New tools for science on the farm –


The value of “connected agriculture” in making life easier for farmers, and helping them reduce the environmental impact of their practices, is no longer unproven. Another of its advantages is beginning to emerge: by producing large amounts of data of near- research quality, it helps align agronomic and zootechnical research closer to farmers’ requirements, and could better inform agricultural public policies.Digital agriculture is a concept which is beginning to reach grass-roots level, as the high visibility of the subject at the Paris Agriculture Fair demonstrated. In the gloomy atmosphere generated by the feeling of “agri-bashing” experienced by many farmers, it was one of the few subjects that gave a positive and attractive picture of recent developments in agriculture.

Digital farming tools were first designed to make life easier for farmers (GPS guidance, herd monitoring sensors), and to help them optimise their farming practices on an environmental level (connected weather stations, crop models used to optimise input usage). They have also strengthened ties with the consumer, who, thanks to the development of traceability and social networks, can now put a face and a name to the food he buys.

More behind the scenes, connected agriculture is also beginning to have a new beneficial effect, which could in future play an even more positive role for the agricultural world: bringing farmers closer to the research world… and as a result to the policy makers who make use of it.

When science has to be done at the farm level

This development is already a reality in some areas of R & D in digital agriculture. To take the example of herd monitoring sensors: they were first developed to detect unusual and clearly identified events, such as detecting temperatures or calving. These initial applications were developed in a conventional research setting, top down from the lab to the field: algorithms for event detection were developed in tests in experimental farms at research or technical institutes, then tested on a small range of farms before being launched commercially.

As these initial applications have reached maturity, research is now focused on analyses of the daily behaviour and welfare of animals: for example, measuring time spent standing or lying, feeding and rumination times. In these areas it is important to detect more subtle changes in the “daily life” of animals, compared to their ordinary activity.

That makes it very difficult to develop this type of algorithm on experimental farms, where the usual activities of livestock (milking, being put out to pasture, etc.) are frequently disturbed by experiments that modify their usual behaviour, and generate movements or immobility that would not happen in a commercial farm. This type of work should therefore be carried out directly in the field, with experiments in controlled conditions being used only as spot checks in a minority of situations. This is an example of an inversion of the classic relationship between scientific experimentation and field data.

From the lab to the vineyard… and back!

Another example of linking research to farmers’ concerns is the use of mechanistic crop models in decision support tools. These models, derived from agronomic research, are increasingly being used for yield forecasting and management of the required inputs (irrigation, fertilisation). Similar epidemiological models are also used to predict the occurrence of diseases or pests threatening crops, in order to position pesticide treatments most accurately.

By design, the result of extensive research in ecophysiology, these models are sufficiently robust and predictive to lend themselves to plausible simulations on the potential effect of changing practices for agro-ecological reasons, or to adapt to climate change. They also have the advantage of objectively quantifying the environmental conditions to which crops are exposed.

Evapotranspiration is a classic example of a simple indicator for measuring crop water demand, which can then be used as a benchmark to check whether irrigation by the farmer has avoided water waste. However, it remains a relatively basic indicator, which is relevant only in the simplest cases: those where we are only seeking to maintain the yield potential by avoiding water deficit for the crop. For some produce, irrigation issues are more complex, because a small, well-controlled water deficit improves the quality of production: the best known case being vines, where the ideal method, defined by the specifications of the wine appellation, aims to create a moderate water deficit during the maturation of the grape, with varying degrees of severity depending on the type of wine you want to produce.

In this case, irrigation management requires much more complex models than a simple evapotranspiration calculation, and they will use not only climate data, but also soil characteristics and the volume of vegetation in the vineyard. At first glance this is once again a top-down approach to the maximisation of research value, from the laboratory to the field. But the use of these models on farms then permits valuable feedback, which will bring the theoretical work closer to the practice of farmers or their consultants.

The Vintel software, developed by iTK in partnership with (among others) INRA and CIRAD, offers a good example of these two-way exchanges between lab and field. Designed to optimise precision irrigation on vines, it is based on a model derived from research work, based on a classic indicator in research of conventional water stress, the basic leaf water potential.

