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.
在作物季节开始之前，选种对农民来说至关重要。因此，本研究尝试对泰米尔纳德邦马杜赖区的三个主要水稻产区，即 Thirumangalam、Peraiyur 和 Usilampatti 的水稻种子种植预测的各种机器学习（ML）分类技术进行比较。为了更好地预测水稻种子，本研究根据气象数据和种子特征对五种机器学习分类技术进行了比较，即 K-近邻（KNN）、决策树（DT）、奈夫贝叶斯（NB）、支持向量机（SVM）和逻辑回归（LR）。评估算法时使用了各种指标，包括 F1 分数、准确度、精确度和召回率。研究结果表明，KNN（K-近邻）的准确度、精确度、召回率和 F1 分数分别为 0.99、0.94、1.0 和 0.96。 它给出了最佳的水稻选种结果，这可能有助于农业社区获得更高的产量和利润。
{"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":"39 4","pages":""},"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}
The study was carried out to investigate the impact of drought on vegetation in Maharashtra's Parbhani district, utilizing remote sensing techniques. Analysis of Landsat 8 data for 2015 (a drought year) and 2020 (a normal year) reveals fluctuations in the Normalized Difference Water Index (NDWI) closely correlated with rainfall patterns. In 2015, NDWI indicated extreme drought conditions, while in 2020, most areas experienced mild drought. The comparison underscores NDWI's sensitivity to rainfall variability and dry spells. Meteorological factors, geographical features, and human activities influence moisture content in vegetation and soil, reflected in the distribution of drought severity classes. In 2020, a higher percentage of the area fell into the moderate drought category, shifting to extreme drought with reduced rainfall. This incremental shift highlights the susceptibility of the Parbhani district to drought conditions, emphasizing the interplay of natural and anthropogenic factors in drought assessment and management.
{"title":"Drought severity estimation using NDWI index in Parbhani district of Maharashtra","authors":"PRITAM PATIL, M. P. Jagtap, K. K. Dakhore","doi":"10.54386/jam.v26i2.2540","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2540","url":null,"abstract":"The study was carried out to investigate the impact of drought on vegetation in Maharashtra's Parbhani district, utilizing remote sensing techniques. Analysis of Landsat 8 data for 2015 (a drought year) and 2020 (a normal year) reveals fluctuations in the Normalized Difference Water Index (NDWI) closely correlated with rainfall patterns. In 2015, NDWI indicated extreme drought conditions, while in 2020, most areas experienced mild drought. The comparison underscores NDWI's sensitivity to rainfall variability and dry spells. Meteorological factors, geographical features, and human activities influence moisture content in vegetation and soil, reflected in the distribution of drought severity classes. In 2020, a higher percentage of the area fell into the moderate drought category, shifting to extreme drought with reduced rainfall. This incremental shift highlights the susceptibility of the Parbhani district to drought conditions, emphasizing the interplay of natural and anthropogenic factors in drought assessment and management.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"43 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141275115","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}
P. Praveenkumar, N. Sathyamoorthy, GA. Dheebakaran, R. Karthikeyan
This study examines the possible effects of climate change on sorghum in the western zone (WZ) comprising Coimbatore, Tirupur, and Erode districts of Tamil Nadu. The DSSAT crop simulation model was used to simulate sorghum yields with considering various planting dates and amounts of fertilizer application. The downscaled CCSM4 climate model data was utilized for the historical baseline period spanning from 1991 to 2020, as well as for future projected data from 2021 to 2099, under the RCP 4.5 scenarios. The key findings indicate that there is a projected yield decline range of -1.3% to 12.5% for the near century (2021-2040), -6.2% to -23.7% for the mid-century (2041-2070), and -12.6% to -30.5% for the end century (2071-2099). The sorghum yield experiences a high decrease at the end of the century (276.83 kg ha-1), mid-century (178.16 kg ha-1), and lastly in the near century (89.4 kg ha-1). The study revealed that a enhanced fertilizer application can have a minor positive effect on sorghum productivity. The study underscores the significant threat that climate change poses to food security in Tamil Nadu and emphasizes the need for adaptation strategies to protect agricultural productivity.
