Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting

Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Modeling earth systems and environment 2021-06, Vol.7 (2), p.1121-1131
Hauptverfasser: Jakariya, Md, Sarker, Sazzadur Rahman, Sayem, Sheikh Mohammad, Saad, Saman, Islam, Md. Nazrul, Rahman, Abir, Alam, Md. Sajadul, Ali, Mirza Shawkat, Akter, Dilruba
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1131
container_issue 2
container_start_page 1121
container_title Modeling earth systems and environment
container_volume 7
creator Jakariya, Md
Sarker, Sazzadur Rahman
Sayem, Sheikh Mohammad
Saad, Saman
Islam, Md. Nazrul
Rahman, Abir
Alam, Md. Sajadul
Ali, Mirza Shawkat
Akter, Dilruba
description Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.
doi_str_mv 10.1007/s40808-020-00969-6
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2517673854</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2517673854</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-e0b6fac9a05449987905e0f938af11a40730b4784a1e7bb2db16258f052b4dd93</originalsourceid><addsrcrecordid>eNp9kE1OwzAQhSMEElXpBVhZYh0Yx4kTs4OKP6mCDawtxxknqVq72AmCW3BkHIpgx2pGo-_Nm3lJckrhnAKUFyGHCqoUMkgBBBcpP0hmGeMs5Rmlh789sONkEcIaACjPOBdilnw-4vsYiNo62xLfayQ775pRD72zRNmGoH3rvbNbtIPaEKP04HwgvSVDh0Q7Faaxx3binSHXyrYb1WDoLokiYXC6i0ivydY1uOmjidpFB6U7YpwnZhxGj1OLeuJse5IcGbUJuPip8-Tl9uZ5eZ-unu4ellerVDMqhhSh5vEYoaDIcyGqUkCBYASrlKFU5VAyqPOyyhXFsq6zpo4vF5WBIqvzphFsnpzt98ZrXkcMg1y70dtoKbOClrxkVZFHKttT2rsQPBq58_1W-Q9JQU7hy334MoYvv8OXPIrYXhQibFv0f6v_UX0BhE2Jug</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2517673854</pqid></control><display><type>article</type><title>Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting</title><source>Springer Nature - Complete Springer Journals</source><creator>Jakariya, Md ; Sarker, Sazzadur Rahman ; Sayem, Sheikh Mohammad ; Saad, Saman ; Islam, Md. Nazrul ; Rahman, Abir ; Alam, Md. Sajadul ; Ali, Mirza Shawkat ; Akter, Dilruba</creator><creatorcontrib>Jakariya, Md ; Sarker, Sazzadur Rahman ; Sayem, Sheikh Mohammad ; Saad, Saman ; Islam, Md. Nazrul ; Rahman, Abir ; Alam, Md. Sajadul ; Ali, Mirza Shawkat ; Akter, Dilruba</creatorcontrib><description>Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.</description><identifier>ISSN: 2363-6203</identifier><identifier>EISSN: 2363-6211</identifier><identifier>DOI: 10.1007/s40808-020-00969-6</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Agricultural economics ; Agricultural production ; Applications programs ; Autoregressive models ; Chemistry and Earth Sciences ; Coastal zone ; Computer Science ; Crop production ; Data analysis ; Data collection ; Earth and Environmental Science ; Earth Sciences ; Earth System Sciences ; Economic forecasting ; Ecosystems ; Elasticity ; Environment ; Environmental factors ; Fertilizers ; Irrigation water ; Longitudinal studies ; Math. Appl. in Environmental Science ; Mathematical Applications in the Physical Sciences ; Mobile computing ; Multiple regression analysis ; Original Article ; Pesticides ; Physics ; Regression analysis ; Regression models ; Rice ; Statistical analysis ; Statistics for Engineering ; Stochastic models ; Sustainability ; Sustainable agriculture ; Sustainable production ; Urea ; Water scarcity</subject><ispartof>Modeling earth systems and environment, 2021-06, Vol.7 (2), p.1121-1131</ispartof><rights>Springer Nature Switzerland AG 2020</rights><rights>Springer Nature Switzerland AG 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-e0b6fac9a05449987905e0f938af11a40730b4784a1e7bb2db16258f052b4dd93</citedby><cites>FETCH-LOGICAL-c319t-e0b6fac9a05449987905e0f938af11a40730b4784a1e7bb2db16258f052b4dd93</cites><orcidid>0000-0003-2677-5245</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40808-020-00969-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40808-020-00969-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Jakariya, Md</creatorcontrib><creatorcontrib>Sarker, Sazzadur Rahman</creatorcontrib><creatorcontrib>Sayem, Sheikh Mohammad</creatorcontrib><creatorcontrib>Saad, Saman</creatorcontrib><creatorcontrib>Islam, Md. Nazrul</creatorcontrib><creatorcontrib>Rahman, Abir</creatorcontrib><creatorcontrib>Alam, Md. Sajadul</creatorcontrib><creatorcontrib>Ali, Mirza Shawkat</creatorcontrib><creatorcontrib>Akter, Dilruba</creatorcontrib><title>Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting</title><title>Modeling earth systems and environment</title><addtitle>Model. Earth Syst. Environ</addtitle><description>Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.