing transformations combined with 2 variable selection methods (competitive adaptive reweighted sampling (CARS) and the successive projections algorithm (SPA)) and 2 regression algorithms (support vector machine (SVM) and partial least squares regression (PLSR)), for a total of 56 calibration methods, were investigated for modeling and predicting the above three soil nutrients using hyperspectral Vis-NIR data (400–2450 nm). The results show that first-order derivatives based on logarithmic and inverse transformations (FD-LGRs) can provide better predictions of soil available potassium and phosphorous, and the best form of soil organic matter transformation is SG+MSC. CARS was superior to the SPA in selecting effective variables, and the PLSR model outperformed the SVM models. The best estimation accuracies (R2, RMSE) for soil available potassium, phosphorous, and organic matter were 0.7532, 32.3090 mg/kg; 0.7440, 6.6910 mg/kg; and 0.9009, 3.2103 g/kg, respectively, and their corresponding calibration methods were (FD-LGR)/SPA/PLSR, (FD-LGR)/SPA/PLSR, and SG+MSC/CARS/SVM, respectively. Overall, for the prediction of the soil nutrient content, organic matter was superior to available phosphorous, followed by available potassium. It was concluded that the application of hyperspectral images (Vis-NIR data) was an efficient method for mapping and monitoring soil nutrients at the regional scale, thus contributing to the development of precision agriculture.

THE EFFECT OF BIOGAS WASTE ON NUTRIENT CONTENTS AND MUSTARD PLANTS ( BRASSICA JU NCEA L.) PERFORMANCES

The aim of research to determine the effect of sludge that mixed with plant waste and livestock waste on soil nutrient content and Brassica L. performances The research method used was the experiment of adding local microorganism solution (LMS) of banana weevil, coconut fiber ash and eggshell flour into sludge of quail and octopus waste as organic fertilizer with a completely randomized design (CRD) method with 6 treatments and 4 replications The treatments used consisted of P0: sludge 100%; P1 :sludge 50% + LMS 20% + Ash 10% + Eggshell Flour 20%; P2: sludge 50% + LMS 20% + Ash 12.5% ​​+ Eggshell Flour 17.5%; P3: sludge 50% + LMS 20% + Ash 15% + Eggshell Flour 15%; P4: sludge 50% + LMS 20% + Ash 17.5% + Eggshell Flour 12.5% and P5: sludge 50% + LM S 20% + Ash 20% + Eggshell Flour 10%. The result showed that the treatment given had a very significant effect (P &lt;0.01) on the total N content, elements P and K, but the highest average was obtained from P0 (100% sludge), so it can be concluded that had no effect on nutrient content. The average of total N values ​​ranged from 1.15 ± 0.10 to 2.39 ± 0.40 percent, element P ranges from 2.65 ± 0.19 to 5.28 ± 0.19 percent and element K ranges from 1.08 ± 0.05 to 4.28 ± 0.21 percent. And for Brassica L. this treatment give a real effect (P &lt;0.01) to the height and weight of a mustard plant wet and did not give an effect (P &lt;0.05) to the number of leaves of mustard plants. The conclusion of this study are the mixed sludge waste had a significant effect on soil nutrient content and on Brassica L. performance.

KEANEKARAGAMAN ORGANISME PADA RHIZOSFER GULMA SIAM DI LAHAN VULKANIK, PESISIR, DAN KARST

Penelitian ini bertujuan untuk membandingkan kondisi edafik, hubungan antara kondisi edafik dan keanekaragaman organisme tanah, serta perbedaan keanekaragaman organisme tanah pada berbagai ekosistem rhizosfer gulma Siam (Chromolaena odorata) yang tumbuh di lahan vulkanik, pesisir, dan karst. Penelitian dilakukan dengan mengambil sampel tanah dari ekosistem rhizosfer gulma Siam di lahan vulkanik, karst, dan pesisir Daerah Istimewa Yogyakarta; mengamati komposisi organisme tanah di laboratorium, yaitu collembola, nematoda, dan mikoriza. Hasil penelitian menunjukkan bahwa tanah pada rhizosfer gulma Siam yang tumbuh di lahan karst menunjukkan tingkat kesuburan tertinggi yang ditunjukkan oleh kandungan N, K, dan C-organik tanah, sedangkan tanah pesisir memiliki kandungan P tertinggi. Tekstur tanah pada rhizosfer gulma Siam lebih berpengaruh terhadap keanekaragaman organisme tanah dibandingkan kandungan hara tanah dan sifat tanah lainnya yang diteliti. Keragaman organisme tanah rhizosfer gulma Siam lebih besar di lahan pesisir dibandingkan di lahan karst dan vulkanik. Implikasi dari hasil tersebut adalah bahwa tanah dengan tekstur berpasir akan lebih bermanfaat bagi pertumbuhan gulma Siam dengan keanekaragaman organisme rhizosfer yang lebih tinggi.ORGANISM DIVERSITY IN THE RHIZOSPHERE OF SIAM WEEDS IN VOLCANIC, COASTAL AND KARST LANDThe research aims to compare the edaphic condition, the relationship between the edaphic condition and soil organism diversity, and the differences of soil organism diversity in different rhizosphere ecosystems of Siam weed growing in volcanic, coastal and karts areas. The research was conducted by taking soil samples from the Siam weed rhizosphere ecosystems in volcanic, karst and coastal areas of the Special Region of Yogyakarta and observing the composition of the soil organisms in the laboratory, including collembola, nematode, and mycorrhiza. The results find that soil from rhizosphere of Siam weed growing in karst area shows the highest level of fertility indicated by the N, K, and C-organic contents of the soil, whereas soil from coastal area has the highest P content. Soil texture in the rhizosphere of Siam weed has more effect on the diversity of soil organisms than the soil nutrient content and other soil properties investigated. The diversity of soil organisms of Siam weed rhizosphere is greater in coastal area than those in karst and volcanic areas. The implication of the results is that soil with a sandy texture will be more beneficial for the growth of Siam weed with a higher diversity of rhizosphere organisms

Effects of Mineral-Solubilizing Microorganisms on Root Growth, Soil Nutrient Content, and Enzyme Activities in the Rhizosphere Soil of Robinia pseudoacacia

Background: Abandoned mining sites are becoming increasingly common due to anthropogenic activities. Consequently, external-soil spray seeding technology has attracted increasing attention as a strategy to remediate them. However, significant challenges remain that greatly inhibit the efficacy of such technologies, such as insufficient nutrients available for plants. Methods: For this study, we designed an experiment, which involved the addition of mineral-solubilizing microorganisms and R. pseudoacacia seedlings to the external-soil spray seeding (ESSS) substrate, and measured the soil nutrients, enzyme activities, and root growth of R. pseudoacacia. Results: First, the combination of certain mineral-solubilizing microorganisms with ESSS advanced its efficiency by increasing the availability of soil nutrients and soil enzymatic activities in association with R. pseudoacacia. Furthermore, the improvement of root growth of R. pseudoacacia was intimately related to soil nutrients, particularly for soil total nitrogen (TN) and total sulfur (TS). In general, the effects of the J2 (combined Bacillus thuringiensis and Gongronella butleri) treatment for soil nutrients, enzyme activities, and plant growth were the strongest. Conclusion: In summary, the results of our experiment revealed that these mineral-solubilizing microorganisms conveyed a promotional effect on R. pseudoacacia seedlings by increasing the soil nutrient content. These results provide basic data and microbial resources for the development and applications of mineral-solubilizing microorganisms for abandoned mine remediation.