Journal of Agrometeorology

Impact of foliar spray of agrochemicals on biophysical parameters, PAR interception and heat use efficiency of mungbean (Vigna radiata (L.) Wilczek) under variable sowing dates in Punjab, India

2024-04-29T20:28:39+00:00

A study was carried out during kharif season of 2022 and 2023 at the Punjab Agricultural University (PAU)-Regional Research Station (RRS), Ballowal Saunkhri (SBS Nagar) with the objective to find out the impact of foliar spray of agrochemicals on biophysical parameters, PAR interception and heat use efficiency of rainfed mung bean (Vigna radiata (L.) Wilczek) under variable sowing dates. Timely sown crop (second fortnight of July) resulted in higher leaf area index, chlorophyll index, PAR interception and heat use efficiency (HUE) as compared to late sowing (first fortnight of August). Significantly higher seed yield, stover yield and biological yields were obtained in timely sowing during both the years of study. Foliar spray of KNO₃ @ 1.5% recorded significantly higher leaf area index, chlorophyll index, PAR interception, heat use efficiency (HUE) and helio-thermal use efficiency (HTUE) but it was statistically similar with foliar spray of N:P:K (20:20:20) @ 1.5%. Foliar spray of KNO₃ @ 1.5% and N:P:K (20:20:20) @ 1.5% gave statistically similar seed, stover and biological yields and significantly better than other treatments. There was an increase of 33.3% in seed yield with foliar spray of KNO₃ @ 1.5% and increase of 29.1% with foliar spraying of N:P:K (20:20:20) @ 1.5%, when compared with control.

Growth performance and agrometeorological indices of rice under different establishment methods

2023-09-16T04:59:26+00:00

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.

Crop-weather relationship of soybean in Marathwada region of Maharashtra

2023-12-25T02:30:36+00:00

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 (27^th SMW, 28^th SMW, 29^thSMW and 30^th 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

Evaluation of CMIP6 GCMs performance and future projection for the Boro and Kharif seasons over the new alluvial zones of West Bengal

2024-02-16T21:57:35+00:00

Present study examined the overall performance of 12 CMIP6 GCMs for rainfall, maximum and minimum temperatures for rice crop-growing seasons i.e., Boro (January to May) and Kharif (June to October) over the new alluvial zone of West Bengal. A wide range of indices i.e., index of agreement, error indices and bias estimators were utilized to put more confidence on the results. Results indicated that CMIP6 models were able to reproduce observed mean climatology and inter-annual variability of maximum and minimum temperature adequately for both seasons while a smaller number of models (3-4 models) out of a total of 12 GCM-CMIP6 models showed satisfactory performance for rainfall. The ranks assigned to the models revealed that CNRM–ESM2–1 was the best-performing model for Kharif and MRI-ESM2-0 showed the highest skill for Boro. ACCESS-CM2 and MPI-ESM1-2-LR performed worst for Kharif and Boro seasons respectively. Further, CNRM–ESM2–1 and MRI-ESM2-0 were used to project the future climate for Kharif and Boro seasons respectively under both moderate (SSP2-4.5) and extreme scenarios (SSP5-8.5). Higher warming was projected during Boro season than Kharif. Projections revealed increasing rainfall during Kharif season but decreasing rainfall in Boro season in both the moderate and extreme future scenarios.

Weather induced physiological responses on the flowering habits of neem trees (Azadirachta indica)

2023-09-20T07:06:11+00:00

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.

Assessment of climate change impact on sorghum (Sorghum bicolor) production and adaptation strategies in the western zone of Tamil Nadu

2024-03-16T13:33:18+00:00

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.

An assessment of the impact of climate on wheat yield in Indo-Gangetic plain region of India: A panel data analysis

2024-03-20T02:26:04+00:00

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.

Trend and frequency analysis of western disturbances and its impact on major crops of Solan district of Himachal Pradesh

2023-09-15T04:34:29+00:00

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.

Innovative trend analysis of annual rainfall in Iraq during 1980-2021

2024-04-04T01:35:11+00:00

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.

Assessment of heat and cold wave incidences and their link with land surface temperature in Bathinda district of Punjab, India

2023-11-25T15:45:49+00:00

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.

Comparison of machine learning classification algorithms based on weather variables and seed characteristics for the selection of paddy seed

2024-04-06T02:11:35+00:00

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.

Modelling of moisture movement and irrigation scheduling in drip irrigated tomato using CROPWAT and HYDRUS-1D

2024-04-03T05:05:06+00:00

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% ET_C per plant per day was 0.24 l plant^-1day^-1 during the initial stage, 0.37 l plant^-1day^-1 during development stage, 0.85 l plant^-1day^-1 during mid-stage and 0.74 l plant^-1day^-1during 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.

Climatic trends and its impact on reference evapotranspiration and crop water requirement of rice crop in Arunachal Pradesh, India

2024-02-04T19:53:22+00:00

Arunachal Pradesh in one of the largest states in north eastern states of India, having subtropical humid climate influenced by monsoon. An attempt has therefore, been made to understand the climatic conditions of the state and its influence on the reference evapotranspiration (ETo) and crop water requirement (CWR) of rice crop, using 21 years (2001-2021) data of 14 districts of Arunachal Pradesh. The results revealed that the maximum temperature varied from 13⁰C to 30⁰C while minimum temperature varied from 3⁰C to 20⁰C and annual rainfall varied from 1200 mm to 2700 mm across the state. The maximum temperature was found to decrease while the minimum temperature and rainfall were found to increase with varying significant levels in different districts. The mean annual reference evapotranspiration (ETo) was found to vary between 900 mm and 1400 mm. The crop water requirement of rice estimated using CROPWAT model revealed a large spatial variation from 508 mm to 731 mm in different districts of the state.

