P. Amrate, Kailash Chaukika, Sanjay Kharte, D. K. Pancheshwar, R.S. Marabi, M.K. Shrivastav, M. Bhale
Background: Macrophomina phaseolina (Tassi) Goid is a necrotrophic soil-inhabiting fungus that causes disease in several economic plants worldwide and has now become a serious threat to soybean cultivation in central India. Methods: The random surveys were done during 2018 and 2019 to determine the present status of charcoal rot (M. phaseolina) in key soybean growing districts of Madhya Pradesh. Sixteen isolates of pathogen were characterized based on morpho-cultural and pathogenic variability by using cut stem inoculation techniques at J.N.K.V.V., Jabalpur. Result: Charcoal rot was prevalent in all surveyed sixteen districts of Madhya Pradesh. Out of six, Kymore plateau and Satpura hills (44.5%), Satpura plateau (42.5%), Central Narmada Valley (42.0%) and Vindhyan plateau agroclimatic zones (35.0%) were identified as favouable zones for charcoal rot. Malwa plateau (16.25%) and Northern hill region (24.5%) had low incidences of charcoal rot. Among varieties, JS 95-60, JS 93-05 and JS 20-29 were highly affected, whereas, JS 20-34, JS 20-98 and JS 20-69 were least affected. Incidence of charcoal rot was comparatively higher in the fields that had Maize-Chickpea (26.32%), Maize-Wheat, Soybean- Pea and Soybean - Chickpea cropping patterns in the previous year and lowest in Rice-Chickpea (12.00%) and Rice - Wheat (12.45%) cropping patterns. The incidence of charcoal rot was partially higher in the fields with light soil (21.3%) than in heavy soil (19.0%). Isolates investigation revealed that isolates from Jabalpur, Hoshangabad, Chhindwara and Sagar were fast-growing variables and highly aggressive in developing necrotic lesions on the cut stem of soybean. This investigation could be instrumental in forewarning sensitive areas of charcoal rot, varietal options and crop rotation to be followed to minimize the incidence of charcoal rot. Moreover, identified variable aggressive isolates could be utilized in genotype resistance screening programs.
{"title":"Distribution of Charcoal Rot of Soybean, its Influencing Factors and Pathogenic Variabilities in Different Regions of Madhya Pradesh","authors":"P. Amrate, Kailash Chaukika, Sanjay Kharte, D. K. Pancheshwar, R.S. Marabi, M.K. Shrivastav, M. Bhale","doi":"10.18805/lr-5262","DOIUrl":"https://doi.org/10.18805/lr-5262","url":null,"abstract":"Background: Macrophomina phaseolina (Tassi) Goid is a necrotrophic soil-inhabiting fungus that causes disease in several economic plants worldwide and has now become a serious threat to soybean cultivation in central India. Methods: The random surveys were done during 2018 and 2019 to determine the present status of charcoal rot (M. phaseolina) in key soybean growing districts of Madhya Pradesh. Sixteen isolates of pathogen were characterized based on morpho-cultural and pathogenic variability by using cut stem inoculation techniques at J.N.K.V.V., Jabalpur. Result: Charcoal rot was prevalent in all surveyed sixteen districts of Madhya Pradesh. Out of six, Kymore plateau and Satpura hills (44.5%), Satpura plateau (42.5%), Central Narmada Valley (42.0%) and Vindhyan plateau agroclimatic zones (35.0%) were identified as favouable zones for charcoal rot. Malwa plateau (16.25%) and Northern hill region (24.5%) had low incidences of charcoal rot. Among varieties, JS 95-60, JS 93-05 and JS 20-29 were highly affected, whereas, JS 20-34, JS 20-98 and JS 20-69 were least affected. Incidence of charcoal rot was comparatively higher in the fields that had Maize-Chickpea (26.32%), Maize-Wheat, Soybean- Pea and Soybean - Chickpea cropping patterns in the previous year and lowest in Rice-Chickpea (12.00%) and Rice - Wheat (12.45%) cropping patterns. The incidence of charcoal rot was partially higher in the fields with light soil (21.3%) than in heavy soil (19.0%). Isolates investigation revealed that isolates from Jabalpur, Hoshangabad, Chhindwara and Sagar were fast-growing variables and highly aggressive in developing necrotic lesions on the cut stem of soybean. This investigation could be instrumental in forewarning sensitive areas of charcoal rot, varietal options and crop rotation to be followed to minimize the incidence of charcoal rot. Moreover, identified variable aggressive isolates could be utilized in genotype resistance screening programs.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"11 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140715439","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}
Udit Kumar, Nishiprabha Behera, K. Prasad, Pramila, Dharminder, Kaushal Kishor, R. Tiwari, B. Upadhaya, Sunil Kumar, Vivek Kumar
