KULDEEP KAUR, K. K. Gill, PRITPAL SINGH, S. S. Sandhu
{"title":"Growth performance and agrometeorological indices of rice under different establishment methods","authors":"KULDEEP KAUR, K. K. Gill, PRITPAL SINGH, S. S. Sandhu","doi":"10.54386/jam.v26i2.2338","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2338","url":null,"abstract":"The field experiment was conducted to study the growth performance and agrometeorological indices of rice for cultivars i.e. PR 122, PR 126 and Pusa 44 grown under direct seeded rice (DSR) and puddled transplanted rice (PTR) conditions during kharif 2020 and 2021 at Punjab Agricultural University, Ludhiana. Results revealed that the accumulated growing degree days (AGDD), accumulated helio-thermal units (AHTU) and accumulated photo thermal units (APTU) were higher in PTR than DSR, while radiation use efficiency (RUE) was higher in DSR in terms of dry matter production and in terms of grain yield RUE was higher in PTR. Heat use efficiency (HUE) was also higher in DSR. AGDD, AHTU and APTU were also higher in Pusa 44, however, RUE and HUE were higher in PR 126 in terms of grain yield and dry matter. Among nitrogen levels, N3 (Leaf colour chart-based nitrogen application) gives at par yield with N1 (Recommended) and N2 (125 % of recommended). Optimum nitrogen level is helpful to get higher light interception rate and RUE while HUE was highest in N2 followed by N1 and N3.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141275356","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}
{"title":"An assessment of the impact of climate on wheat yield in Indo-Gangetic plain region of India: A panel data analysis","authors":"ANUJ KUMAR, SWAMI PRASAD SAXENA","doi":"10.54386/jam.v26i2.2535","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2535","url":null,"abstract":"This paper is an attempt to assess the impact of climate on wheat yield in the Indo-Gangetic Plain (IGP) region of India by using panel data analysis. Five IGP states namely Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal have been considered to frame a panel. The study used the data of climatic and non-climatic variables from 1990 to 2022 to achieve the objective of the study. The Im-Pesaran-Shin unit-root test was applied to check the stationarity of data. The results of the panel least square dummy variable model indicated that all the climatic variables had non significant influence. Among non-climatic variables that help increase wheat yield, fertilizer consumption and mechanization in agriculture were found to have a significant positive impact on wheat yield in the IGP region of India.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278858","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}
Mukta Nainwal, Anurag Satpathi, Rajeev Ranjan, A. Nain
{"title":"Development of weather based statistical models for Rhizoctonia aerial blight disease of soybean in Tarai region of Uttarakhand","authors":"Mukta Nainwal, Anurag Satpathi, Rajeev Ranjan, A. Nain","doi":"10.54386/jam.v26i2.2530","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2530","url":null,"abstract":"","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141274803","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}
{"title":"Blue and green water footprint assessment of rice crop in high altitude temperate zone of Kashmir, India","authors":"Shafaq Hassan, Aditya Rana","doi":"10.54386/jam.v26i2.2569","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2569","url":null,"abstract":"The water footprint (WF) for rice has been calculated from 2010 to 2022 for three different districts viz Anantnag, Budgam and Baramulla representing three different climatic regions of Kashmir valley. CROPWAT 8.0 model was used to calculate effective rainfall, reference evapotranspiration (ETo), crop evapotranspiration (ETc), and thereby the green and blue water footprint of rice was determined. ET0 was 117-133 mm in Budgam district, 100-112 mm in Baramulla district and 143-155 mm in Anantnag district. ETc in Budgam was found in the range of 136-149 m3ha-1, in Baramulla district it was found in the range of 115-140 m3ha-1 and in Anantnag district it was highest of the three districts ranging from 163-178 m3ha-1.The results showed that the WF was the highest (3444 l kg-1) in Baramulla district followed by 2300 l kg-1 in Anantnag and 2003 l kg-1 in Budgam districts. The share of green and blue components of WF (WFgreen and WFblue) also varied with the locations and in years. WFgreen and WFblue contributed more or less equally in Baramulla district, 68% and 32% respectively in Burmuda district and 60% and 40 % in Anantnag districts respectively.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141275523","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}
R. Balasree, G. Dheebakaran, A. Senthil, N. K. Sathyamoorthy, P. S. Ganapati, K. Pugazenthi
