scholarly journals Hydrochemical Characteristic of Groundwater and Its Impact on Crop Yields in the Baojixia Irrigation Area, China

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1443 ◽  
Author(s):  
Wenwen Feng ◽  
Hui Qian ◽  
Panpan Xu ◽  
Kai Hou
Keyword(s):  
Groundwater Quality ◽  
Crop Yield ◽  
Irrigation Water ◽  
Crop Yields ◽  
Economic Loss ◽  
Research Area ◽  
Rock Interaction ◽  
Factors Affecting ◽  
Irrigation Area ◽  
The Impact

While irrigated crops produce much higher yields than rain-fed crops, the ionic components of irrigation water have important effects on crop yield. Groundwater is widely used for irrigation in the Baojixia irrigation area in China. The chemical characteristics and water quality of groundwater in the Baojixia irrigation area were analyzed and evaluated to study the impact of groundwater quality on crop yield. Results showed cations in the groundwater to mainly be Na+, Ca2+, and Mg2+, whereas the anions are mainly HCO3−, SO42−, and Cl−. Water-rock interaction and cation exchange were identified as the main factors affecting hydrogeochemical properties from west to east. The study found salinity and alkalinity of groundwater in the western region of the study area to be low, and therefore suitable for irrigation. Groundwater in the eastern part of the study area was found to have a medium to high salinity and alkalinity, and is therefore not recommended for long-term irrigation. The groundwater irrigated cultivation of wheat and corn in the research area over 2019, for example, would have resulted in a drop in the annual crop output and an economic loss of 0.489 tons and 0.741 × 104 yuan, respectively. Irrigation using groundwater was calculated to result in the cumulative loss of crop yields and an economic loss of 49.17 tons and 80.781 × 104 yuan, respectively, by 2119. Deterioration of groundwater quality will reduce crop yields. It is recommended that crop yields in the study area be increased by strengthening irrigation water management and improving groundwater quality.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

scholarly journals The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Production ◽  
Yield Loss ◽  
Crop Yields ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Arable Farming ◽  
Herbicide Use ◽  
The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

WAYS TO MINIMIZE YIELD RISKS BASED ON THE DIVERSIFICATION OF PRODUCTION IN FARMS

2021 ◽  
Vol 4 (4) ◽  
pp. 86-93
Author(s):  
Dilmurod Baymirzaev ◽  
◽  
Nazira Khoshimova ◽  
Keyword(s):  
Crop Yield ◽  
Agricultural Crops ◽  
Factors Affecting ◽  
The Impact

The article deals with the issues of minimizing yield risks based on the diversification of production in farms. Crop yield risks in farms are described and quantified. The factors affecting the yield were analyzed. The correlation between the yield of agricultural crops, such as cotton and wheat, is determined and grouped. Proposals have been developed to minimize the impact of risks on farms.

scholarly journals The Factors of Deterioration of Natural Pastures From The View Point of Agricultural Employees in Al-Muthanna Governorate

2021 ◽  
Vol 923 (1) ◽  
pp. 012066
Author(s):  
Emad Fahad Nafeh Al-Bahli ◽  
Mahmoud Hadis Jassim Al-Jumaili
Keyword(s):  
Personal Characteristics ◽  
Research Area ◽  
Point Of View ◽  
Personal Factors ◽  
Factors Affecting ◽  
Work Location ◽  
Natural Factors ◽  
Significant Difference ◽  
The Impact ◽  
Selection Of

Abstract The research aimed to determine the impact studied factors represented by (people’s activities, government activities, natural factors) on the deterioration of natural pastures in the Governorate of Al-Muthanna the point of view of agricultural employees in the governorate. The research included all agricultural employees with a preparatory scientific qualification in agriculture and above in the governorate their number is (94) employees. A questionnaire was prepared to collect the data necessary to achieve the objectives of the research. It consisted of two parts. The first part included the factors related to the employees, which are (term of service, academic achievement, participation in extension activities, job position and work location). The second part included a measure to identify the agricultural employees’ the point of view of on the factors affecting the deterioration of natural pastures. It consists of (46) section spread over (3) field covered by the research. The results showed that government activities have the most impact on the deterioration of natural pastures, it was found a statistically significant difference in the respondents’ point of view about the influence of the studied factors according to their personal characteristics. The researchers concluded the necessity of agricultural expansion in pasture lands and industrial investments, as well as the importance of personal factors in assigning employees who can work in the development of natural pastures, and the researchers recommend activating government laws for the protection of natural pastures to prevent abuses (people’s activities, government activities) that contributed greatly to the deterioration of vegetation cover in the research area and taking into account the factors studied in the selection of workers in the development of natural pastures in the research area.

scholarly journals DAMPAK KENAlKAN BARGA MINYAK GORENG TERHADAP KELAYAKAN USAHA INDUSTRI RUMAH TANGGA KERIPIK TEMPE DI KECAMATAN RAWALO KABUPATEN BANYUMAS

Agro Ekonomi ◽  
2017 ◽  
Vol 15 (2) ◽  
Author(s):  
Altri Mulyani ◽  
Masyhuri Masyhuri ◽  
Ken Suratiyah
Keyword(s):  
Production Capacity ◽  
Research Area ◽  
Oil Price ◽  
Profit Function ◽  
Factors Affecting ◽  
Cooking Oil ◽  
Production Frequency ◽  
Unit Output ◽  
Home Industries ◽  
The Impact

