Pub Date : 2024-07-04DOI: 10.9734/ijecc/2024/v14i74270
Z. Gichana
This study investigated the influence of human activities on water quality parameters in the Molo River, one of the major inflow rivers of Lake Baringo. Monthly measurements of physical and chemical parameters were conducted for six months (February-July 2023) at sampling stations established along the river to represent areas with different human activities. Analysis of variance was used to test for significant differences in water quality parameters among sampling stations. The results revealed significant downstream increases (p < 0.05) in water temperature, electrical conductivity, pH, total dissolved solids (TDS), and nutrients (total nitrogen, ammonium nitrogen, total phosphorus, and soluble reactive phosphorus) compared to upstream stations. Conversely, dissolved oxygen (DO) levels exhibited a downstream decrease. Sachangwan emerged as the most polluted sampling station with elevated levels of conductivity, total dissolved solids, total phosphorus, soluble reactive phosphorus, and ammonium nitrogen. In contrast, Sirindet recorded low pollutant levels. These observations are likely attributable to deforestation, agricultural practices, and point source pollution, which were more prevalent in downstream stations compared to the less disturbed upstream stations. The findings highlight the significant influence of human activities on the water quality along the Molo River. Understanding these interactions is crucial for developing effective pollution control strategies to protect the Molo River and Lake Baringo.
{"title":"Anthropogenic Influences on Water Quality in Molo River, Lake Baringo Basin","authors":"Z. Gichana","doi":"10.9734/ijecc/2024/v14i74270","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74270","url":null,"abstract":"This study investigated the influence of human activities on water quality parameters in the Molo River, one of the major inflow rivers of Lake Baringo. Monthly measurements of physical and chemical parameters were conducted for six months (February-July 2023) at sampling stations established along the river to represent areas with different human activities. Analysis of variance was used to test for significant differences in water quality parameters among sampling stations. The results revealed significant downstream increases (p < 0.05) in water temperature, electrical conductivity, pH, total dissolved solids (TDS), and nutrients (total nitrogen, ammonium nitrogen, total phosphorus, and soluble reactive phosphorus) compared to upstream stations. Conversely, dissolved oxygen (DO) levels exhibited a downstream decrease. Sachangwan emerged as the most polluted sampling station with elevated levels of conductivity, total dissolved solids, total phosphorus, soluble reactive phosphorus, and ammonium nitrogen. In contrast, Sirindet recorded low pollutant levels. These observations are likely attributable to deforestation, agricultural practices, and point source pollution, which were more prevalent in downstream stations compared to the less disturbed upstream stations. The findings highlight the significant influence of human activities on the water quality along the Molo River. Understanding these interactions is crucial for developing effective pollution control strategies to protect the Molo River and Lake Baringo.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141677801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.9734/ijecc/2024/v14i74271
Ganta Harshitha, G. Sreenivas, N. Mahesh, K. Chandrashekhar, Anima Biswal, P. Srikanth
This experiment was conducted to study the effect of different tillage practices, irrigation schedules and nitrogen levels on the grain yield, stalk yield, harvest index and economics of rabi maize in rice fallows. The design selected for this study was Split- split plot design. This experiment was conducted at Regional Agricultural Research Station farm, Polasa, Jagtial during rabi 2022 and 2023. The experiment was laid out in split- split plot design with twelve treatment combinations which are replicated thrice. The treatments are two main plots: T1- Zero tillage, T2- Conventional tillage (cultivator twice fb rotovator twice); three sub plots: I1- 60% ASM, I2- 40% ASM and I3- Irrigation at six critical stages; and two sub-sub plot treatments: N1- 100% RDN and N2- 120% RDN. Results indicated that higher grain yield, stalk yield, gross returns, net returns and B-C ratio were higher in conventional tillage among the two tillage practices, in I3 treatment among the three irrigation schedules and in N2 (120% RDN) among the two nitrogen levels. The lowest values were recorded with zero tillage, I2 treatment and N1 (100% RDN). Harvest index was significantly effected by tillage practices but it is non-significant with irrigation schedules and nitrogen levels.