Background: The optimum sowing date is crucial among the different agronomic procedures for maximizing output. Optimizing a crop's planting time may be one of the most significant climate resilient tactics for increasing production and hence it becomes necessary to study the crop growth behaviors in changing climatic conditions. The proposed field investigations were undertaken to study the influence of different sowing dates on yield of vegetable pea. Methods: Field investigations were undertaken during Rabi seasons of 2020-21 and 2021-22 at the Vegetable Research Farm, Department of Horticulture, Dr. Rajendra Prasad Central Agricultural University, Pusa (85.67oE - 25.98oN.), which comes under sub-Himalayan foothills region of India. The research study was performed in Randomized Block Design with three replications consisting of eight different sowing dates of vegetable pea. cv. Azad Pea-3 at 10 days interval between each sowing dates. Observations were made on various growth and yield attributing parameters. Result: Results revealed that the parameters under study were substantially affected by various sowing dates. Second week of sowing in November in the years produced maximum plant height at 60 DAS (83.77cm), number of branches per plant (3.97), number of nodules per plant at flowering (26.13), number of green pods per plant (20.80), 10 pods weight (75.67g) and pod yield (52.06q/ha).
{"title":"Impact of Different Sowing Dates on Growth and Pod Yield of Vegetable Pea under Sub-Himalayan Foothills Region of India","authors":"Udit Kumar, Nishiprabha Behera, K. Prasad, Pramila, Dharminder, Kaushal Kishor, R. Tiwari, B. Upadhaya, Sunil Kumar, Vivek Kumar","doi":"10.18805/lr-5158","DOIUrl":"https://doi.org/10.18805/lr-5158","url":null,"abstract":"Background: The optimum sowing date is crucial among the different agronomic procedures for maximizing output. Optimizing a crop's planting time may be one of the most significant climate resilient tactics for increasing production and hence it becomes necessary to study the crop growth behaviors in changing climatic conditions. The proposed field investigations were undertaken to study the influence of different sowing dates on yield of vegetable pea. Methods: Field investigations were undertaken during Rabi seasons of 2020-21 and 2021-22 at the Vegetable Research Farm, Department of Horticulture, Dr. Rajendra Prasad Central Agricultural University, Pusa (85.67oE - 25.98oN.), which comes under sub-Himalayan foothills region of India. The research study was performed in Randomized Block Design with three replications consisting of eight different sowing dates of vegetable pea. cv. Azad Pea-3 at 10 days interval between each sowing dates. Observations were made on various growth and yield attributing parameters. Result: Results revealed that the parameters under study were substantially affected by various sowing dates. Second week of sowing in November in the years produced maximum plant height at 60 DAS (83.77cm), number of branches per plant (3.97), number of nodules per plant at flowering (26.13), number of green pods per plant (20.80), 10 pods weight (75.67g) and pod yield (52.06q/ha).\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"14 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140715287","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. Natarajan, Noorjehan A. K. A. Hanif, J. Jayakumar, K. Senguttuvan, G. Gayathry, K. B. Kumar, P. Veeramani, S. Kannan, A.S. Mailappa
Background: Groundnut is a prominent oilseed crop in India but its productivity is far below the potential yield due to lack of knowledge and adoption of improved varieties and technologies. Technology gap is a major problem in groundnut production in North Eastern zone of Tamil Nadu State in which Cuddalore district falls. A scientific and systematic effort was made to study the impact on yield by assessing technological gap existing in various components of groundnut cultivation through cluster frontline demonstrations (CFLDs) with scientific technologies. Methods: Cluster Frontline Demonstrations was implemented in groundnut to improve the production potential of improved varieties and new technologies through Krishi Vigyan Kendra (KVK). The study with one of its objective to assess yield and technology gap in groundnut was conducted with 175 demonstrations during the period from 2020-21 to 2022-23 covering seven blocks in an area of 70 hectares in Cuddalore district following cluster random sampling method. Two main varieties VRI 8 and VRI 10 along with improved technologies were demonstrated in farmer’s field by providing necessary critical inputs seed pods, bio control agents along with seed drill sowing, Result: There resulted 62.13 per cent increase in yield as observed in demonstration plots over farmers’ practices in groundnut. The study revealed that in groundnut, the average extension gap (difference of demo and farmer plot yield) is 16.26 q/ha, average technology gap (difference of potential and demo plot yield) is 12.21 q/ha and average technology index of demonstrations is 22.21 per cent. The higher average net returns (Rs. 149758/ha) were recorded in demonstration plot (BCR 2.3) compared to farmers’ plot. The Sustainability Yield Index (SYI) and Sustainability Value Index (SVI) in demo plot are higher consistently than farmers plot mainly due to the effect of cluster frontline demonstrations with proper application of inputs/technologies viz., VRI 8 and VRI 10 varieties, seed treatment with bio fertilizers, bio control agents, soil test based nutrient management, application of TNAU crop booster groundnut rich and gypsum application.