Drought severity estimation using NDWI index in Parbhani district of Maharashtra

2024-04-10T16:09:00+00:00

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.

Blue and green water footprint assessment of rice crop in high altitude temperate zone of Kashmir, India

2024-04-14T13:26:26+00:00

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. ET₀was 117-133 mm in Budgam district, 100-112 mm in Baramulla district and 143-155 mm in Anantnag district. ET_c 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 (WF_green and WF_blue) also varied with the locations and in years. WF_green and WF_blue contributed more or less equally in Baramulla district, 68% and 32% respectively in Burmuda district and 60% and 40 % in Anantnag districts respectively.

Crop water requirement of rice in different agroclimatic zones of Jharkhand

2023-12-16T04:12:58+00:00

The crop water requirement of rice in different agroclimatic zones of Jharkhand, India was estimated using the CROPWAT 8.0 and CLIMWAT 2.0 models with data collected through NASA data-access-viewer on climate, soil, crop, and water availability. The evapotranspiration (ET_o), effective rainfall (P_eff), and crop water requirement (CWR) for the four zones of the Jharkhand State were calculated. Results revealed that the reference evapotranspiration (ETo) varied from 420.4 mm to 516.5 mm during the crop growing season of rice in different zones. The effective precipitation varied from 748.4 mm to 760.8 mm. The crop water requirement of rice varied from 482.5 mm to 592.4 mm. Effective rainfall was sufficient to meet the water requirement of rice in most of the zones except Alluvial zone wherein the net irrigation water requirement was only 67.6 mm.

Influence of weather factors on population dynamics of major insect pests in moringa (Moringa oleifera Lam.) in south Tamil Nadu

2023-10-25T09:41:23+00:00

The field experiments were conducted to study the relationship of major moringa pests infesting buds (budworm), flowers(ants) and pods (podfly) with weather factors (maximum and minimum temperature and relative humidity and rainfall) during the rabi-summer and kharif seasons of 2021 and 2022 in Dindigul district, Tamil Nadu. The pest population data indicated that the infestations were found to vary with the seasons as well as years. The correlation with weather parameters revealed that the budworm infestation was significant and positively correlated with maximum temperature (r= 0.459^***) and negatively correlated with morning relative humidity (r= -0.277^*), evening relative humidity (r= -0.584^***) and rainfall (r= -0.459^***). While in infestation by ants, it was positively correlated with the maximum temperature (r=0.42^**) and minimum temperature (r= -0.296^*), relative humidity (evening) (r= -0.649^***) and negatively correlated with rainfall (r= -0.382^**). The moringa pod fly infestation had a strong significant positive correlation with relative humidity (evening) (r= 0.7^***) and rainfall (r= 0.517^***) and a negative correlation (r= -0.518^***) with maximum temperature. The stepwise linear regression showed that all the weather factors collectively influenced the budworm infestation by up to 60.7 %, ants infestation by 50.5 % and up to 60.7 % in podfly infestation.

Population prediction model of citrus psylla, Diaphorina citri Kuwayama on Kinnow Mandarin using weather data in Punjab, India

2023-11-29T11:58:41+00:00

Field experiments were carried out to study the population dynamics of citrus psylla, Diaphorina citri Kuwayama on Kinnow Mandarin for twelve years (2007-08 to 2019-20) in relation to different weather parameters and to develop population prediction model. Adult psyllids were observed throughout the year but the population was very low during November-January. Two population peaks were observed during March and September. Highest mean population (80.8 nymphs/25 twigs) was observed during second fortnight of September which varied in different years. Psyllid population showed significant and positive correlation with maximum and minimum temperature, vapour pressure, wind speed, sunshine hours, rainfall and negative correlation with relative humidity and number of rainy days. A weather-based model was developed to predict psylla population seven days in advance. The validation of the model carried out using various indices viz, root mean square error, coefficient of determination, Nash-Sctuliffe efficiency and mean bias error suggested that, the model predicted the population of citrus psylla quite satisfactorily. Thus, the developed model can be used satisfactorily for weather-based prediction of citrus psylla in Punjab, seven days in advance.

Water use efficiency and water productivity of aerobic rice under drip irrigation and fertigation system by using daily soil water balance

2024-03-19T21:50:22+00:00

Crop water and irrigation requirements of major crops in coastal agro-climatic zone of Odisha

2024-02-17T21:30:20+00:00

Crop-weather relationship of finger millet varieties under varying environments at Keonjhar, Odisha

2024-03-23T01:43:39+00:00

Rainfall variability and its effect on kharif rice yield in Manipur: a multi-decadal analysis

2024-02-12T17:40:17+00:00

Application of innovative trend analysis for rainfall variability in the middle catchment of Mahanadi River basin, India

2024-03-06T14:28:06+00:00

Development of weather based statistical models for Rhizoctonia aerial blight disease of soybean in Tarai region of Uttarakhand

2024-02-09T04:53:03+00:00

Climate change adaptation and mitigation in Indian agriculture

2024-04-29T20:24:30+00:00

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.