This indicator is the most reliable for measuring the moisture condition of a vine plant, but its measurement is fiddly, which limits its use in vineyards: it has to be measured at dawn with a specific instrument, the pressure chamber. Some wine consultants, particularly in California, use pressure chambers to advise winegrowers. However, they use these measures at noon for convenience, but also to better understand the water deficit of the plot at the time of the day when it is at its height.

This way of measuring is much less common in research, and so originally it was impossible to develop a mechanistic model to simulate it. Vintel was initially released with a model which only estimated the basic leaf water potential. A few years of use of this first version, by consultants expert in the use of the midday potential measurement, then allowed the development of a second model for midday leaf water potential, combining meteorological data and indicators from the base potential, without going through the laboratory process again.

This example clearly demonstrates the new complementarity between research and digital tools for farmers: it is obviously the data from the field that made it possible to develop a model of midday leaf water potential, in line with the habits of winegrower technicians. But that alone would not have been enough to develop a reliable statistical model: only combining them with indicators from a mechanistic model derived from research could lead to the development of a model robust enough to be entrusted to winegrowers and consultants.

“Medium Data” vs Big Data

A few years ago, the explosion of Big Data technologies, and their introduction into the agricultural world, gave rise to a rather binary view split between two scientific approaches:

  • On the one hand, the classic approach of agronomic or zootechnical research, relying on high-quality but relatively sparse experiments, to develop predictive models that can be used in decision support, based on the human expertise of researchers,
  • On the other hand, the new data-centred Big Data approaches applying machine learning techniques (machine learning, deep learning) to massive volumes of data from new sensors deployed in agriculture (combine yield sensors, data collected by milking robots),

The enthusiasm for Big Data was based on the assumption that deep learning would allow the development of reliable predictive models, despite the “noise” generated by the information from the masses of data collected, which exceed what human expertise is capable of analysing. In fact, this hope quickly came up against the major pitfall of machine learning techniques: their lack of user-friendliness…both for end users (farmers or breeders), and service designers! Machine learning certainly now makes it possible to define seemingly satisfactory decision rules or models from any sufficiently large dataset.

But without knowing the “reasoning” underlying these models, even their designers are unable to predict to what extent these rules or models can be used in new contexts: a rather distressing uncertainty when developing new agricultural services beyond the region where they were initially proven, or in new climate situations.

In addition to its sensitivity to unpredictable climate risks, agriculture has another unfortunate feature for machine learning: the real data that can be accumulated on the ground is far from covering all possible combinations of cultivation techniques. The technical strategies used by farmers are influenced by their habits, experience and the expertise of their consultants, and are therefore absolutely implicitly limited by human rationales.  The situation is in this regard completely different from areas such as machine learning applied to games such as chess or go: in the latter case, the algorithm is able, based on the rules of the game, to test all possible and imaginable combinations, even those that a human expert would not think of. In agriculture, artificial intelligence is hampered by the fact that the available data is the result of human reasoning, which prevents it from finding original “solutions” to invent new practices.

The result of these constraints is that purely data-driven approaches are struggling to make a decisive breakthrough in agricultural decision support. The future is undoubtedly, as we have seen from Vintel’s example, the combination of data-driven approaches and mechanistic models to integrate human expertise into Artificial Intelligence. This new vision, hybrid AI, has been chosen as one of the major themes of ANITI, the new Institute of Artificial Intelligence currently being created in Toulouse… and agriculture has been identified as one of its priority areas of application.

This close interconnection between scientific expertise and farm data has an obvious corollary: the need to bridge the gap between Big Data and research data. This is the mission of what can be called “Medium Data”: well-founded data from farms, or at least from plots run under conditions similar to those of farms. Until now, this role of producing intermediate data has been entirely devolved to experiments at agricultural development agencies: technical institutes, chambers of agriculture, cooperatives[4]. Digital agriculture will allow for the emergence of a new category of “medium data”: data of near-research quality, but spread across hundreds or thousands of farms.