{"title":"A Study on Yield and Value Sustainability in Groundnut (Arachis hypogea) Through Cluster Frontline Demonstrations Approach in Cuddalore District of Tamil Nadu","authors":"K. Natarajan, Noorjehan A. K. A. Hanif, J. Jayakumar, K. Senguttuvan, G. Gayathry, K. B. Kumar, P. Veeramani, S. Kannan, A.S. Mailappa","doi":"10.18805/lr-5292","DOIUrl":"https://doi.org/10.18805/lr-5292","url":null,"abstract":"Background: Groundnut is a prominent oilseed crop in India but its productivity is far below the potential yield due to lack of knowledge and adoption of improved varieties and technologies. Technology gap is a major problem in groundnut production in North Eastern zone of Tamil Nadu State in which Cuddalore district falls. A scientific and systematic effort was made to study the impact on yield by assessing technological gap existing in various components of groundnut cultivation through cluster frontline demonstrations (CFLDs) with scientific technologies. Methods: Cluster Frontline Demonstrations was implemented in groundnut to improve the production potential of improved varieties and new technologies through Krishi Vigyan Kendra (KVK). The study with one of its objective to assess yield and technology gap in groundnut was conducted with 175 demonstrations during the period from 2020-21 to 2022-23 covering seven blocks in an area of 70 hectares in Cuddalore district following cluster random sampling method. Two main varieties VRI 8 and VRI 10 along with improved technologies were demonstrated in farmer’s field by providing necessary critical inputs seed pods, bio control agents along with seed drill sowing, Result: There resulted 62.13 per cent increase in yield as observed in demonstration plots over farmers’ practices in groundnut. The study revealed that in groundnut, the average extension gap (difference of demo and farmer plot yield) is 16.26 q/ha, average technology gap (difference of potential and demo plot yield) is 12.21 q/ha and average technology index of demonstrations is 22.21 per cent. The higher average net returns (Rs. 149758/ha) were recorded in demonstration plot (BCR 2.3) compared to farmers’ plot. The Sustainability Yield Index (SYI) and Sustainability Value Index (SVI) in demo plot are higher consistently than farmers plot mainly due to the effect of cluster frontline demonstrations with proper application of inputs/technologies viz., VRI 8 and VRI 10 varieties, seed treatment with bio fertilizers, bio control agents, soil test based nutrient management, application of TNAU crop booster groundnut rich and gypsum application.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717919","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}
Subhrajyoti Chatterjee, Debmala Mukherjee, Partha Choudhuri, P. K. Maurya, A. Maji, A. Mandal, A. Chattopadhyay
Background: French bean (Phaseolus vulgaris L.) production in the tropics is threatened by heavy incidence of anthracnose disease causing substantial crop loss when infection is at the early growth stages. Breeding strategies for tolerance against anthracnose disease along with enhanced productivity, and high pod protein content are to be formulated. Methods: Genotypes having broad genetic base and phenotypic diversity in 5 bush and 1 pole types were crossed in a 6 × 6 half diallel mating design to estimate combining ability, mode of gene action, and extent of heterosis for 11 quantitative traits. Result: The additive genetic effect was evident for percent disease index (PDI) of anthracnose and 10 pod weight. Rapid genetic gain can be achieved due to predominance of additive gene action in their control and can therefore be selected in early generation through simple breeding methods. Rest of the economic traits controlled by additive and non-additive gene effects could be improved through biparental mating, reciprocal recurrent selection, or diallel selective mating. Anthracnose disease tolerant and high yielding cultivars of might be developed utilizing parents, ‘Laxmi’, ‘Arka Sharath’ and ‘Vaishnavi-264’ with high gca effects. Although two cross combinations ‘Arka Sharath × Lakshmi’ and ‘Arjun × Arka Sharath’ showed significant heterobeltiosis in desired direction for PDI of anthracnose and other desirable horticultural traits but could not be exploited at commercial level due to complexity in hybridization. Identifying pure lines with tolerance against anthracnose disease and favorable horticultural attributes could be accomplished in segregating generations of the prospective hybrids.