{"title":"Influence of Different Tillage Practices, Irrigation and Nitrogen Levels on Yield and Economics of Rice Fallow Maize","authors":"Ganta Harshitha, G. Sreenivas, N. Mahesh, K. Chandrashekhar, Anima Biswal, P. Srikanth","doi":"10.9734/ijecc/2024/v14i74271","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74271","url":null,"abstract":"This experiment was conducted to study the effect of different tillage practices, irrigation schedules and nitrogen levels on the grain yield, stalk yield, harvest index and economics of rabi maize in rice fallows. The design selected for this study was Split- split plot design. This experiment was conducted at Regional Agricultural Research Station farm, Polasa, Jagtial during rabi 2022 and 2023. The experiment was laid out in split- split plot design with twelve treatment combinations which are replicated thrice. The treatments are two main plots: T1- Zero tillage, T2- Conventional tillage (cultivator twice fb rotovator twice); three sub plots: I1- 60% ASM, I2- 40% ASM and I3- Irrigation at six critical stages; and two sub-sub plot treatments: N1- 100% RDN and N2- 120% RDN. Results indicated that higher grain yield, stalk yield, gross returns, net returns and B-C ratio were higher in conventional tillage among the two tillage practices, in I3 treatment among the three irrigation schedules and in N2 (120% RDN) among the two nitrogen levels. The lowest values were recorded with zero tillage, I2 treatment and N1 (100% RDN). Harvest index was significantly effected by tillage practices but it is non-significant with irrigation schedules and nitrogen levels.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-03DOI: 10.9734/ijecc/2024/v14i74269
Gandaa, Z, Bizoola
Concepts of ecosystem services have been developed to make explicit connections between human welfare and ecological sustainability for policy, development, and conservation initiatives. Economic concepts such as the distinction between prices and values, and the acknowledgment of their values are context-specific which may change across space and time. Contingent valuation is a survey-based economic technique for valuing non-market resources, such as vegetation. This method is often used to establish the amount people are willing to be compensated for maintaining the existence of an environmental feature such as a tree, shrub, or grass. The level of importance attached to provisioning services as well as cultural services and cultural heritage differ in the rural communities hence different cash values attached. It is often perceived that rural community members do not put monetary value on vegetation, the study is therefore aimed at establishing monetary value rural communities have value for vegetation. The study was conducted in two irrigated and two unirrigated landscapes consisting of about 54 communities and comprising 240 respondents. Participatory Rural Appraisal tools were used. Random Utility Theory was applied and used for the analysis. The willingness to sell vegetation was significant at a 5% confidence level concerning native, sex, age, education, and household head. Marital status was, however, not significant in all the landscapes. The price trend is observed to be across a landscape, from the catchment to the downstream ecosystem.
{"title":"Evaluating Willingness to Sell Vegetation in the White Volta Basin in Northern Ghana","authors":"Gandaa, Z, Bizoola","doi":"10.9734/ijecc/2024/v14i74269","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74269","url":null,"abstract":"Concepts of ecosystem services have been developed to make explicit connections between human welfare and ecological sustainability for policy, development, and conservation initiatives. Economic concepts such as the distinction between prices and values, and the acknowledgment of their values are context-specific which may change across space and time. Contingent valuation is a survey-based economic technique for valuing non-market resources, such as vegetation. This method is often used to establish the amount people are willing to be compensated for maintaining the existence of an environmental feature such as a tree, shrub, or grass. The level of importance attached to provisioning services as well as cultural services and cultural heritage differ in the rural communities hence different cash values attached. It is often perceived that rural community members do not put monetary value on vegetation, the study is therefore aimed at establishing monetary value rural communities have value for vegetation. The study was conducted in two irrigated and two unirrigated landscapes consisting of about 54 communities and comprising 240 respondents. Participatory Rural Appraisal tools were used. Random Utility Theory was applied and used for the analysis. The willingness to sell vegetation was significant at a 5% confidence level concerning native, sex, age, education, and household head. Marital status was, however, not significant in all the landscapes. The price trend is observed to be across a landscape, from the catchment to the downstream ecosystem.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"77 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-03DOI: 10.9734/ijecc/2024/v14i74267
Akhila Ashokan, Mini V., Rani B, Anand S.