{"title":"Assessment of climate change impact on sorghum (Sorghum bicolor) production and adaptation strategies in the western zone of Tamil Nadu","authors":"P. Praveenkumar, N. Sathyamoorthy, GA. Dheebakaran, R. Karthikeyan","doi":"10.54386/jam.v26i2.2536","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2536","url":null,"abstract":"This study examines the possible effects of climate change on sorghum in the western zone (WZ) comprising Coimbatore, Tirupur, and Erode districts of Tamil Nadu. The DSSAT crop simulation model was used to simulate sorghum yields with considering various planting dates and amounts of fertilizer application. The downscaled CCSM4 climate model data was utilized for the historical baseline period spanning from 1991 to 2020, as well as for future projected data from 2021 to 2099, under the RCP 4.5 scenarios. The key findings indicate that there is a projected yield decline range of -1.3% to 12.5% for the near century (2021-2040), -6.2% to -23.7% for the mid-century (2041-2070), and -12.6% to -30.5% for the end century (2071-2099). The sorghum yield experiences a high decrease at the end of the century (276.83 kg ha-1), mid-century (178.16 kg ha-1), and lastly in the near century (89.4 kg ha-1). The study revealed that a enhanced fertilizer application can have a minor positive effect on sorghum productivity. The study underscores the significant threat that climate change poses to food security in Tamil Nadu and emphasizes the need for adaptation strategies to protect agricultural productivity.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278165","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}
Nuzhat Bint Nazir, Yogesh Pandey, S. Qayoom, S. M. Dadhich
The irrigation systems require modernization and management by evaluating water system prerequisites precisely. A study was carried out at Srinagar during kharif 2022 to determine the crop water demands, irrigation scheduling and simulation of moisture movement under different irrigation regimes on tomato crop in open field conditions using CROPWAT and HYDRUS-1D models. The results revealed that the average crop water requirement at 100% ETC per plant per day was 0.24 l plant-1 day-1 during the initial stage, 0.37 l plant-1 day-1 during development stage, 0.85 l plant-1 day-1 during mid-stage and 0.74 l plant-1 day-1 during the end stage. Soil water content was simulated by HYDRUS-1D model in 0 to 30 cm of soil profile. Higher values (0.86 to 0.95) of coefficient of determination (R2) indicated that observed and simulated values of moisture content are highly correlated and the model predicts that lower values of mean absolute error (MAE) and root mean square error (RMSE) indicates that the HYDRUS-1D model is more accurate at simulating the movement of moisture under different irrigation regimes.
{"title":"Modelling of moisture movement and irrigation scheduling in drip irrigated tomato using CROPWAT and HYDRUS-1D","authors":"Nuzhat Bint Nazir, Yogesh Pandey, S. Qayoom, S. M. Dadhich","doi":"10.54386/jam.v26i2.2492","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2492","url":null,"abstract":"The irrigation systems require modernization and management by evaluating water system prerequisites precisely. A study was carried out at Srinagar during kharif 2022 to determine the crop water demands, irrigation scheduling and simulation of moisture movement under different irrigation regimes on tomato crop in open field conditions using CROPWAT and HYDRUS-1D models. The results revealed that the average crop water requirement at 100% ETC per plant per day was 0.24 l plant-1 day-1 during the initial stage, 0.37 l plant-1 day-1 during development stage, 0.85 l plant-1 day-1 during mid-stage and 0.74 l plant-1 day-1 during the end stage. Soil water content was simulated by HYDRUS-1D model in 0 to 30 cm of soil profile. Higher values (0.86 to 0.95) of coefficient of determination (R2) indicated that observed and simulated values of moisture content are highly correlated and the model predicts that lower values of mean absolute error (MAE) and root mean square error (RMSE) indicates that the HYDRUS-1D model is more accurate at simulating the movement of moisture under different irrigation regimes.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141279184","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}
K. K. DAKHORE, Y. E. KADAM, D. R. KADAM, R. B. MANE, P. S. KAPSE, S. K. BAL
