Impact of Polyethylene on Soil Physicochemical Properties and Characteristics of Sweet Potato Growth and Polyethylene Absorption

2021 ◽  
Author(s):  
Liang Shi ◽  
Yanan Hou ◽  
Zanming Chen ◽  
Yuan Bu ◽  
Xiyang Zhang ◽  
...  
Keyword(s):  
Physicochemical Properties ◽  
Sweet Potato ◽  
Soil Physicochemical Properties ◽  
Potato Growth

scholarly journals Effect of Low Zeolite Doses on Plants and Soil Physicochemical Properties

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2617
Author(s):  
Alicja Szatanik-Kloc ◽  
Justyna Szerement ◽  
Agnieszka Adamczuk ◽  
Grzegorz Józefaciuk
Keyword(s):  
Plant Growth ◽  
Physicochemical Properties ◽  
Cation Exchange ◽  
Surface Area ◽  
Cation Exchange Capacity ◽  
N Fertilization ◽  
Exchange Capacity ◽  
First Year ◽  
Soil Physicochemical Properties ◽  
Water Holding

Thousands of tons of zeolitic materials are used yearly as soil conditioners and components of slow-release fertilizers. A positive influence of application of zeolites on plant growth has been frequently observed. Because zeolites have extremely large cation exchange capacity, surface area, porosity and water holding capacity, a paradigm has aroused that increasing plant growth is caused by a long-lasting improvement of soil physicochemical properties by zeolites. In the first year of our field experiment performed on a poor soil with zeolite rates from 1 to 8 t/ha and N fertilization, an increase in spring wheat yield was observed. Any effect on soil cation exchange capacity (CEC), surface area (S), pH-dependent surface charge (Qv), mesoporosity, water holding capacity and plant available water (PAW) was noted. This positive effect of zeolite on plants could be due to extra nutrients supplied by the mineral (primarily potassium—1 ton of the studied zeolite contained around 15 kg of exchangeable potassium). In the second year of the experiment (NPK treatment on previously zeolitized soil), the zeolite presence did not impact plant yield. No long-term effect of the zeolite on plants was observed in the third year after soil zeolitization, when, as in the first year, only N fertilization was applied. That there were no significant changes in the above-mentioned physicochemical properties of the field soil after the addition of zeolite was most likely due to high dilution of the mineral in the soil (8 t/ha zeolite is only ~0.35% of the soil mass in the root zone). To determine how much zeolite is needed to improve soil physicochemical properties, much higher zeolite rates than those applied in the field were studied in the laboratory. The latter studies showed that CEC and S increased proportionally to the zeolite percentage in the soil. The Qv of the zeolite was lower than that of the soil, so a decrease in soil variable charge was observed due to zeolite addition. Surprisingly, a slight increase in PAW, even at the largest zeolite dose (from 9.5% for the control soil to 13% for a mixture of 40 g zeolite and 100 g soil), was observed. It resulted from small alterations of the soil macrostructure: although the input of small zeolite pores was seen in pore size distributions, the larger pores responsible for the storage of PAW were almost not affected by the zeolite addition.

The effects of biochar addition on soil physicochemical properties: A review

CATENA ◽  
2021 ◽  
Vol 202 ◽  
pp. 105284
Author(s):  
Yafu Zhang ◽  
Jinman Wang ◽  
Yu Feng
Keyword(s):  
Physicochemical Properties ◽  
Soil Physicochemical Properties

Soil physicochemical properties and bacterial community composition jointly affect crop yield

2020 ◽  
Vol 112 (5) ◽  
pp. 4358-4372
Author(s):  
Meiqi Chen ◽  
Jisheng Xu ◽  
Zengqiang Li ◽  
Bingzi Zhao ◽  
Jiabao Zhang
Keyword(s):  
Bacterial Community ◽  
Physicochemical Properties ◽  
Community Composition ◽  
Crop Yield ◽  
Bacterial Community Composition ◽  
Soil Physicochemical Properties

Correlation of pH on Soil Physicochemical Properties using Linear Regression Model for Spectral Data Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 3492-3500
Author(s):  
Vipin Y. Borole ◽  
◽  
Sonali B. Kulkarni ◽  
Keyword(s):  
Linear Regression ◽  
Plant Growth ◽  
Physicochemical Properties ◽  
Regression Model ◽  
Soil Properties ◽  
Spectral Data ◽  
Linear Regression Model ◽  
Soil Analysis ◽  
Soil Physicochemical Properties ◽  
Analytical Technique

Soil properties may be varied by spatially and temporally with different agricultural practices. An accurate and reliable soil properties assessment is challenging issue in soil analysis. The soil properties assessment is very important for understanding the soil properties, nutrient management, influence of fertilizers and relation between soil properties which are affecting the plant growth. Conventional laboratory methods used to analyses soil properties are generally impractical because they are time-consuming, expensive and sometimes imprecise. On other hand, Visible and infrared spectroscopy can effectively characterize soil. Spectroscopic measurements are rapid, precise and inexpensive. Soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. In the present research, we use spectroscopy techniques for soil properties analysis. The spectra of agglomerated farming soils were acquired by the ASD Field spec 4 spectroradiometer. Different fertilizers treatment applied soil samples are collected in pre monsoon and post monsoon season for 2 year (4 season) for banana and cotton crops in the form of DS-I and DS-II respectively. The soil spectra of VNIR region were preprocessed to get pure spectra. Then process the acquired spectral data by statistical methods for quantitative analysis of soil properties. The detected soil properties were carbon, Nitrogen, soil organic matter, pH, phosphorus, potassium, moisture sand, silt and clay. Soil pH is most important chemical properties that describe the relative acidity or alkalinity of the soil. It directly effect on plant growth and other soil properties. The relationship between pH properties on soil physical and chemical parameters and their influence were analyses by using linear regression model and show the performance of regression model with R2 and RMSE. Keywords soil; physicochemical properties; spectroscopy; pH

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