{"title":"Weather induced physiological responses on the flowering habits of neem trees (Azadirachta indica)","authors":"R. Balasree, G. Dheebakaran, A. Senthil, N. K. Sathyamoorthy, P. S. Ganapati, K. Pugazenthi","doi":"10.54386/jam.v26i2.2335","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2335","url":null,"abstract":"Adaptability and significant economic value of the neem tree are well-known, as it can flourish in a variety of environmental conditions. While the neem seed production is highly sensitive to prevailing weather conditions during the reproductive phase and flowering behaviour of the tree. A study was conducted at Tamil Nadu Agricultural University, Coimbatore in 2023 with the primary objective of validating the weather influence on neem seed production using the logics of physiological responses, as a continuation of research conducted the previous year (2022). During the pre-flowering and flowering stages, diverse weather conditions led to notable changes in the physiological traits of neem trees, which displayed varying patterns of flowering. Trees that flowered consistently showed elevated levels of indole acetic acid (IAA) oxidase, relative water content, and nitrate reductase compared to those that lacked flowers or produced intermittently. In the flowering stage, the neem trees responded positively in terms of physiological aspects like IAA oxidase, relative water content, nitrate reductase, and exhibited lower proline levels, which can be attributed to the optimal maximum temperature, rainfall, and soil moisture. Proline levels rose during the pre-flowering stage due to soil moisture deficits but fell during the flowering stage with the onset of rain. These physiological changes, driven by climatic factors, are likely to enhance the flowering, fruiting, and overall yield of neem trees.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278378","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}
CH. Srinivasa Rao, Kirttiranjan Baral, V. MANI CHANADANA, M. JAGADESH, R. KARTHIK
{"title":"Climate change adaptation and mitigation in Indian agriculture","authors":"CH. Srinivasa Rao, Kirttiranjan Baral, V. MANI CHANADANA, M. JAGADESH, R. KARTHIK","doi":"10.54386/jam.v26i2.2582","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2582","url":null,"abstract":"Climate change poses significant challenges to Indian agriculture, impacting crop yields, water availability, and overall food security. To address these challenges, a combination of adaptation and mitigation strategies is crucial. Adaptation measures involve adjusting agricultural practices to changing climate conditions, such as altering planting schedules, implementing water-saving techniques, and promoting resilient crop varieties. Mitigation strategies focus on reducing greenhouse gas emissions from agricultural activities, like adopting sustainable farming practices and enhancing carbon sequestration in soils. In India, the integration of adaptation and mitigation efforts is essential to enhance the resilience of farmers and agricultural systems to climate change impacts while contributing to global climate goals. By combining traditional knowledge with modern scientific approaches, Indian agriculture can navigate the complexities of climate change, ensuring sustainable food production and livelihood security for millions of farmers across the country. A concerted effort involving policymakers, researchers, extension workers, and farming communities is vital to bolster the resilience of Indian agriculture while contributing to global climate change mitigation efforts. Effective extension services are paramount for educating farmers and ensuring widespread adoption of these strategies. By prioritizing both adaptation and mitigation, Indian agriculture can navigate the challenges of climate change and ensure long-term food security.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277267","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}
{"title":"Assessment of heat and cold wave incidences and their link with land surface temperature in Bathinda district of Punjab, India","authors":"Anjusha Sanjay Gawai, Raj Kumar Pal, SOMPAL SINGH","doi":"10.54386/jam.v26i2.2398","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2398","url":null,"abstract":"This study investigates the incidence of heat wave and cold wave condition during 2000 – 2022 in the Bathinda district of South-Western region of Punjab. Notable spikes in heat wave (HW) activity were observed in 2002 and 2022 with 29 and 27 days respectively. Similarly, for severe heat waves (SHW), 2010 and 2022 witnessed the highest frequencies recording 16 and 18 days respectively. Conversely, cold wave (CW) events peaked in 2005 and 2008 with 10 and 11 days respectively. Notably, 2008 also observed the highest frequency of severe cold wave (SCW) days with 15 days. However, results revealed decline in cold wave days towards the latter years, while severe cold wave days also exhibited decreasing frequencies like 2015 and 2016 recorded zero CW and SCW days. One key finding highlights a substantial correlation between land surface temperature (LST) and maximum air temperature during heat wave periods (R2 = 0.83), indicating LST's efficacy as an indicator for monitoring temperature trends during heat wave events.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141276435","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}
