Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 73
 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]
Code Context


        trigger_error($message, E_USER_DEPRECATED);

    }
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 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.'
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deprecationWarning - CORE/src/Core/functions.php, line 311
Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421
App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 73
Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610
Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120
Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94
Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51
Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98

Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 74
 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]
Code Context


        trigger_error($message, E_USER_DEPRECATED);

    }
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 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.'
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deprecationWarning - CORE/src/Core/functions.php, line 311
Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421
App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 74
Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610
Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120
Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94
Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96
Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51
Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98

Warning (512): Unable to emit headers. Headers sent in file=/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php line=853 [CORE/src/Http/ResponseEmitter.php, line 48]
Code Context
            if (Configure::read('debug')) {

                trigger_error($message, E_USER_WARNING);

            } else {
$response = object(Cake\Http\Response) {

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-The Indian Express&lt;br /&gt;
&lt;em&gt;&lt;br /&gt;
The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.&lt;br /&gt;
&lt;br /&gt;
In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.&lt;br /&gt;
&lt;br /&gt;
Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&amp;rsquo;s 2011 project for crops and pest surveillance), etc.&lt;br /&gt;
&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/&quot;&gt;click here&lt;/a&gt; to read more.
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The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. &lt;br /&gt;
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Please &lt;a href=&quot;https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/&quot;&gt;click here&lt;/a&gt; to read more.
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The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. 

Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from..."/>
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                <div align="justify">-The Indian Express<br /><em><br />The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. <br /></em><br />Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.<br /><br />In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.<br /><br />Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&rsquo;s 2011 project for crops and pest surveillance), etc.<br /><br />Please <a href="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/" title="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/">click here</a> to read more.</div>               </font>
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&lt;em&gt;&lt;br /&gt;
The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.&lt;br /&gt;
&lt;br /&gt;
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                <strong>Satellite imagery, artificial intelligence to improve farm yields in Maharashtra -Kavitha Iyer</strong></h1>
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                <div align="justify">-The Indian Express<br /><em><br />The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. <br /></em><br />Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.<br /><br />In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.<br /><br />Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&rsquo;s 2011 project for crops and pest surveillance), etc.<br /><br />Please <a href="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/" title="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/">click here</a> to read more.</div>               </font>
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The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. &lt;br /&gt;
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-The Indian Express

The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. 

Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from..."/>
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                <strong>Satellite imagery, artificial intelligence to improve farm yields in Maharashtra -Kavitha Iyer</strong></h1>
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                <div align="justify">-The Indian Express<br /><em><br />The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. <br /></em><br />Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.<br /><br />In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.<br /><br />Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&rsquo;s 2011 project for crops and pest surveillance), etc.<br /><br />Please <a href="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/" title="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/">click here</a> to read more.</div>               </font>
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-The Indian Express<br />
<em><br />
The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. <br />
</em><br />
Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.<br />
<br />
In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.<br />
<br />
Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&rsquo;s 2011 project for crops and pest surveillance), etc.<br />
<br />
Please <a href="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/">click here</a> to read more.
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-The Indian Express<br />
<em><br />
The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. <br />
</em><br />
Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest.<br />
<br />
In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers.<br />
<br />
Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department&rsquo;s 2011 project for crops and pest surveillance), etc.<br />
<br />
Please <a href="https://indianexpress.com/article/india/satellite-imagery-artificial-intelligence-to-improve-farm-yields-in-maharashtra-6056933/">click here</a> to read more.
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Satellite imagery, artificial intelligence to improve farm yields in Maharashtra -Kavitha Iyer

-The Indian Express The Maha Agri Tech project attempts to mitigate agricultural risks by using data anlytics to plug gaps. Launched in January this year, the Maha Agri Tech project seeks to use technology to address various cultivation risks ranging from poor rains to pest attacks, accurately predict crop-wise and area-wise yield and eventually to use this data to inform policy decisions including pricing, warehousing and crop insurance. When farmers in six districts of Maharashtra begin sowing for the coming rabi season, this project will enter its second phase where artificial intelligence and satellite imagery will be used to mitigate risks. Fields of the farmers that are part of the project will be monitored via satellite images at every stage right until the harvest. In its first phase the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to assess the acreage and the conditions of select crops in select talukas. In its second phase, various data sets from diverse data providers will be combined to build yield modelling and a geospatial database of soil nutrients, rainfall, moisture stress and other parameters to facilitate location-specific advisories to farmers. Already, officials said, satellite imagery helped analyse the extent of crop destruction in parts of western Maharashtra after the floods this August. Once indicative crop yield prediction and accurate analysis of highly localised soil health/moisture conditions is possible using satellite imagery combined with artificial intelligence, policy decisions and advisories ranging from crop suitability, inventory, crop damage assessment and early season crop forecasts can be based on these. Working on the coming rabi season simultaneously are the MRSAC and the NRSC that have expertise in analysis of satellite imagery, as well as other agencies providing diverse kinds of data, such as Mahavedh (decentralised rainfall data from over 2,000 automated weather stations), Groundwater Survey Development Agency, CROPSAP (the agriculture department’s 2011 project for crops and pest surveillance), etc. Please click here to read more.