Between the scientific data of research, high quality but sparse, and the “Big Data” of sensors embedded on agricultural equipment, connected agriculture allows the emergence of a “Medium Data”: data of near-research quality, acquired on farms, and not small, unrepresentative experimental plots. It is this continuum of data that will fuel hybrid artificial intelligence (a combination of machine learning and mechanistic human expertise), one of the most promising avenues in today’s AI.


Information to ground agricultural public policy

We have seen, with the example of irrigation, that agricultural decision support tools lend themselves well to the creation of objective indicators of crop needs: the same approach is easily transferable to fertilisation, as well as crop protection. Epidemiological models, already used to advise optimal treatment dates for diseases and pests, could also be used at plot level to quantify the still vague and subjective idea of “threat of disease”  Such indicators would be valuable in improving the monitoring of Ecophyto, the plan to reduce the use of pesticides launched in 2010 following the “Grenelle de l’Environnement” debate.

It’s not overstating the case to say that, almost 10 years after its inception, the plan is far from the 50% reduction target (“if possible”) assigned to it: pesticide consumption shows no significant changes on the national average. Even more disturbing, even the plan’s flagship farms, the Dephy network, are a long way from achieving the expected goal. In view of what can hardly be described other than as a failure, the Académie d’Agriculture de France has recently made recommendations to improve the management of the Ecophyto Plan, including the creation of this kind of indicator of health pressure on crops. Digital agriculture could also play a major role in another of the Academy’s proposals: annual surveys of agricultural practices, the only references that can be used to calculate farmers’ pesticide consumption in any detail.

Indeed, the current indicator for the Ecophyto Plan, NODU, is not suited to an agronomic interpretation, which would allow calculation of the potential reduction in pesticide use at farm level. Another indicator, the TFI, would allow for this calculation, although it is currently calculated only every three years, due to the cost of the surveys currently required to collect the data. This still remains the situation, but plot management software enables the automatic calculation of this indicator for farmers who have the equipment. A representative network of farms equipped with this software would therefore allow the annual TFIs to be calculated at a lower cost and cross-linked with the health pressure indicators mentioned above. It should thus be possible to follow up the Ecophyto plan with greater accuracy… and probably to redefine a more realistic set of goals for it, differentiated by crop and region!

Participatory science, which draws on the knowledge of its future users and civil society stakeholders, is one of the key trends in current research. INRA has also been heavily involved in this area. However, much participatory science work remains very asymmetrical: researchers are often the only players putting forward the theories based on the informal and unorganised knowledge of the stakeholders involved in the project. Connected agriculture offers a unique opportunity for farmers to take ownership of research topics that affect them, producing data for themselves which is as understandable for them as for the researchers who will make use of it. Beyond its impact on the daily work of farmers, it therefore has great potential to bring research closer to their needs and enable politicians to better understand their practices. This is how agriculture will be able to meet society’s many expectations of it.


Benefits and Drawbacks of AI Agriculture Sustainability to the Economy. –


This research paper examines the profound impact of Artificial Intelligence (AI) on the agricultural sector and its benefits and drawbacks on our economy.It explores primarily the pros and cons to the countries economy and additionally various applications, benefits, and challenges of AI technologies in agriculture,discusses their potential to revolutionize farming practices for sustainability.

Agriculture is the primary source of food production globally. Ensuring a stable and sufficient food supply is essential for the well-being of the world’s growing population. Sustainable agriculture practices help meet this demand while minimizing negative impacts on the environment. Agriculture is also a significant driver of economic growth in many countries. It provides employment opportunities for millions of people, especially in developing nations so its sustainability is necessary. Agriculture is often the backbone of rural economies. Sustainable agriculture can stimulate rural development by providing income opportunities, improving infrastructure, and enhancing the overall quality of life in rural areas. Agriculture is a significant user of freshwater resources. Sustainable practices, such as efficient irrigation methods and soil management, can reduce water wastage and contamination.

A significant portion of the global food supply is lost or wasted, from farm to plate. Sustainable agriculture can contribute to reducing food waste.