{"title":"Trend and frequency analysis of western disturbances and its impact on major crops of Solan district of Himachal Pradesh","authors":"Prakriti Dadial, Mohan Singh, Purnima Mehta","doi":"10.54386/jam.v26i2.2342","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2342","url":null,"abstract":"The study was conducted to examine the trend and frequency distribution of western disturbances (WD) and their effect on crops grown in Solan district of Himachal Pradesh. The daily rainfall data was collected for the period of 1971–2021. The results revealed that during the period of 50 years, the WD arrived as early as in the month of October and occurred as late as in May in the Solan district of Himachal Pradesh. The duration of WD persisted for 1 to 5 days. The number of WD with 1 day duration was found to be highest in May (89) and lowest during the month of November (21). The Man-Kendall and Sen’s slope estimator analysed an annual increasing trend of Z=2.62 number of WD year-1 and Q=0.47 number of WD year-1. The deterministic coefficient explained the positive relationship between the number of WD and productivity at the development stage while showing a negative relationship at the maturity stage of different crops.\u0000 ","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141398512","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}
{"title":"Innovative trend analysis of annual rainfall in Iraq during 1980-2021","authors":"A. Al-Lami, Y. Al-Timimi, Ali Al-Salihi","doi":"10.54386/jam.v26i2.2561","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2561","url":null,"abstract":"Rainfall trend analysis is essential for managing water resources, agriculture, disaster management, and climate change research. The current study aims to examine annual rainfall variability and trend over 38 meteorological stations in Iraq during the period (1980-2021) using three tests: linear regression analysis (LRA), Mann-Kendall (MK), and the innovative trend analysis (ITA). The results of the three different tests showed that most stations recorded a decreasing trend except for four stations in ITA, six stations in MK, and seven stations in the LRA test, which exhibit a positive trend. However, three stations, Emaidyah, Rabiah, and Biji, showed an increasing trend for all three tests. The ITA test recorded more significant results (14 stations) than the other two tests. The larger significant result appeared in the significance level of 95 % (nine in LRA, eight in MK, and five in ITA). The outcomes of the three trend-detection approaches by assessing the statistical significance levels, 90 %, 95 %, and 99 %, revealed no significant trend in 16 stations dispersed throughout the various climatic zones of Iraq. Only Emadiayah station indicated a positive trend at the significance of 99 %. The overall results showed that the ITA test outperformed the MK and LRA tests since it produced more significant results.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277289","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}
{"title":"Comparison of machine learning classification algorithms based on weather variables and seed characteristics for the selection of paddy seed","authors":"Dhinakaran Sakthipriya, Chandrakumar Thangavel","doi":"10.54386/jam.v26i2.2553","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2553","url":null,"abstract":"Selection of seed is very crucial for the farmers before the start of the crop season. In this study therefore, an attempt has been made to compare various machine learning (ML) classification techniques for paddy seed forecast for cultivation in three major paddy producing taluk of Madurai district, Tamil Nadu viz Thirumangalam, Peraiyur, and Usilampatti. Five machine learning classification techniques viz. K-nearest neighbour (KNN), decision tree (DT), naive bayes (NB), support vector machine (SVM), and logistic regression (LR) used in this study were compared based on weather data and seed characteristics for the better predictions of a paddy seed. Various measures were used to evaluate the algorithms, including F1-score, accuracy, precision, and recall. The findings indicated that the KNN (K-Nearest Neighbour) gave a better accuracy, precision, recall, and F1-score values of about 0.99, 0.94, 1.0, and 0.96 correspondingly. It gave the best result of the paddy seed selection which may be helpful for the farming community in getting higher yield and profit.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141275209","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}