</description><subject>Agricultural economics</subject><subject>Agricultural production</subject><subject>Applications programs</subject><subject>Autoregressive models</subject><subject>Chemistry and Earth Sciences</subject><subject>Coastal zone</subject><subject>Computer Science</subject><subject>Crop production</subject><subject>Data analysis</subject><subject>Data collection</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth System Sciences</subject><subject>Economic forecasting</subject><subject>Ecosystems</subject><subject>Elasticity</subject><subject>Environment</subject><subject>Environmental factors</subject><subject>Fertilizers</subject><subject>Irrigation water</subject><subject>Longitudinal studies</subject><subject>Math. Appl. in Environmental Science</subject><subject>Mathematical Applications in the Physical Sciences</subject><subject>Mobile computing</subject><subject>Multiple regression analysis</subject><subject>Original Article</subject><subject>Pesticides</subject><subject>Physics</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Rice</subject><subject>Statistical analysis</subject><subject>Statistics for Engineering</subject><subject>Stochastic models</subject><subject>Sustainability</subject><subject>Sustainable agriculture</subject><subject>Sustainable production</subject><subject>Urea</subject><subject>Water scarcity</subject><issn>2363-6203</issn><issn>2363-6211</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1OwzAQhSMEElXpBVhZYh0Yx4kTs4OKP6mCDawtxxknqVq72AmCW3BkHIpgx2pGo-_Nm3lJckrhnAKUFyGHCqoUMkgBBBcpP0hmGeMs5Rmlh789sONkEcIaACjPOBdilnw-4vsYiNo62xLfayQ775pRD72zRNmGoH3rvbNbtIPaEKP04HwgvSVDh0Q7Faaxx3binSHXyrYb1WDoLokiYXC6i0ivydY1uOmjidpFB6U7YpwnZhxGj1OLeuJse5IcGbUJuPip8-Tl9uZ5eZ-unu4ellerVDMqhhSh5vEYoaDIcyGqUkCBYASrlKFU5VAyqPOyyhXFsq6zpo4vF5WBIqvzphFsnpzt98ZrXkcMg1y70dtoKbOClrxkVZFHKttT2rsQPBq58_1W-Q9JQU7hy334MoYvv8OXPIrYXhQibFv0f6v_UX0BhE2Jug</recordid><startdate>20210601</startdate><enddate>20210601</enddate><creator>Jakariya, Md</creator><creator>Sarker, Sazzadur Rahman</creator><creator>Sayem, Sheikh Mohammad</creator><creator>Saad, Saman</creator><creator>Islam, Md. Nazrul</creator><creator>Rahman, Abir</creator><creator>Alam, Md. Sajadul</creator><creator>Ali, Mirza Shawkat</creator><creator>Akter, Dilruba</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>7UA</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><orcidid>https://orcid.org/0000-0003-2677-5245</orcidid></search><sort><creationdate>20210601</creationdate><title>Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting</title><author>Jakariya, Md ; Sarker, Sazzadur Rahman ; Sayem, Sheikh Mohammad ; Saad, Saman ; Islam, Md. Nazrul ; Rahman, Abir ; Alam, Md. Sajadul ; Ali, Mirza Shawkat ; Akter, Dilruba</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-e0b6fac9a05449987905e0f938af11a40730b4784a1e7bb2db16258f052b4dd93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agricultural economics</topic><topic>Agricultural production</topic><topic>Applications programs</topic><topic>Autoregressive models</topic><topic>Chemistry and Earth Sciences</topic><topic>Coastal zone</topic><topic>Computer Science</topic><topic>Crop production</topic><topic>Data analysis</topic><topic>Data collection</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Earth System Sciences</topic><topic>Economic