Artificial Intelligence (AI) plays a significant role in addressing agricultural challenges by enhancing efficiency, productivity, and sustainability across various aspects of farming and food production. Such as AI-driven technologies, for example satellite imagery, drones, and sensors, enable farmers to gather real-time data about their fields. Machine learning algorithms process this data to provide insights into crop health, soil conditions, and irrigation needs. This allows for precise resource management, reducing waste and optimizing crop yields.AI can analyze images of crops to identify diseases, pests, and nutrient deficiencies early in the growing season hence helping farmers detect targeted actions to be taken.AI models can analyze historical weather data, crop performance, and market trends to make predictions about future conditions. Farmers can use these insights to make informed decisions about planting times, crop selection, and marketing strategies, reducing risks and maximizing profits.AI-powered autonomous tractors and harvesters can perform tasks like planting, harvesting, and weeding with precision and efficiency. This reduces labor costs, minimizes fuel consumption, and can lead to more sustainable farming practices.AI can analyze soil data to provide recommendations for soil improvement strategies, such as optimal crop rotation and nutrient management additionally AI can optimize irrigation systems by monitoring soil moisture levels and weather forecasts, allowing for precise and efficient water usage which would benefit a great deal to scarce areas.

As mentioned the main goal for this research paper is to tell the benefits and drawbacks to economy by agriculture through the assistance of Artificial Intelligence. However, AI agriculture itself is a big challenge which is going to be further discussed in this paper and we will find out if it possible to accomplish this task or not while looking for our economy as well.

The historical context of agriculture sustainability and economic challenges are a complex and evolving story that spans thousands of years. In earlier years agriculture was the foundation of many ancient civilizations, including the Sumerians, Egyptians, Greeks, and Romans. These societies developed sophisticated farming techniques, such as irrigation systems and crop rotation. However, many also faced sustainability challenges, including soil degradation and deforestation, in spite Practices like over farming and improper land management could lead to soil degradation and erosion. The resulting loss of arable land affected agricultural productivity and contributed to economic decline. Though during the the middle ages sustainable practices, like crop rotation and fallow fields, were developed to manage land use more effectively.

Furthermore, the Industrial Revolution in 18th century brought mechanization and technological advances to agriculture, however, the shift from traditional farming methods to more mechanized and industrialized agriculture led to significant rural-to-urban migration. While this contributed to the growth of urban economies, it often left rural areas economically depressed and resulted in the displacement of rural communities. These issues carried out throughout the years affecting the economies and the sustainability of the agriculture kept decreasing as newer innovations came such as high yield crops, modern farming practices etc.

Then there were new challenges such as climate change and a sudden increase in population for example the Great Depression, in the agricultural sector in the United States faced severe economic challenges. Falling agricultural prices, coupled with drought and the Dust Bowl phenomenon, led to widespread farm bankruptcies and rural economic hardships. Additionally, soil erosion, nutrient depletion, and degradation threaten the long-term productivity of agricultural land and these unsustainable agricultural practices which have contributed to land degradation and desertification in some regions. This can render previously arable land unusable and lead to economic hardships for affected communities. A significant portion of the food produced is lost or wasted, hence which leads to more economic issues. Lastly, Excessive use of pesticides and synthetic fertilizers can harm the environment, human health additionally the use of pesticides, fertilizers, and other chemicals in modern agriculture has led to environmental problems like chemical runoff into water bodies, which can harm ecosystems and lead to economic costs related to environmental remediation and health issues.