The objectives are to know: (1) the impact of cooking oil price increasing to the feasibility of tempe chips home industry; (2) income decreasing of tempe chips home industry after cooking oil price increasing; (3)factors affecting the profit of tempe chips home industry; (4) strategy of the tempe chips home industry when the production cost increase as cooking oil price increase. The research area is Rawalo sub-district, Banyumas district. Data collected by census method of 49 tempe home industries. Analyses used are RIC ratio, 1C/Cratio, BEP production, BEP revenue, BEP price, and Unit-Output-Price Cobb-Douglas Profit Function. The results show that: (1) tempe chips home industries have to be maintained although cooking oil price increasing has increased the product's price also; (2) after cooking oil price increasing period, tempe chips home industry has decreasing income; (3) UOP Cobb-Douglas Profit Function shows that cooking oil price, soybean price, cassava powder price, production capacity, dummy variable of before and after increasing cooking oil price period affect the profit function of tempe chips home industry; (4) strategy have been practiced by tempe chips home industries tempe chips product's size, decrease the tempe chips per pack capacity, decrease the production capacity, decrease the production frequency, and add cassava in the processing of tempe making.

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

scholarly journals What Is the Consensus from Multiple Conclusions of Future Crop Yield Changes Affected by Climate Change in China?

2020 ◽  
Vol 17 (24) ◽  
pp. 9241
Author(s):  
Chengfang Huang ◽  
Ning Li ◽  
Zhengtao Zhang ◽  
Yuan Liu ◽  
Xi Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Positive Impact ◽  
Scientific Evidence ◽  
Future Climate Change ◽  
Systematic Review Methodology ◽  
Uncertainty Interval ◽  
The Impact ◽  
Yield Decrease

Many studies have shown that climate change has a significant impact on crop yield in China, while results have varied due to uncertain factors. This study has drawn a highly consistent consensus from the scientific evidence based on numerous existing studies. By a highly rational systematic review methodology, we obtained 737 result samples with the theme of climate change affecting China’s crop yields. Then, we used likelihood scale and trend analysis methods to quantify the consensus level and uncertainty interval of these samples. The results showed that: (i) The crop yield decrease in the second half of the 21st century will be greater than 5% of that in the first half. (ii) The crop most affected by climate change will be maize, with the decreased value exceeding −25% at the end of this century, followed by rice and wheat exceeding −10% and −5%. (iii) The positive impact of CO2 on crop yield will change by nearly 10%. Our conclusions clarify the consensus of the impact of future climate change on China’s crop yield, and this study helps exclude the differences and examine the policies and actions that China has taken and should take in response to climate change.

ECONOMIC AND PHYSICAL MODELING OF LAND USE IN GCAM 3.0 AND AN APPLICATION TO AGRICULTURAL PRODUCTIVITY, LAND, AND TERRESTRIAL CARBON

2014 ◽  
Vol 05 (02) ◽  
pp. 1450003 ◽  
Author(s):  
MARSHALL WISE ◽  
KATE CALVIN ◽  
PAGE KYLE ◽  
PATRICK LUCKOW ◽  
JAE EDMONDS
Keyword(s):  
Land Use ◽  
Crop Yield ◽  
Carbon Emissions ◽  
Crop Yields ◽  
Assessment Model ◽  
Agricultural Crop ◽  
Terrestrial Carbon ◽  
Global Change Assessment Model ◽  
The Impact

The release of the Global Change Assessment Model (GCAM) version 3.0 represents a major revision in the treatment of agriculture and land-use activities in a model of long-term, global human and physical Earth systems. GCAM 3.0 incorporates greater spatial and temporal resolution compared to GCAM 2.0. In this paper, we document the methods embodied in the new release, describe the motivation for the changes, compare GCAM 3.0 methods to those of other long-term, global agriculture-economy models and apply GCAM 3.0 to explore the impact of changes in agricultural crop yields on global land use and terrestrial carbon. In the absence of continued crop yield improvements throughout the century, not only are cumulative carbon emissions a major source of CO 2 emissions to the atmosphere, but bioenergy production remains trivial — land is needed for food. In contrast, the high crop yield improvement scenario cuts terrestrial carbon emissions dramatically and facilitates both food and energy production.

scholarly journals Determining the Yield of the Crop using Artificial Neural Network Method

2019 ◽  
Vol 9 (1) ◽  
pp. 2959-2965
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Crop Yield ◽  
Crop Yields ◽  
Back Propagation ◽  
Large Data ◽  
Machine Learning Techniques ◽  
Agricultural System ◽  
Factors Affecting ◽  
Artificial Neural

The agricultural system is complex and comprehend since it deals with large data that comes from several factors. Lot of techniques and have been used to identify any interactions between factors affecting yields with crop performance. The major objective of this paper is to help us predict the yield of a particular crop before even cultivating it for its production. We are using artificial neural networks for forwarding and implementing a system that will help the farmers in finding their crop yields according to their given data as input in the system and the system will give output based on previous data. The method used in this crop yield system is an artificial neural network and the algorithm used is feed forward and back propagation. Provide the input of data sets and the desired outcome of the system. Compute the error between the actual and desired outcome of the system. Amendment of the weight associated with different inputs and different functions. Compare the errors and the tolerance ratio of the output. Various machine learning techniques have been used in the past for calculating the crop yield using remote data. However, these methods are less useful and effective for predicting the yield of maize and for some other crops, which is cultivated at different times in various fields.The major application of this crop yield system is that it will help us to predict the yield before even cultivating it by studying the previous data collected such as soil fertility, pH level.

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