forecasting</topic><topic>Ecosystems</topic><topic>Elasticity</topic><topic>Environment</topic><topic>Environmental factors</topic><topic>Fertilizers</topic><topic>Irrigation water</topic><topic>Longitudinal studies</topic><topic>Math. Appl. in Environmental Science</topic><topic>Mathematical Applications in the Physical Sciences</topic><topic>Mobile computing</topic><topic>Multiple regression analysis</topic><topic>Original Article</topic><topic>Pesticides</topic><topic>Physics</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Rice</topic><topic>Statistical analysis</topic><topic>Statistics for Engineering</topic><topic>Stochastic models</topic><topic>Sustainability</topic><topic>Sustainable agriculture</topic><topic>Sustainable production</topic><topic>Urea</topic><topic>Water scarcity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jakariya, Md</creatorcontrib><creatorcontrib>Sarker, Sazzadur Rahman</creatorcontrib><creatorcontrib>Sayem, Sheikh Mohammad</creatorcontrib><creatorcontrib>Saad, Saman</creatorcontrib><creatorcontrib>Islam, Md. Nazrul</creatorcontrib><creatorcontrib>Rahman, Abir</creatorcontrib><creatorcontrib>Alam, Md. Sajadul</creatorcontrib><creatorcontrib>Ali, Mirza Shawkat</creatorcontrib><creatorcontrib>Akter, Dilruba</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><jtitle>Modeling earth systems and environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jakariya, Md</au><au>Sarker, Sazzadur Rahman</au><au>Sayem, Sheikh Mohammad</au><au>Saad, Saman</au><au>Islam, Md. Nazrul</au><au>Rahman, Abir</au><au>Alam, Md. Sajadul</au><au>Ali, Mirza Shawkat</au><au>Akter, Dilruba</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting</atitle><jtitle>Modeling earth systems and environment</jtitle><stitle>Model. Earth Syst. Environ</stitle><date>2021-06-01</date><risdate>2021</risdate><volume>7</volume><issue>2</issue><spage>1121</spage><epage>1131</epage><pages>1121-1131</pages><issn>2363-6203</issn><eissn>2363-6211</eissn><abstract>Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40808-020-00969-6</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-2677-5245</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 2363-6203
ispartof Modeling earth systems and environment, 2021-06, Vol.7 (2), p.1121-1131
issn 2363-6203
2363-6211
language eng
recordid cdi_proquest_journals_2517673854
source Springer Nature - Complete Springer Journals
subjects Agricultural economics
Agricultural production
Applications programs
Autoregressive models
Chemistry and Earth Sciences
Coastal zone
Computer Science
Crop production
Data analysis
Data collection
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Economic forecasting
Ecosystems
Elasticity
Environment
Environmental factors
Fertilizers
Irrigation water
Longitudinal studies
Math. Appl. in Environmental Science
Mathematical Applications in the Physical Sciences
Mobile computing
Multiple regression analysis
Original Article
Pesticides
Physics
Regression analysis
Regression models
Rice
Statistical analysis
Statistics for Engineering
Stochastic models
Sustainability
Sustainable agriculture
Sustainable production
Urea
Water scarcity
title Nexus among rice production and environmental factors in the coastal region of Bangladesh: a stochastic modeling approach for future forecasting
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T19%3A10%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Nexus%20among%20rice%20production%20and%20environmental%20factors%20in%20the%20coastal%20region%20of%20Bangladesh:%20a%20stochastic%20modeling%20approach%20for%20future%20forecasting&rft.jtitle=Modeling%20earth%20systems%20and%20environment&rft.au=Jakariya,%20Md&rft.date=2021-06-01&rft.volume=7&rft.issue=2&rft.spage=1121&rft.epage=1131&rft.pages=1121-1131&rft.issn=2363-6203&rft.eissn=2363-6211&rft_id=info:doi/10.1007/s40808-020-00969-6&rft_dat=%3Cproquest_cross%3E2517673854%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2517673854&rft_id=info:pmid/&rfr_iscdi=true