The food demand over the world is increasing due to the rapid increase in the population. Direct and indirect effects of climate change have severely affected the growth and development of crops. Of these, abiotic stress factors are reported to cause a reduction in crop productivity ranging from 51 percent to 82 percent. Abiotic stresses like drought, waterlogging stress, salt stress, soil acidity, metal toxicities and temperature variations have overwhelming impact on the growth and productivity of crops. Abiotic stress causes increase in reactive oxygen species (ROS) levels and affects various physiological processes, causing reduction in plant growth and yield. Nutrient management proves to be an effective strategy for alleviating various abiotic stress factors affecting agricultural crops. Nutrients such as nitrogen, potassium, calcium and magnesium increase the production of antioxidant enzymes such as superoxide dismutase, peroxidase, catalase and reduces ROS production. Micronutrients such as iron, boron and zinc as well as biofertilizers improve plant adaptation to various stresses through activation of antioxidant enzymes. Current review focuses on the impact of mineral nutrients, organic amendments and biofertilizers in alleviating abiotic stress in agricultural crops.
{"title":"Mitigation of Abiotic Stresses in Plants through Nutrient Management","authors":"Akhila Ashokan, Mini V., Rani B, Anand S.","doi":"10.9734/ijecc/2024/v14i74267","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74267","url":null,"abstract":"The food demand over the world is increasing due to the rapid increase in the population. Direct and indirect effects of climate change have severely affected the growth and development of crops. Of these, abiotic stress factors are reported to cause a reduction in crop productivity ranging from 51 percent to 82 percent. Abiotic stresses like drought, waterlogging stress, salt stress, soil acidity, metal toxicities and temperature variations have overwhelming impact on the growth and productivity of crops. Abiotic stress causes increase in reactive oxygen species (ROS) levels and affects various physiological processes, causing reduction in plant growth and yield. Nutrient management proves to be an effective strategy for alleviating various abiotic stress factors affecting agricultural crops. Nutrients such as nitrogen, potassium, calcium and magnesium increase the production of antioxidant enzymes such as superoxide dismutase, peroxidase, catalase and reduces ROS production. Micronutrients such as iron, boron and zinc as well as biofertilizers improve plant adaptation to various stresses through activation of antioxidant enzymes. Current review focuses on the impact of mineral nutrients, organic amendments and biofertilizers in alleviating abiotic stress in agricultural crops.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Field experiment was conducted during kharif season of 2017 and 2018 at Instructional Farm under Bidhan Chandra Krishi Viswavidyalaya, West Bengal in sandy loam soil to study the growth and yield of transplanted kharif rice variety Satabdi (cv. IET 4786) as influenced by biological products. The experiment was laid down in randomized complete block design (RCBD) with seven treatment combinations replicated thrice. Results revealed that RDF + soil applied Bolt GR @ 10 kg/ha produced higher growth attributes and yield of tested rice cultivar. The same treatment registered significantly higher total N and K uptake in tested cultivar; while the highest P uptake was recorded with RDF + Seed treatment with JumpStart2.0 @ 0.83 ml/kg seed. The treatment RDF + soil applied Azospirillum @ 2 kg/ha brought about significant positive changes of available N content in post-harvest soil over control situation (only RDF). However, significantly higher available P content was estimated in plots with RDF + soil applied PSB @ 2 kg/ha. Application of bio-products failed to exert any significant influence on residual soil K. The crop receiving RDF + soil applied Bolt GR @ 10 kg/ha gave highest gross return, net return and B:C ratio. Hence, application of RDF (60-30-30 kg N, P2O5 and K2O/ha) along with Bolt GR @ 10 kg/ha or Azospirillum @ 2 kg/ha may be recommended to achieve higher grain yield of tested cultivar Satabdi (cv. IET 4786).