A long-term experiment was conducted during kharif seasons of2013 to 2020 at AICRP on Agrometeorology, VNMKV, Parbhani, to study the crop-weather relationship of soybean grown under four environments (27th SMW, 28th SMW, 29th SMW and 30th SMW) with three soybean varieties (MAUS-158, MAUS-71, and JS-335). Results indicated that soybean yield was significantly highest in (1541.4 kg ha-1) in the early sown crop, and it decreased with delay in sowing with the lowest yield (803.8 kg ha-1). Among the cultivars, MAUS-158 produced significantly the highest yield (1321.3 kg ha-1). Correlation analysis between weather parameters during different phases with the yield revealed that the vegetative and grain formation period of soybean were found to be the most sensitive to weather parameters, as the correlation coefficients with most of the weather parameters. Rainfall, number of rainy days, humidity and soil moisture had favorable effects while temperatures and sunshine duration had negative effects on the yield of soybean in the Marathwada region. Individual weather parameters during 50% flowering to maturity period could explain 40 to 55% variation in the soybean yield while the multiple regression developed all weather parameters during grain formation to physiological maturity period could explain up to 82% variation which could be used the predict the soybean yield in Marathwada region
{"title":"Crop-weather relationship of soybean in Marathwada region of Maharashtra","authors":"K. K. DAKHORE, Y. E. KADAM, D. R. KADAM, R. B. MANE, P. S. KAPSE, S. K. BAL","doi":"10.54386/jam.v26i2.2438","DOIUrl":"https://doi.org/10.54386/jam.v26i2.2438","url":null,"abstract":"A long-term experiment was conducted during kharif seasons of2013 to 2020 at AICRP on Agrometeorology, VNMKV, Parbhani, to study the crop-weather relationship of soybean grown under four environments (27th SMW, 28th SMW, 29th SMW and 30th SMW) with three soybean varieties (MAUS-158, MAUS-71, and JS-335). Results indicated that soybean yield was significantly highest in (1541.4 kg ha-1) in the early sown crop, and it decreased with delay in sowing with the lowest yield (803.8 kg ha-1). Among the cultivars, MAUS-158 produced significantly the highest yield (1321.3 kg ha-1). Correlation analysis between weather parameters during different phases with the yield revealed that the vegetative and grain formation period of soybean were found to be the most sensitive to weather parameters, as the correlation coefficients with most of the weather parameters. Rainfall, number of rainy days, humidity and soil moisture had favorable effects while temperatures and sunshine duration had negative effects on the yield of soybean in the Marathwada region. Individual weather parameters during 50% flowering to maturity period could explain 40 to 55% variation in the soybean yield while the multiple regression developed all weather parameters during grain formation to physiological maturity period could explain up to 82% variation which could be used the predict the soybean yield in Marathwada region","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141281086","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}
Abhishek Painkra, M. Shamim, H. V. Puranik, N. Ravisankar, Prakash Ghasal, Poonam Kashyap, A. K. Prusty, Debashish Dutta
The present study to quantify the variations in microclimate under wheat, mustard and chickpea crops was conducted at ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut (U.P.), India. Air temperature, relative humidity, CO2 concentration below and above the canopies of wheat, mustard and chickpea were recorded at hourly interval from 07:30 to 17:30 hours at different heights (0.5 m, 1.0 m and 2.0 m) from the ground. CO2 probes like GMP-343, (Diffusion aspiration) was used to record data of CO2 concentration and HPM-75 probes was used to capture the observation of air temperature and relative humidity. Results revealed that diurnal air temperature was continuously increasing from morning to afternoon hrs and highest air temperature was recorded at 13:30 hrs (afternoon). Thereafter, air temperature decreased and reached to the lowest at 17:30 hrs irrespective of crops and height from the ground. Analysis of diurnal air temperature variations at different height clearly showed that tall statured crop such as wheat and mustard reached higher air temperature regime early (13.30 hrs) compared to short statured crop like chickpea at 15.30 hrs. Highest relative humidity was observed at 07.30 hrs and lowest relative humidity was recorded either at 13:30 hrs or at 15:30 hrs. As per study maximum CO2 concentration was found at 07:30 hrs morning and minimum at 15:30 hrs. The lowest concentration of CO2 (624 ppm) was recorded from the chickpea field and highest from the mustard field (630 ppm) at the same point of observation during vegetative phase of crops.