Due to these issues governments, international organizations and consumers were in quest to find solutions to these hurdles, therefore, Artificial Intelligence agriculture was introduced due to its efficiency and it provides aid for the economy as well. For instance some places where AI aids agriculture is: Machine learning algorithms analyze large datasets to make predictions about crop yields, disease outbreaks, weather forecast patterns, and optimal planting times. This helps farmers make data-driven decisions for crop management, resource allocation, furthermore, enables farmers to make more informed decisions about planting, harvesting, and marketing their products, potentially increasing profitability.AI-powered robots and autonomous vehicles can also perform tasks like planting, harvesting, and weeding. These technologies reduce the need for manual labor, increase efficiency, and can operate 24/7, improving overall farm productivity. While this may lead to some job displacement, it can also free up labor for more skilled and higher-paying roles, potentially balancing out the economic impact. Another major leverage offered by Artificial Intelligence is precision agriculture in which sensors, GPS technology, and AI algorithms enable precise planting, irrigation, and fertilization based on real-time data, leading to reduced waste and environmental impact. This increased productivity can boost agricultural output and contribute positively to the economy by increasing food availability and reducing prices. Moreover, AI helps farmers monitor soil conditions, moisture levels, and nutrient content for instance: Internet of Things (IoT) devices equipped with sensors are deployed in the field to monitor environmental conditions, plant growth, and livestock health which enhance resilience to climate-related challenges and reduce economic losses due to extreme weather events. Furthermore Artificial Intelligence can identify early signs of crop diseases and pest infestations through image analysis and sensor data, decreasing its impact to the economy as low as possible, in addition to this allows for timely interventions, reducing crop losses and the need for chemical treatments. The adoption of AI technologies in agriculture can stimulate economic growth in rural areas by creating job opportunities in technology development, maintenance, and support services, similarly also benefitting small-scale and remote farmers in improved market access by providing real-time market information and facilitating direct connections with buyers. This can result in higher incomes for farmers and boost the overall rural economy. Lastly, by increasing agricultural productivity and reducing food waste through better crop management, AI can contribute to global food security. Stable food supplies can help stabilize prices and reduce economic volatility related to food shortages.Frontiers | Towards making the fields talks: A real-time cloud enabled IoT  crop management platform for smart agriculture

Some examples or AI technologies being used are as follows: Robotics and Autonomous Systems (RAS) are introduced in large sectors of the economy with relatively low productivity such as Agri-Food. According to UK-RAS White papers (2018) the UK Agri-Food chain, from primary farming through to retail, generates over £108bn p.a., and with 3.7 m employees in a truly international industry yielding £20bn of exports in 2016. Robotics has played a substantial role in the agricultural production and management. Kumar (2014) discusses about the different irrigation methods with the primary motive of developing a system with reduced resource usage and increased efficiency. Devices like fertility meter and PH meter are set up on the field to determine the fertility of the soil by detecting the percentage of the primary ingredients of the soil like potassium, phosphorous, nitrogen. The M2M that is, Machine to Machine technology is been developed to ease the communication and data sharing among each other and to the server or the cloud through the main network between all the nodes of the agricultural field (Shekhar et al., 2017). They (2017) developed an automated robotic model for the detection of the moisture content and temperature of the Arduino and Raspberry. The data is sensed at regular intervals and is sent to the microcontroller of Arduino, it further converts the input analog to digital. The signal is sent to the Raspberry and it sends the signal to Arduino to start the water source for irrigation. The water will be supplied by the resource according to the requirement Lie Tang et al. (2000) brought up a vision based weed detection technology in natural lighting. It was created utilizing hereditary calculation distinguishing a locale in Hue-Saturation-Intensity (HSI) shading space (GAHSI) for open air field weed detecting. Unmanned aeronautical vehicles (UAVs) can be remotely controlled (Mogli and Deepak, 2018). They work in confluence with the GPS and others sensors mounted on them. Drones are being implemented in agriculture for crop health monitoring, irrigation equipment monitoring, weed identification, herd and wildlife monitoring, crop spraying and disaster management (Veroustraete, 2015; Ahirwar et al., 2019; Natu and Kulkarni, 2016). 

As a result of all these developments there are countless of benefits to the economy and the agriculture but it also has some drawbacks which should be taken into consideration.First and foremost ss automation and AI technologies are integrated into agriculture, there is the potential for job displacement among farm workers. This can lead to unemployment or underemployment in rural areas, impacting local economies.Implementing AI technologies can be expensive, especially for small-scale farmers. The high upfront costs of AI systems and the need for training can be a barrier to adoption, potentially exacerbating economic disparities. Overreliance on AI and technology can make the agricultural sector vulnerable to disruptions caused by technical failures, cyberattacks, or changes in technology trends. This dependency can pose economic risks. Farmers need training to effectively use AI tools, and there may be resistance or reluctance to adopt new technologies and a shortage of skilled labor in rural areas can hinder the adoption of AI and automation, limiting the economic benefits. Collecting and sharing data for AI applications raises concerns about data privacy and security, as sensitive information about farming practices is involved leading to have economic repercussions and damage trust within the industry. In summary, AI in agriculture offers significant outcomes and benefits, such as increased yields, resource efficiency, and sustainability. However, challenges related to data, infrastructure, affordability, and ethical considerations must be addressed too. Many agricultural regions lack adequate internet connectivity and technology infrastructure, hindering the widespread adoption of AI solutions hence providing this infrastructure can lead to a big dent in the economy.