{"title":"Effect of Biological Products on Yield, Production Economics and Soil Nutrient Status of Transplanted kharif Rice (Oryza sativa L.) in Gangetic Alluvial Soil of West Bengal, India","authors":"M. Sana, Kalyan Jana, Ramyajit Mondal, Krishnendu Mondal, Subhajit Banerjee, Hirak Banerjee","doi":"10.9734/ijecc/2024/v14i74268","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74268","url":null,"abstract":"Field experiment was conducted during kharif season of 2017 and 2018 at Instructional Farm under Bidhan Chandra Krishi Viswavidyalaya, West Bengal in sandy loam soil to study the growth and yield of transplanted kharif rice variety Satabdi (cv. IET 4786) as influenced by biological products. The experiment was laid down in randomized complete block design (RCBD) with seven treatment combinations replicated thrice. Results revealed that RDF + soil applied Bolt GR @ 10 kg/ha produced higher growth attributes and yield of tested rice cultivar. The same treatment registered significantly higher total N and K uptake in tested cultivar; while the highest P uptake was recorded with RDF + Seed treatment with JumpStart2.0 @ 0.83 ml/kg seed. The treatment RDF + soil applied Azospirillum @ 2 kg/ha brought about significant positive changes of available N content in post-harvest soil over control situation (only RDF). However, significantly higher available P content was estimated in plots with RDF + soil applied PSB @ 2 kg/ha. Application of bio-products failed to exert any significant influence on residual soil K. The crop receiving RDF + soil applied Bolt GR @ 10 kg/ha gave highest gross return, net return and B:C ratio. Hence, application of RDF (60-30-30 kg N, P2O5 and K2O/ha) along with Bolt GR @ 10 kg/ha or Azospirillum @ 2 kg/ha may be recommended to achieve higher grain yield of tested cultivar Satabdi (cv. IET 4786).","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"57 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141683906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.9734/ijecc/2024/v14i74266
Junaid Mehraj, Latief Ahmed, Kahkashan Qayoom, Faisul Rasool, Raies A. Bhat, Umer Fayaz, Umar Rashid Abdullah, Sajad Yousuf Dar, Amir Hussain Mir
Climate change (CC) and climate variability (CV) are causing irregular precipitation, rising sea levels, and frequent extreme weather events, which threaten global agricultural crop production through prolonged droughts, floods, and shifting agroclimatic zones. Addressing greenhouse gas emissions and ensuring food security are among the greatest challenges of this century. Climate Smart Agriculture (CSA) emerges as a global strategy to enhance food productivity amid these uncertainties. CSA aims to create climate-resilient agricultural systems that increase soil health, water, and nutrient efficiency, provide stable yields, and reduce greenhouse gas emissions. By improving farmers' incomes and resilience to climate impacts, CSA contributes to both climate change mitigation and adaptation. Future CSA development directions include leveraging advanced internet technology for secure agricultural information, optimizing cropping patterns and management, integrating "internet + weather" services, and implementing agricultural weather index-based insurance. These strategies offer new pathways for ecological protection, green agricultural development, and climate change mitigation.
{"title":"Climate Smart Agriculture: A Roadmap to Sustainable Food Security","authors":"Junaid Mehraj, Latief Ahmed, Kahkashan Qayoom, Faisul Rasool, Raies A. Bhat, Umer Fayaz, Umar Rashid Abdullah, Sajad Yousuf Dar, Amir Hussain Mir","doi":"10.9734/ijecc/2024/v14i74266","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74266","url":null,"abstract":"Climate change (CC) and climate variability (CV) are causing irregular precipitation, rising sea levels, and frequent extreme weather events, which threaten global agricultural crop production through prolonged droughts, floods, and shifting agroclimatic zones. Addressing greenhouse gas emissions and ensuring food security are among the greatest challenges of this century. Climate Smart Agriculture (CSA) emerges as a global strategy to enhance food productivity amid these uncertainties. CSA aims to create climate-resilient agricultural systems that increase soil health, water, and nutrient efficiency, provide stable yields, and reduce greenhouse gas emissions. By improving farmers' incomes and resilience to climate impacts, CSA contributes to both climate change mitigation and adaptation. Future CSA development directions include leveraging advanced internet technology for secure agricultural information, optimizing cropping patterns and management, integrating \"internet + weather\" services, and implementing agricultural weather index-based insurance. These strategies offer new pathways for ecological protection, green agricultural development, and climate change mitigation.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.9734/ijecc/2024/v14i74264
Raj Godvani, Chetan R. Dudhagara
Climate change is becoming one of the major constraints for agricultural production. Impact on the crop yield due to unseasonal rain, hailstorms, and sudden temperature rise is becoming more frequent. The study assesses the damage done by the heat wave in the Ludhiana district of Punjab in the year 2021-22. Satellite datasets have been used named Sentinel-2 and MODIS datasets. By using the Sentinel-2 Images crop discrimination was performed and wheat crop mask was generated for the year 2018-19 to 2021-22. A comparison of the Normalized Difference Vegetation Index (NDVI) was performed for the study period. MODIS dataset was used to calculate the Temperature Condition Index (TCI) and Temperature Stress Index, which reflects the effect of the heat wave that happened in March 2022. APY (Area, Production, Yield) and data on the procurement of wheat for the year 2021-22 and normal years were compared to visualize the impact of heat wave on the various market dynamics such as production, productivity, etc.
