Are microplastics correlated to phthalates in facility agriculture soil?

2021 ◽  
Vol 412 ◽  
pp. 125164
Author(s):  
Qinglan Li ◽  
Anrong Zeng ◽  
Xin Jiang ◽  
Xueyuan Gu
Keyword(s):  

The article deals with the distribution of agricultural periodicals on the territory of the Russian Em-pire in the early twentieth century. Before that there were practically no publications on the pages of sci-entific magazines. Great emphasis is placed on the analysis of agricultural magazines published before 1917 in the Upper Volga region, namely in Vladimir, Kostroma, Tver and Yaroslavl provinces. Thanks to existed in pre-revolutionary Russian periodicals on agricultural subjects advanced knowledge of agron-omy, agriculture, soil science, horticulture, fruit growing, vegetable growing, winemaking, viticulture, 135 tobacco growing, livestock, poultry, bee-keeping, veterinary medicine, forestry, and hunting, land man-agement, irrigation, horse breeding were promoted. On the basis of statistical data, office documentation and other published sources, the author draws conclusions about the degree of accessibility of agricul-tural periodicals for the population, including the peasantry. Availability of agricultural periodicals largely depended on its price, so the author studied the situation with the cost of the annual subscription fee of these publications. The article investigates the issues of periodicity of agricultural magazines and newspapers, the exact number of such publications, as well as their subject matter. Existence duration of different types of periodicals is analyzed, the main publishers of magazines and newspapers, places of their publication are revealed. A prominent place is given to the publishing activities of agricultural pub-lic organizations and zemstvo self-government bodies. It is concluded that natural process of agricultural knowledge distribution among the population of Russia through publications on the pages of periodicals was disrupted by revolutionary events of 1917.


Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 971
Author(s):  
Matilde Ciani ◽  
Antonio Lippolis ◽  
Federico Fava ◽  
Liliana Rodolfi ◽  
Alberto Niccolai ◽  
...  

Current projections estimate that in 2050 about 10 billion people will inhabit the earth and food production will need to increase by more than 60%. Food security will therefore represent a matter of global concern not easily tackled with current agriculture practices and curbed by the increasing scarcity of natural resources and climate change. Disrupting technologies are urgently needed to improve the efficiency of the food production system and to reduce the negative externalities of agriculture (soil erosion, desertification, air pollution, water and soil contamination, biodiversity loss, etc.). Among the most innovative technologies, the production of microbial protein (MP) in controlled and intensive systems called “bioreactors” is receiving increasing attention from research and industry. MP has low arable land requirements, does not directly compete with crop-based food commodities, and uses fertilizers with an almost 100% efficiency. This review considers the potential and limitations of four MP sources currently tested at pilot level or sold as food or feed ingredients: hydrogen oxidizing bacteria (HOB), methanotrophs, fungi, and microalgae (cyanobacteria). The environmental impacts (energy, land, water use, and GHG emissions) of these MP sources are compared with those of plant, animal, insect, and cultured meat-based proteins. Prices are reported to address whether MP may compete with traditional protein sources. Microalgae cultivation under artificial light is discussed as a strategy to ensure independence from weather conditions, continuous operation over the year, as well as high-quality biomass. The main challenges to the spreading of MP use are discussed.


2017 ◽  
Vol 9 (2) ◽  
pp. 310 ◽  
Author(s):  
Avanthi Igalavithana ◽  
Sang Lee ◽  
Nabeel Niazi ◽  
Young-Han Lee ◽  
Kye Kim ◽  
...  

2021 ◽  
Author(s):  
◽  
Jane Marie Niemeyer

A historical analysis of precipitation using 72 years of data from Midwest stations focuses on the implications of climate change for agricultural interests. The number of precipitation events, consecutive days of precipitation, and a Fourier transformation on precipitation are included. Although increased precipitation can be of benefit in agricultural production resulting in yield benefits in the Midwest, excessive rainfall events lead to runoff, which does not improve soil water content and plant available water. To examine the beneficial nature of rainfall events in the Midwest, rainfall retention is estimated using the United States Department of Agriculture Soil Conservation Service (USDA-NRCS/SCS) method. This method can be described briefly as an empirical formula estimating the soil's ability to store water and the amount of runoff. It was found that not only has rainfall increased but so have the number of rainfall days and the number of consecutive days of rainfall. To appricultural focus, spring and fall rainfall days were also found to increase implying that farmers may have fewer days to complete fieldwork in the current climate. With increasing precipitation, the potential for runoff also increases, losing valuable water needed for crops and contributing to lost nutrients in the soil.


2018 ◽  
Vol 4 (10) ◽  
pp. 5
Author(s):  
Smriti Singhatiya ◽  
Dr. Shivnath Ghosh

Now-a-days there is a need to study the nutrient status in lower horizons of the soil. Soil testing has played historical role in evaluating soil fertility maintenance and in sustainable agriculture. Soil testing shall also play its crucial role in precision agriculture. At present there is a need to develop basic inventory as per soil test basis and necessary information has to be built into the system for translating the results of soil test to achieve the crop production goal in new era. To achieve this goal artificial intelligence approach is used for predicting the soil properties.  In this paper for analysing these properties support vector regression (SVR), ensembled regression (ER) and neural network (NN) are used. The performance is evaluated with respect to MSE and RMSE and it is observed that ER outperforms better with respect to SVR and NN.


2021 ◽  
Author(s):  
Vishal Kumar ◽  
Raushan Kumar ◽  
Shubham Kumar ◽  
Ajinkya . ◽  
P. P. Jorvekar

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