{"title":"Breeding Strategies for Simultaneous Improvement in Anthracnose Disease Resistance and Economically Important Traits in French Bean","authors":"Subhrajyoti Chatterjee, Debmala Mukherjee, Partha Choudhuri, P. K. Maurya, A. Maji, A. Mandal, A. Chattopadhyay","doi":"10.18805/lr-5279","DOIUrl":"https://doi.org/10.18805/lr-5279","url":null,"abstract":"Background: French bean (Phaseolus vulgaris L.) production in the tropics is threatened by heavy incidence of anthracnose disease causing substantial crop loss when infection is at the early growth stages. Breeding strategies for tolerance against anthracnose disease along with enhanced productivity, and high pod protein content are to be formulated. Methods: Genotypes having broad genetic base and phenotypic diversity in 5 bush and 1 pole types were crossed in a 6 × 6 half diallel mating design to estimate combining ability, mode of gene action, and extent of heterosis for 11 quantitative traits. Result: The additive genetic effect was evident for percent disease index (PDI) of anthracnose and 10 pod weight. Rapid genetic gain can be achieved due to predominance of additive gene action in their control and can therefore be selected in early generation through simple breeding methods. Rest of the economic traits controlled by additive and non-additive gene effects could be improved through biparental mating, reciprocal recurrent selection, or diallel selective mating. Anthracnose disease tolerant and high yielding cultivars of might be developed utilizing parents, ‘Laxmi’, ‘Arka Sharath’ and ‘Vaishnavi-264’ with high gca effects. Although two cross combinations ‘Arka Sharath × Lakshmi’ and ‘Arjun × Arka Sharath’ showed significant heterobeltiosis in desired direction for PDI of anthracnose and other desirable horticultural traits but could not be exploited at commercial level due to complexity in hybridization. Identifying pure lines with tolerance against anthracnose disease and favorable horticultural attributes could be accomplished in segregating generations of the prospective hybrids.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"92 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140720510","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}
In Seop Na, Sungkeun Lee, Atif M. Alamri, Salman A. AlQahtani
Background: For the enhancement of agricultural productivity, while ensuring sustainability, this study delves into the under-explored domain of monitoring legume crop health and growth. Traditional methods of crop assessment encounter limitations, prompting a push for innovation by integrating advanced remote sensing technologies and artificial intelligence (AI). The purpose is to revolutionize crop assessment techniques and overcome existing constraints. Methods: The data was collected using a combination of satellite imagery and ground-based sensors, resulting in a rich repository of multispectral and spatial information. By using the capabilities of AI, a robust model was developed to interpret the gathered data, offering a detailed insight into the health and growth dynamics of legume crops. The AI algorithms not only identify anomalies but also forecast future states, facilitating timely interventions and informed decision-making in agriculture. Result: The findings of this study signify a significant change in precision agriculture, where the synergy of remote sensing and AI optimizes resource allocation, minimizes environmental impact and maximizes crop yields. The research unlocks the potential to transform legume farming practices, promoting sustainability and ushering in an era of data-driven cultivation. The implications extend beyond the legume crop sector, influencing the broader agricultural landscape with the promise of more efficient and sustainable practices.