{"title":"Assessing the Impact of Heatwaves on Wheat Crop Health in Ludhiana District Using Remote Sensing Technologies","authors":"Raj Godvani, Chetan R. Dudhagara","doi":"10.9734/ijecc/2024/v14i74264","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74264","url":null,"abstract":"Climate change is becoming one of the major constraints for agricultural production. Impact on the crop yield due to unseasonal rain, hailstorms, and sudden temperature rise is becoming more frequent. The study assesses the damage done by the heat wave in the Ludhiana district of Punjab in the year 2021-22. Satellite datasets have been used named Sentinel-2 and MODIS datasets. By using the Sentinel-2 Images crop discrimination was performed and wheat crop mask was generated for the year 2018-19 to 2021-22. A comparison of the Normalized Difference Vegetation Index (NDVI) was performed for the study period. MODIS dataset was used to calculate the Temperature Condition Index (TCI) and Temperature Stress Index, which reflects the effect of the heat wave that happened in March 2022. APY (Area, Production, Yield) and data on the procurement of wheat for the year 2021-22 and normal years were compared to visualize the impact of heat wave on the various market dynamics such as production, productivity, etc.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"81 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141695985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.9734/ijecc/2024/v14i74263
Ritik Raj, Shailesh Kumar, S. Lal, Hemlata Singh, J. Pradhan, Yash Bhardwaj
As global population continues to grow, there is an increasing need for innovative solutions to enhance agricultural productivity, efficiency, and sustainability. To meet increasing population demand, agricultural production must be doubled. The global population is projected to rise by almost two billion individuals within the next three decades. With global challenges such as population growth, climate change, and resource formation, automation in farming practices is one of the key driving forces behind this revolution. Robotics, coupled with artificial intelligence (AI) and advanced data analytics, are transformative solutions for precision farming and smart farming technologies. These technologies enable continuous and efficient farming operations and provide detailed monitoring at a plant-by-pant level, optimizing resource use and reducing the environmental footprint. Technological advancements have led to the development of various robotic systems, including agricultural grippers and autonomous machinery, which are integral to the automation of farming tasks, from sowing to harvesting. However, the adoption of such technologies is not without challenges. High initial investment costs, connectivity issues, and data security are some of the barriers that need to be addressed. The potential benefits of reduced operational costs, improved crop quality, and enhanced farm output make it a promising solution for the future of farming. In this article, we discuss the multifaceted role of robotics in modern agriculture by exploring both technological advancements and challenges to widespread adoption.
{"title":"A Brief Overview of Technologies in Automated Agriculture: Shaping the Farms of Tomorrow","authors":"Ritik Raj, Shailesh Kumar, S. Lal, Hemlata Singh, J. Pradhan, Yash Bhardwaj","doi":"10.9734/ijecc/2024/v14i74263","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74263","url":null,"abstract":"As global population continues to grow, there is an increasing need for innovative solutions to enhance agricultural productivity, efficiency, and sustainability. To meet increasing population demand, agricultural production must be doubled. The global population is projected to rise by almost two billion individuals within the next three decades. With global challenges such as population growth, climate change, and resource formation, automation in farming practices is one of the key driving forces behind this revolution. Robotics, coupled with artificial intelligence (AI) and advanced data analytics, are transformative solutions for precision farming and smart farming technologies. These technologies enable continuous and efficient farming operations and provide detailed monitoring at a plant-by-pant level, optimizing resource use and reducing the environmental footprint. Technological advancements have led to the development of various robotic systems, including agricultural grippers and autonomous machinery, which are integral to the automation of farming tasks, from sowing to harvesting. However, the adoption of such technologies is not without challenges. High initial investment costs, connectivity issues, and data security are some of the barriers that need to be addressed. The potential benefits of reduced operational costs, improved crop quality, and enhanced farm output make it a promising solution for the future of farming. In this article, we discuss the multifaceted role of robotics in modern agriculture by exploring both technological advancements and challenges to widespread adoption.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141698642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.9734/ijecc/2024/v14i74262