{"title":"Microclimatic study under wheat, mustard and chickpea crops in western plain zone of Uttar Pradesh","authors":"Abhishek Painkra, M. Shamim, H. V. Puranik, N. Ravisankar, Prakash Ghasal, Poonam Kashyap, A. K. Prusty, Debashish Dutta","doi":"10.54386/jam.v26i1.2340","DOIUrl":"https://doi.org/10.54386/jam.v26i1.2340","url":null,"abstract":"The present study to quantify the variations in microclimate under wheat, mustard and chickpea crops was conducted at ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut (U.P.), India. Air temperature, relative humidity, CO2 concentration below and above the canopies of wheat, mustard and chickpea were recorded at hourly interval from 07:30 to 17:30 hours at different heights (0.5 m, 1.0 m and 2.0 m) from the ground. CO2 probes like GMP-343, (Diffusion aspiration) was used to record data of CO2 concentration and HPM-75 probes was used to capture the observation of air temperature and relative humidity. Results revealed that diurnal air temperature was continuously increasing from morning to afternoon hrs and highest air temperature was recorded at 13:30 hrs (afternoon). Thereafter, air temperature decreased and reached to the lowest at 17:30 hrs irrespective of crops and height from the ground. Analysis of diurnal air temperature variations at different height clearly showed that tall statured crop such as wheat and mustard reached higher air temperature regime early (13.30 hrs) compared to short statured crop like chickpea at 15.30 hrs. Highest relative humidity was observed at 07.30 hrs and lowest relative humidity was recorded either at 13:30 hrs or at 15:30 hrs. As per study maximum CO2 concentration was found at 07:30 hrs morning and minimum at 15:30 hrs. The lowest concentration of CO2 (624 ppm) was recorded from the chickpea field and highest from the mustard field (630 ppm) at the same point of observation during vegetative phase of crops.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"115 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140088213","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}
Drought is one of the most common natural disasters globally, having major impacts on environmental, economic, and social conditions and Ethiopia is no exception particularly the Oromia region. In order to evaluate and characterize the meteorological droughts associated with El Niño years over the Oromia region, the satellite data CHIRPS was used. The monthly time series data for the period from 1991 to 2020 was used for temporal and spatial analysis of meteorological drought using standardized precipitation index (SPI) across SPI3, SPI6, SPI9 and SPI12 indices using GeoCLIM, GIS, and Python tools. The results of this study show that meteorological droughts during the El Niño years indicated an increment across weak, moderate, and strong El Niño events over the Oromia region. The dryness was visualized with frequency and duration in time-scale across short-term drought indices in time steps. The time-scale temporal meteorological drought indices in three to twelve months show that the drought indices varied in magnitude, duration, and frequency in meteorological droughts. In general, the meteorological drought severity of correlation for the remaining zones analysis between SPI3 and SPI6, SPI6 and SPI12, and SPI9 and SPI12 indices was dominated by an increment of the correlation values over short to long timescales over the study area.
{"title":"Spatiotemporal analysis of meteorological drought in El Niño years over Oromia region, Ethiopia","authors":"Gezahegn Mergia","doi":"10.54386/jam.v26i1.2329","DOIUrl":"https://doi.org/10.54386/jam.v26i1.2329","url":null,"abstract":"Drought is one of the most common natural disasters globally, having major impacts on environmental, economic, and social conditions and Ethiopia is no exception particularly the Oromia region. In order to evaluate and characterize the meteorological droughts associated with El Niño years over the Oromia region, the satellite data CHIRPS was used. The monthly time series data for the period from 1991 to 2020 was used for temporal and spatial analysis of meteorological drought using standardized precipitation index (SPI) across SPI3, SPI6, SPI9 and SPI12 indices using GeoCLIM, GIS, and Python tools. The results of this study show that meteorological droughts during the El Niño years indicated an increment across weak, moderate, and strong El Niño events over the Oromia region. The dryness was visualized with frequency and duration in time-scale across short-term drought indices in time steps. The time-scale temporal meteorological drought indices in three to twelve months show that the drought indices varied in magnitude, duration, and frequency in meteorological droughts. In general, the meteorological drought severity of correlation for the remaining zones analysis between SPI3 and SPI6, SPI6 and SPI12, and SPI9 and SPI12 indices was dominated by an increment of the correlation values over short to long timescales over the study area.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140090865","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}