{"title":"Remote Sensing and AI-based Monitoring of Legume Crop Health and Growth","authors":"In Seop Na, Sungkeun Lee, Atif M. Alamri, Salman A. AlQahtani","doi":"10.18805/lrf-795","DOIUrl":"https://doi.org/10.18805/lrf-795","url":null,"abstract":"Background: For the enhancement of agricultural productivity, while ensuring sustainability, this study delves into the under-explored domain of monitoring legume crop health and growth. Traditional methods of crop assessment encounter limitations, prompting a push for innovation by integrating advanced remote sensing technologies and artificial intelligence (AI). The purpose is to revolutionize crop assessment techniques and overcome existing constraints. Methods: The data was collected using a combination of satellite imagery and ground-based sensors, resulting in a rich repository of multispectral and spatial information. By using the capabilities of AI, a robust model was developed to interpret the gathered data, offering a detailed insight into the health and growth dynamics of legume crops. The AI algorithms not only identify anomalies but also forecast future states, facilitating timely interventions and informed decision-making in agriculture. Result: The findings of this study signify a significant change in precision agriculture, where the synergy of remote sensing and AI optimizes resource allocation, minimizes environmental impact and maximizes crop yields. The research unlocks the potential to transform legume farming practices, promoting sustainability and ushering in an era of data-driven cultivation. The implications extend beyond the legume crop sector, influencing the broader agricultural landscape with the promise of more efficient and sustainable practices.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"134 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140720010","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}
Background: In the realm of agriculture, the insidious menace of legume crop diseases looms large, posing a significant threat to food security. This study embarks on a transformative journey, harnessing the prowess of Convolutional Neural Networks (CNNs), to fortify early disease detection in legume crops. By utilizing the inherent capabilities of deep learning, try to develop a sentinel that can identify even the most minor signs of crop diseases. Thorough data curation and preprocessing provide the system the ability to examine photos of legume leaves with previously unheard-of clarity. Methods: Meticulously crafted, the CNN architecture plays the role of a virtuoso, skilfully traversing the convolutional layers. It gains proficiency in the complex language of illness-induced aberrations via intense training, enabling it to discern between health and illness. Result: Provide remarkable results from the experimental experience using a wide range of assessment metrics. By undertaking this project, the commitment to preserving agricultural yields and, consequently, global food security is reaffirmed. It portends a more optimistic future for legume farming by indicating a ground-breaking effort at the nexus of artificial intelligence and agriculture.
{"title":"Exploring Advanced Machine Learning Techniques for Swift Legume Disease Detection","authors":"Ok-Hue Cho, In Seop Na, Jin Gwang Koh","doi":"10.18805/lrf-789","DOIUrl":"https://doi.org/10.18805/lrf-789","url":null,"abstract":"Background: In the realm of agriculture, the insidious menace of legume crop diseases looms large, posing a significant threat to food security. This study embarks on a transformative journey, harnessing the prowess of Convolutional Neural Networks (CNNs), to fortify early disease detection in legume crops. By utilizing the inherent capabilities of deep learning, try to develop a sentinel that can identify even the most minor signs of crop diseases. Thorough data curation and preprocessing provide the system the ability to examine photos of legume leaves with previously unheard-of clarity. Methods: Meticulously crafted, the CNN architecture plays the role of a virtuoso, skilfully traversing the convolutional layers. It gains proficiency in the complex language of illness-induced aberrations via intense training, enabling it to discern between health and illness. Result: Provide remarkable results from the experimental experience using a wide range of assessment metrics. By undertaking this project, the commitment to preserving agricultural yields and, consequently, global food security is reaffirmed. It portends a more optimistic future for legume farming by indicating a ground-breaking effort at the nexus of artificial intelligence and agriculture.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"100 S104","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140731736","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}
B. Saliha, R. Indrani, A. Anuratha, T. S. J. Rajammal, A.H. Syed Hussainy, R. Murugaragavan
Background: In recent years, there is growing demand for pulses in Tamil Nadu and the government has implemented various schemes and programmes to promote cultivation. However, the evaluation and categorization of soils for pulse production is crucial in determining the suitability of land for pulse cultivation and offer improvement through the adoption of improved crop management practices. Methods: A systematic soil quality assessment survey was taken up during 2020-2022 in the major pulse growing blocks of Virudhunagar district viz., Sattur, Aruppukottai and Thiruchuli based on past ten years yield data and it was classified into three categories viz., low yielding ( less than 400 kg ha-1), medium (400 to 700 kg ha-1) and high yielding ( greater than 700 kg ha-1) categories. Three hundred samples were collected from these zones. Results: The positive effects of soil physical, chemical, and biological qualities on the yield of pulse crops were justified through the yield data of the high yielding zone which ranged from 769 to 989 kg ha-1 with an average pulse yield of 880 kg ha-1. This may be attributed to more favourable soil physical environment in terms of soil texture (sandy clay loam), higher mean percentage of water stable aggregates (51%) and a favourable pH of 7.52. These parameters coupled with lower bulk density (1.23 Mgm-3), optimum infiltration rate (1.76 cm hr-1) and maximum mean organic carbon status (1.38 mg kg-1) contributed to higher range of soil cation exchange capacity (28.7 to 47.2 cmol p+ kg-1). In addition, the presence of avilable nitrogen and phosphorus, potassium, sulphur and availability of mean micronutrient contents viz., DTPA iron and DTPA zinc resulted in better quality of these soils contributing to maximum pulse productivity in this zone. Soil respiration rate with mean respiration rate of 4.48 mg CO2 kg-1 d-1 in high yield category compared to that of 2.34 mg CO2 kg-1 d-1 in low yield category, which is well correlated with better soil organic matter content in the former than the latter group of soil. Therefore, this study formulates a clear understanding of the variations in soil quality parameters for adopting efficient nutrient management practices towards obtaining maximum productivity of pulse crops.