B. M. Naik, A.K. Singh, Saikat Maji, P. Venkatesan
Since the start of this century, there has been significant attention placed on climate change, largely due to its direct impact on ecosystems and agriculture, particularly affecting farmers in vulnerable regions. A descriptive research study was undertaken to explore the attitude of farmers towards climate resilient agricultural technologies in the National Innovations on Climate Resilient Agriculture (NICRA) project implemented villages of Suryapet and Khammam districts of Telangana state, India. The ex-post facto research design was used in this study. A sample of 200 respondents from the two districts i.e. Suryapet and Khammam were randomly selected to assess the attitude of farmers towards these CRA technologies and also employed Z test to evaluate significant difference between the attitude of farmers in Suryapet and Khammam districts towards climate resilient technologies. The findings of the study revealed that the majority of the Suryapet and Khammam (62.67% and 72.00%) farmers had highly favourable attitude towards CRA technologies which was followed by moderately favourable (35.33% and 28.00%) and less favourable (2.00% and 0.00%). On the whole, nearly two third (65.00%) of the respondents had highly favourable attitude towards CRA technologies which is considered as a precursor for adoption of these technologies by the farming community. By employing the Z-test it was observed that there was a difference between farmers' attitude in the Suryapet and Khammam districts where Khammam farmers were having slightly more favourable attitude when compared to Suryapet farmers. Therefore, the outcomes of this research study could assist extension organizations in effectively training and implementing climate-resilient technologies under the National Innovations on Climate Resilient Agriculture (NICRA) initiative in the other villages.
自本世纪初以来，气候变化一直备受关注，这主要是因为气候变化对生态系统和农业产生了直接影响，尤其影响到脆弱地区的农民。我们开展了一项描述性研究，以探讨印度特兰甘纳邦苏里亚佩特和卡马姆地区实施国家气候适应性农业创新（NICRA）项目的村庄的农民对气候适应性农业技术的态度。本研究采用事后研究设计。从苏里亚佩特和卡曼姆两个地区随机抽取了 200 名受访者，以评估农民对这些 CRA 技术的态度，并采用 Z 检验来评估苏里亚佩特和卡曼姆地区农民对气候适应性技术态度的显著差异。研究结果表明，苏里亚佩特和卡曼姆的大多数农民（62.67% 和 72.00%）对 CRA 技术持非常赞成的态度，其次是一般赞成（35.33% 和 28.00%）和不太赞成（2.00% 和 0.00%）。总体而言，近三分之二（65.00%）的受访者对 CRA 技术持非常好的态度，这被认为是农业社区采用这些技术的先决条件。通过 Z 检验发现，苏里亚佩特区和卡曼姆区农民的态度存在差异，卡曼姆区农民的态度比苏里亚佩特区农民略好。因此，本研究的成果可以帮助推广机构在其他村庄有效培训和实施国家气候适应性农业创新（NICRA）倡议下的气候适应性技术。
{"title":"Exploring Farmers Attitudes towards Climate Resilient Agricultural Technologies in Telangana State, India","authors":"B. M. Naik, A.K. Singh, Saikat Maji, P. Venkatesan","doi":"10.9734/ijecc/2024/v14i74262","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74262","url":null,"abstract":"Since the start of this century, there has been significant attention placed on climate change, largely due to its direct impact on ecosystems and agriculture, particularly affecting farmers in vulnerable regions. A descriptive research study was undertaken to explore the attitude of farmers towards climate resilient agricultural technologies in the National Innovations on Climate Resilient Agriculture (NICRA) project implemented villages of Suryapet and Khammam districts of Telangana state, India. The ex-post facto research design was used in this study. A sample of 200 respondents from the two districts i.e. Suryapet and Khammam were randomly selected to assess the attitude of farmers towards these CRA technologies and also employed Z test to evaluate significant difference between the attitude of farmers in Suryapet and Khammam districts towards climate resilient technologies. The findings of the study revealed that the majority of the Suryapet and Khammam (62.67% and 72.00%) farmers had highly favourable attitude towards CRA technologies which was followed by moderately favourable (35.33% and 28.00%) and less favourable (2.00% and 0.00%). On the whole, nearly two third (65.00%) of the respondents had highly favourable attitude towards CRA technologies which is considered as a precursor for adoption of these technologies by the farming community. By employing the Z-test it was observed that there was a difference between farmers' attitude in the Suryapet and Khammam districts where Khammam farmers were having slightly more favourable attitude when compared to Suryapet farmers. Therefore, the outcomes of this research study could assist extension organizations in effectively training and implementing climate-resilient technologies under the National Innovations on Climate Resilient Agriculture (NICRA) initiative in the other villages.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"12 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141704405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.9734/ijecc/2024/v14i74265