In conclusion, the marriage of agriculture and artificial intelligence holds the promise of a more sustainable and resilient future for our food production systems and our economy. Through my extensive research paper, we have explored innovative ways to optimize resource utilization, mitigate environmental impacts, increase agricultural productivity and most importantly enhance our economy. Moreover, the evolving nature of climate change and global food demands necessitate adaptive strategies that utilizes our economy efficiently. In summary, the economic impact of AI in agriculture is multifaceted, with both positive and negative aspects. Maximizing the benefits while mitigating the drawbacks requires a holistic approach that considers technological, economic, social, and regulatory factors. Policymakers, farmers, and technology providers should collaborate to ensure that AI enhances agricultural sustainability and contributes positively to the economy

In closing, my research underscores the profound impact that AI can have in building a more sustainable and resilient agricultural sector, while also yielding the best economic results. It is my hope that this study serves as a catalyst for further exploration and innovation in the field of agriculture sustainability through AI, ultimately paving the way for an improved economy, simultaneously accommodating a brighter and more food-secure future for all.

Abdullah Anwar


Crop-boosting AI can benefit many fields »


A team from the University of Illinois has stacked together six high-powered algorithms to help researchers make more precise predictions from hyperspectral data to identify high-yielding crop traits. Credit: RIPE project.

Machine learning algorithms developed to select high-yield food crops could be applied to ‘hyperspectral analysis’ in other disciplines, from astronomy to espionage

— by University of Illinois at Urbana-Champaign

To help researchers better predict high-yielding crop traits, a team from the University of Illinois have stacked together six high-powered, machine learning algorithms that are used to interpret hyperspectral data. They demonstrated that this technique improved the predictive power of a recent study by up to 15 percent, compared to using just one algorithm.

Hyperspectral data comprises maps of the full light spectrum — not just the visible wavelengths — and has many other applications, from understanding the health of the Great Barrier Reef to tracking the rate of loss of the Amazon rainforest.

“We are empowering scientists from many fields, who are not necessarily experts in computational analysis, to translate their enormous datasets into beneficial results,” said first author Peng Fu, a postdoctoral researcher at Illinois, who led this work for a research project called Realizing Increased Photosynthetic Efficiency (RIPE). “Now scientists do not need to scratch their heads to figure out which machine learning algorithms to use; they can apply six or more algorithms–for the price of one–to make more accurate predictions.”


RIPE for the picking of high-yield crops

RIPE, which is led by Illinois, is engineering crops to be more productive by improving photosynthesis, the natural process all plants use to convert sunlight into energy and yields. RIPE is supported by the Bill & Melinda Gates Foundation, the U.S. Foundation for Food and Agriculture Research (FFAR), and the U.K. Government’s Department for International Development (DFID).

In a recent study the team introduced spectral analysis as a means to quickly identify photosynthetic improvements that could increase yields. In this new study, published in Frontiers in Plant Science, the team improved their previous predictions of photosynthetic capacity by as much as 15 percent using machine learning, where computers automatically applied these six algorithms to their dataset without human help.

“I’ve loved seeing what’s possible when you can use computational power to exploit the data for all its worth,” said co-author Katherine Meacham-Hensold, a RIPE postdoctoral researcher at Illinois, who led the previous study in Remote Sensing of Environment. “It’s exciting to see what a data analyst like Peng can do with my data. Now other non-data-analyst scientists can test several powerful algorithms to figure out which one will help them leverage their data to the fullest extent.”