{"title":"Evaluating the Soil Quality Indicators in Various Yield Zones of Pulses in Tamil Nadu, India","authors":"B. Saliha, R. Indrani, A. Anuratha, T. S. J. Rajammal, A.H. Syed Hussainy, R. Murugaragavan","doi":"10.18805/lr-5202","DOIUrl":"https://doi.org/10.18805/lr-5202","url":null,"abstract":"Background: In recent years, there is growing demand for pulses in Tamil Nadu and the government has implemented various schemes and programmes to promote cultivation. However, the evaluation and categorization of soils for pulse production is crucial in determining the suitability of land for pulse cultivation and offer improvement through the adoption of improved crop management practices. Methods: A systematic soil quality assessment survey was taken up during 2020-2022 in the major pulse growing blocks of Virudhunagar district viz., Sattur, Aruppukottai and Thiruchuli based on past ten years yield data and it was classified into three categories viz., low yielding ( less than 400 kg ha-1), medium (400 to 700 kg ha-1) and high yielding ( greater than 700 kg ha-1) categories. Three hundred samples were collected from these zones. Results: The positive effects of soil physical, chemical, and biological qualities on the yield of pulse crops were justified through the yield data of the high yielding zone which ranged from 769 to 989 kg ha-1 with an average pulse yield of 880 kg ha-1. This may be attributed to more favourable soil physical environment in terms of soil texture (sandy clay loam), higher mean percentage of water stable aggregates (51%) and a favourable pH of 7.52. These parameters coupled with lower bulk density (1.23 Mgm-3), optimum infiltration rate (1.76 cm hr-1) and maximum mean organic carbon status (1.38 mg kg-1) contributed to higher range of soil cation exchange capacity (28.7 to 47.2 cmol p+ kg-1). In addition, the presence of avilable nitrogen and phosphorus, potassium, sulphur and availability of mean micronutrient contents viz., DTPA iron and DTPA zinc resulted in better quality of these soils contributing to maximum pulse productivity in this zone. Soil respiration rate with mean respiration rate of 4.48 mg CO2 kg-1 d-1 in high yield category compared to that of 2.34 mg CO2 kg-1 d-1 in low yield category, which is well correlated with better soil organic matter content in the former than the latter group of soil. Therefore, this study formulates a clear understanding of the variations in soil quality parameters for adopting efficient nutrient management practices towards obtaining maximum productivity of pulse crops.","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"198 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140740172","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}
Kartikey Singh, B.K. Singh, A. K. Singh, Rakesh Pandey, Awnindra Kumar Singh, Saurabh Singh, Happy Singh
Background: The pod fly, Melanagromyza obtusa (Malloch) is one of the major biotic constraints in increasing production and productivity of pigeonpea crop throughout the country and it causes up to 100 per cent losses in field condition. Injudicious use of pesticides against this destructive pest, further ignites the problem of resistance, resurgence and environmental and ecological imbalances. Methods: Experiments were conducted at Banda University of Agricultural and Technology, Banda during kharif, 2020 and 2021. To estimate the bio-efficacy of insecticides for the management of M. obtusa in pigeonpea the experiment was laid out in randomized block design (RBD) with eight treatments and three replications. Pod and grain damage were assessed and C:B ratio was calculated. Result: First appearance of pod fly was noticed in third standard week. Throughout cropping period highest pod damage was recorded in eighth standard week and lowest pod damage was recorded in twelfth standard week. Emamectin benzoate 5 SG @ 11g a.i./ha + Dimethoate 30 EC @ 300 g a.i./ha was the best treatment as it exhibited minimum pod damage and highest yield.