V. Sunil, V. J. Lakshmi, K. Chiranjeevi, D. SANJEEVA RAO, M. SAMPATH KUMAR
Feeding behavior of brown planthopper, Nilaparvata lugens (Stål) populations collected from different geographical regions Ludhiana, Nalgonda and West Godavari at three generations 1, 5 and 10 fed on rice plants grown under different CO2 and temperature levels 1) Ambient CO2@ 380±25ppm + ambient temperature (aCO2+aT), 2) Elevated CO2@500±25ppm + ambient temperature (eCO2+aT) and 3) Elevated CO2@500±25ppm + elevated temperature (eCO2+eT) in closed CO2 chambers was studied. Elevated CO2 + elevated temperature increased feeding rate of BPH nymphs while BPH adults showed declined feeding rate. BPH nymphal feeding rate increased with progressive generations while it decreased in BPH adults. Ludhiana adult BPH population showed higher honeydew excretion compared to West Godavari and Nalgonda populations. CO2 + temperature levels at progressive generations have varying effects on adults and nymphs of three BPH populations. Biochemical composition of rice plants grown under different CO2 levels revealed increased rate of soluble sugars, phenols and decreased rate of reducing sugars, soluble proteins, free amino acids, nitrogen, potassium, phosphorous in elevated CO2 + elevated temperature levels compared to ambient conditions. Increased feeding rate of BPH under elevated CO2 levels may be to compensate changes in host plant quality i.e., high soluble sugars and low nitrogen.
{"title":"Rice brown planthopper, Nilaparvata lugens (Stål) feeding behavior in relation to elevated CO2 and temperature","authors":"V. Sunil, V. J. Lakshmi, K. Chiranjeevi, D. SANJEEVA RAO, M. SAMPATH KUMAR","doi":"10.54386/jam.v26i1.2519","DOIUrl":"https://doi.org/10.54386/jam.v26i1.2519","url":null,"abstract":"Feeding behavior of brown planthopper, Nilaparvata lugens (Stål) populations collected from different geographical regions Ludhiana, Nalgonda and West Godavari at three generations 1, 5 and 10 fed on rice plants grown under different CO2 and temperature levels 1) Ambient CO2@ 380±25ppm + ambient temperature (aCO2+aT), 2) Elevated CO2@500±25ppm + ambient temperature (eCO2+aT) and 3) Elevated CO2@500±25ppm + elevated temperature (eCO2+eT) in closed CO2 chambers was studied. Elevated CO2 + elevated temperature increased feeding rate of BPH nymphs while BPH adults showed declined feeding rate. BPH nymphal feeding rate increased with progressive generations while it decreased in BPH adults. Ludhiana adult BPH population showed higher honeydew excretion compared to West Godavari and Nalgonda populations. CO2 + temperature levels at progressive generations have varying effects on adults and nymphs of three BPH populations. Biochemical composition of rice plants grown under different CO2 levels revealed increased rate of soluble sugars, phenols and decreased rate of reducing sugars, soluble proteins, free amino acids, nitrogen, potassium, phosphorous in elevated CO2 + elevated temperature levels compared to ambient conditions. Increased feeding rate of BPH under elevated CO2 levels may be to compensate changes in host plant quality i.e., high soluble sugars and low nitrogen.","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140091815","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}
Sonali Swagatika, J. C. Paul, D. M. Das, S. K. Raul, A. P. Sahu
{"title":"Impact of climate change on runoff and potential evapotranspiration in Brahmani basin, Odisha, India","authors":"Sonali Swagatika, J. C. Paul, D. M. Das, S. K. Raul, A. P. Sahu","doi":"10.54386/jam.v26i1.2489","DOIUrl":"https://doi.org/10.54386/jam.v26i1.2489","url":null,"abstract":"","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":" 1062","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140091874","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":"Extraction of MODIS land surface temperature and its validation over Samastipur district of Bihar","authors":"RAJESH G. M., SUDARSHAN PRASAD","doi":"10.54386/jam.v26i1.2279","DOIUrl":"https://doi.org/10.54386/jam.v26i1.2279","url":null,"abstract":"","PeriodicalId":56127,"journal":{"name":"Journal of Agrometeorology","volume":"6 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140083740","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}
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