Kossivi Fabrice Dossa, Y. Miassi
Geospatial technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) provide a platform for swiftly evaluating terrestrial Carbon Stock (CS) across extensive regions. Employing an integrated RS-GIS method for estimating Above-Ground Biomass (AGB) and precise carbon management emerges as a timely and economical strategy for implementing effective management plans on a localized and regional level. This study reviews different RS-related techniques utilized in CS assessment, particularly in arid lands, shedding light on the challenges, opportunities, and future trends associated with the process. As global warming poses adverse impacts on major ecosystems through temperature and precipitation changes, professionals have a call to develop evidence-based interventions to mitigate them. Carbon sequestration involves harnessing and storing carbon stocks from the atmosphere to minimize the adverse effects of climate change. The review explores the effectiveness of integrating remote sensing and GIS methodologies in quantifying carbon sequestration within agroforestry landscapes. In addition, this review also assesses the traditional methods, including their limitations, and deeply delves into recent techniques, emphasizing key remote sensing (RS) variables for biophysical predictions. This study showcases the efficacy of geospatial technologies in evaluating terrestrial carbon stock, particularly in arid regions. The study reviews diverse techniques and sensors, like optical Radio Detection and Ranging (RADAR), and Light Detection and Ranging (LiDAR), extensively employed for above-ground biomass (AGB) estimation and carbon stock assessment with RS data, introducing and discussing new methods. Existing literature was examined to present knowledge and evidence on the effectiveness of these technologies in carbon sequestration. The key findings of this review will inform future research and integration of technology, policy formulation, and carbon sequestration management to mitigate the impacts of climate change.
{"title":"Remote Sensing Methods and GIS Approaches for Carbon Sequestration Measurement: A General Review","authors":"Kossivi Fabrice Dossa, Y. Miassi","doi":"10.9734/ijecc/2024/v14i74265","DOIUrl":"https://doi.org/10.9734/ijecc/2024/v14i74265","url":null,"abstract":"Geospatial technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) provide a platform for swiftly evaluating terrestrial Carbon Stock (CS) across extensive regions. Employing an integrated RS-GIS method for estimating Above-Ground Biomass (AGB) and precise carbon management emerges as a timely and economical strategy for implementing effective management plans on a localized and regional level. This study reviews different RS-related techniques utilized in CS assessment, particularly in arid lands, shedding light on the challenges, opportunities, and future trends associated with the process. As global warming poses adverse impacts on major ecosystems through temperature and precipitation changes, professionals have a call to develop evidence-based interventions to mitigate them. Carbon sequestration involves harnessing and storing carbon stocks from the atmosphere to minimize the adverse effects of climate change. The review explores the effectiveness of integrating remote sensing and GIS methodologies in quantifying carbon sequestration within agroforestry landscapes. In addition, this review also assesses the traditional methods, including their limitations, and deeply delves into recent techniques, emphasizing key remote sensing (RS) variables for biophysical predictions. This study showcases the efficacy of geospatial technologies in evaluating terrestrial carbon stock, particularly in arid regions. The study reviews diverse techniques and sensors, like optical Radio Detection and Ranging (RADAR), and Light Detection and Ranging (LiDAR), extensively employed for above-ground biomass (AGB) estimation and carbon stock assessment with RS data, introducing and discussing new methods. Existing literature was examined to present knowledge and evidence on the effectiveness of these technologies in carbon sequestration. The key findings of this review will inform future research and integration of technology, policy formulation, and carbon sequestration management to mitigate the impacts of climate change.","PeriodicalId":506431,"journal":{"name":"International Journal of Environment and Climate Change","volume":"290 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141708305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：