背景：豆荚蝇（Melanagromyza obtusa (Malloch)）是全国各地鸽子豆作物增产的主要生物制约因素之一，在田间造成的损失高达 100%。对这种毁灭性害虫滥用杀虫剂，进一步引发了抗药性、死灰复燃以及环境和生态失衡等问题。研究方法在 2020 年和 2021 年的收获季节，在班达农业与技术大学（Banda University of Agricultural and Technology, Banda）进行了实验。为了评估杀虫剂在防治鸽子豆上的害虫方面的生物功效，实验采用了随机区组设计（RBD），共有八个处理和三次重复。评估了荚果和谷粒的损害情况，并计算了 C:B 比率。结果豆荚实蝇在第三个标准周首次出现。在整个种植期间，第八个标准周的豆荚受害程度最高，第十二个标准周的豆荚受害程度最低。Emamectin benzoate 5 SG @ 11g a.i./ha + Dimethoate 30 EC @ 300 g a.i./ha 的处理效果最好，因为豆荚受害最少，产量最高。
{"title":"Damage of Melanagromyza obtusa (Malloch) and Management Potential of Newer Insecticides in Pigeon Pea","authors":"Kartikey Singh, B.K. Singh, A. K. Singh, Rakesh Pandey, Awnindra Kumar Singh, Saurabh Singh, Happy Singh","doi":"10.18805/lr-5258","DOIUrl":"https://doi.org/10.18805/lr-5258","url":null,"abstract":"Background: The pod fly, Melanagromyza obtusa (Malloch) is one of the major biotic constraints in increasing production and productivity of pigeonpea crop throughout the country and it causes up to 100 per cent losses in field condition. Injudicious use of pesticides against this destructive pest, further ignites the problem of resistance, resurgence and environmental and ecological imbalances. Methods: Experiments were conducted at Banda University of Agricultural and Technology, Banda during kharif, 2020 and 2021. To estimate the bio-efficacy of insecticides for the management of M. obtusa in pigeonpea the experiment was laid out in randomized block design (RBD) with eight treatments and three replications. Pod and grain damage were assessed and C:B ratio was calculated. Result: First appearance of pod fly was noticed in third standard week. Throughout cropping period highest pod damage was recorded in eighth standard week and lowest pod damage was recorded in twelfth standard week. Emamectin benzoate 5 SG @ 11g a.i./ha + Dimethoate 30 EC @ 300 g a.i./ha was the best treatment as it exhibited minimum pod damage and highest yield.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"10 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140745812","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}
Labhya Rani Gogoi, P. Behera, Nayanmoni Borah, Ramendra Nath Sarma
Background: Mungbean is one important short duration pulse mostly grown in South and Southeast Asia. The level of variability available in the germplasm influences how well a breeding programme would be productive. Understanding the nature and extent of genetic diversity in breeding material is greatly helped by estimates of genetic variability parameters and character associations. The current study aimed to study genetic variability and character associations in mungbean for yield and its attributes, pre-requisite for formulating an effective breeding programme. Methods: The present experiments were carried out with 107 mungbean genotypes collected from NBPGR (New Delhi) and AAU-Zonal research station, Shillongani. The genotypes were evaluated in randomized complete block design over two replications for yield and yield attributing traits at the experimental farm Assam Agricultural University, Jorhat during 2020-2021. Result: The traits like yield per plant, number of branches per plant, clusters per plant, pods per plant, plant height, 100 seeds weight and peduncle length exhibited a high to medium magnitude of genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV). Additionally, these traits showed high heritability and high genetic advance. The correlation studies revealed significant positive relationships between yield and all the assessed traits, with the exception of shelling percentage. The results of the path analysis indicated that a few traits, such as the number of pods per plant and the weight of 100 seeds, had a significant positive impact on seed yield. This suggests that when selecting for seed yield in mungbean, it would be advantageous to take into account these traits.
{"title":"Genetic Variability and Correlation Studies for Yield and Yield Attributing Traits in Mungbean [Vigna radiata (L.) Wilczek]","authors":"Labhya Rani Gogoi, P. Behera, Nayanmoni Borah, Ramendra Nath Sarma","doi":"10.18805/lr-5241","DOIUrl":"https://doi.org/10.18805/lr-5241","url":null,"abstract":"Background: Mungbean is one important short duration pulse mostly grown in South and Southeast Asia. The level of variability available in the germplasm influences how well a breeding programme would be productive. Understanding the nature and extent of genetic diversity in breeding material is greatly helped by estimates of genetic variability parameters and character associations. The current study aimed to study genetic variability and character associations in mungbean for yield and its attributes, pre-requisite for formulating an effective breeding programme. Methods: The present experiments were carried out with 107 mungbean genotypes collected from NBPGR (New Delhi) and AAU-Zonal research station, Shillongani. The genotypes were evaluated in randomized complete block design over two replications for yield and yield attributing traits at the experimental farm Assam Agricultural University, Jorhat during 2020-2021. Result: The traits like yield per plant, number of branches per plant, clusters per plant, pods per plant, plant height, 100 seeds weight and peduncle length exhibited a high to medium magnitude of genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV). Additionally, these traits showed high heritability and high genetic advance. The correlation studies revealed significant positive relationships between yield and all the assessed traits, with the exception of shelling percentage. The results of the path analysis indicated that a few traits, such as the number of pods per plant and the weight of 100 seeds, had a significant positive impact on seed yield. This suggests that when selecting for seed yield in mungbean, it would be advantageous to take into account these traits.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"15 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140745829","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}
M.T. Gandhi, Manish Sharma, M. P. Patel, N. V. Soni, G.S. Dave
Background: Rajmash (Phaseolus vulgaris L.) is a significant leguminous crop known for its high protein content and dietary value. As global demand for nutritious food sources rises, enhancing the productivity and nutritional quality of Rajmash has become imperative. This research paper aims to investigate the combining ability and character associations in rajmash to facilitate the development of improved varieties with superior agronomic traits. Methods: An experiment was carried out in Rajmash using line × tester mating design to estimate the gca effect of parents and sca effect of 21 hybrids for yield and its traits using 7 lines and 3 testers. Hybrids along with ten parents were studied for combining ability and phenotypic correlations for seed yield and nine yield related traits. Result: The result indicated that the general combining ability (GCA) and specific combining ability (SCA) were significant for most characters indicating the importance of both additive and non-additive genetic components. This implies that a comprehensive understanding of both types of genetic effects is crucial for effective breeding programs. Among parent TRCR 3, SKAU-R-19, RR-21-01 and RKR 1033 were found to be good general combiners for seed yield per plant. This indicates their potential to consistently impart favorable traits to their progeny. The identification of such strong general combiners is valuable information for breeders aiming to enhance overall seed yield. The most promising specific combiners for seed yield were from crosses including SKAU-R-19 × RKR 1033, IPR-205-19 × HUR, RR-21-01 × RKR 1033, RR-21-12 × GR 1 and RR-21-01 × HUR. Significant desirable phenotypic correlations were observed between seed yield with days to flowering, days maturity, number of pods per plant, pod length and 100 seed weight these characters can act as indirect selection criteria in yield that could be used in rajmash breeding programs. The identification of strong general combiners, promising specific crosses and meaningful phenotypic correlations offers practical guidance for future breeding efforts, contributing to the development of improved varieties with enhanced yield potential and desirable agronomic traits.
{"title":"Combining Ability Analysis and Association of Yield and Yield Components among Selected Rajmash (Phaseolus vulgaris L.) Lines","authors":"M.T. Gandhi, Manish Sharma, M. P. Patel, N. V. Soni, G.S. Dave","doi":"10.18805/lr-5254","DOIUrl":"https://doi.org/10.18805/lr-5254","url":null,"abstract":"Background: Rajmash (Phaseolus vulgaris L.) is a significant leguminous crop known for its high protein content and dietary value. As global demand for nutritious food sources rises, enhancing the productivity and nutritional quality of Rajmash has become imperative. This research paper aims to investigate the combining ability and character associations in rajmash to facilitate the development of improved varieties with superior agronomic traits. Methods: An experiment was carried out in Rajmash using line × tester mating design to estimate the gca effect of parents and sca effect of 21 hybrids for yield and its traits using 7 lines and 3 testers. Hybrids along with ten parents were studied for combining ability and phenotypic correlations for seed yield and nine yield related traits. Result: The result indicated that the general combining ability (GCA) and specific combining ability (SCA) were significant for most characters indicating the importance of both additive and non-additive genetic components. This implies that a comprehensive understanding of both types of genetic effects is crucial for effective breeding programs. Among parent TRCR 3, SKAU-R-19, RR-21-01 and RKR 1033 were found to be good general combiners for seed yield per plant. This indicates their potential to consistently impart favorable traits to their progeny. The identification of such strong general combiners is valuable information for breeders aiming to enhance overall seed yield. The most promising specific combiners for seed yield were from crosses including SKAU-R-19 × RKR 1033, IPR-205-19 × HUR, RR-21-01 × RKR 1033, RR-21-12 × GR 1 and RR-21-01 × HUR. Significant desirable phenotypic correlations were observed between seed yield with days to flowering, days maturity, number of pods per plant, pod length and 100 seed weight these characters can act as indirect selection criteria in yield that could be used in rajmash breeding programs. The identification of strong general combiners, promising specific crosses and meaningful phenotypic correlations offers practical guidance for future breeding efforts, contributing to the development of improved varieties with enhanced yield potential and desirable agronomic traits.\u0000","PeriodicalId":503097,"journal":{"name":"LEGUME RESEARCH - AN INTERNATIONAL JOURNAL","volume":"79 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140755402","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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