Stacks of applications

Further studies will prove the relevance of this stacked algorithm technique to the plant science community and other fields of study.

“By applying the expertise of data analysts to address the needs of plant physiologists like myself, we ended up refining a technique that is relevant to other hyperspectral datasets,” said co-author Carl Bernacchi, a RIPE research leader and scientist with the U.S. Department of Agriculture, who is based at Illinois’ Carl R. Woese Institute for Genomic Biology. “The next step is to test more stacked machine learning algorithms on datasets from many more crop species and explore the utility of this technique to estimate other parameters, such as abiotic stresses from drought or disease.”

“As scientists, we should try to use our domain knowledge to explain advanced performance from machine learning methods,” said co-author Kaiyu Guan, an assistant professor in Illinois’ College of Agriculture, Consumer, and Environmental Sciences (ACES). “Combining computational methods and domain disciplines allows us to possibly unravel what causes the measurable differences in hyperspectral datasets–which is an unsolved mystery in our work and worth future exploration.”

Original article: Hyperspectral Leaf Reflectance as Proxy for Photosynthetic Capacities: An Ensemble Approach Based on Multiple Machine Learning Algorithms


Trends That Will Transform The Agriculture And Farming Industry Outlook In 2020 »


The agriculture industry influences many sectors of the economy locally as well as internationally. From farmers and real estate to supermarkets and restaurants, it’s important to understand what is going on in this industry and how it will affect the production and distribution of food. These agricultural trends that are being seen this year are likely to set the stage for many years going forward and beyond. Issues like new vaccinations, the use of global water resources and new technological ability to monitor crops even further will continue to play a role in the United States and in agricultural procedures in the rest of the world.

Animal Vaccines

Vaccines are an incredible human accomplishment. In the new year, vaccines continue to be applied to many areas of agriculture. Efforts being made to help provide even more access to animal vaccines. In the United States, officials are concerned about the spread of certain vaccine preventable illnesses in livestock. As a result they are trying to set up a bank to combat FMD disease. They are concerned there are only about 1.75 million doses on hand. Officials hope to have the desired twenty-five million doses on hand via the use of a vaccine bank.

Attracting New People

Another issue that remains at the forefront of efforts to make agriculture continue to pay off is attracting new people to the farming world. Many graduates who enter farming programs face a great deal of debt once they are done with their studies. In the meantime, the average age of current farmers is about sixty. Farmers want to work closely with young people to the mutual benefit of both parties and think about their own retirement. Helping young people discover how rewarding agriculture can be is essential. Officials are working to help them reduce their debt and find a place for themselves in this all important world.

Increased Income For Small Farmers

Large farm operations constitute less than half of all farms in the United States. Yet these farms is expected to continue to rise. Experts who watch the farm industry closely anticipate such farms will experience growth and income of about 9.3 percent when compared to the previous year. Small farms are those that help power the rest of the industry and bring much desired food to many parts of the United States and the rest of the world. This increased income should help such farmers pay their bills as well as providing additional capital to invest in new equipment.

Crop Monitoring and Other Technologies

Just as technology has transformed many areas of the economy, it will continue to have an impact on the world of farming. According to officials at the FCC, over twenty-four million Americans lack access to the world of broadband internet. Farmers are increasingly rising to the challenge and discovering new ways to put their use of broadband and other forms of technology to work for them. A farmer can now use many types of apps to monitor crops each day. Less expensive drones deliver things where and when they are needed.

Agricultural drones are easier to fly and easier to understand the data they provide. These are also drones that can respond well even in the event of changing weather conditions. Extremely localized weather data is also being offered. Now farmers can have even more detailed predictions about the state of the local weather in their area. This helps them determine what should be planted in any given timeframe as well as if crops should be harvested if weather conditions are about to change in their area.

Lightweight graphene is also being used to provide even more data about field and soil conditions in any given area. This kind of “plant tattoo” can help scientists and farmers work together to decide how best to use use soils as well as breed up better plants with higher yields and more ability to survive even under less than ideal conditions.

Focus on Tariffs

A tariff is essentially a tax on goods and services that are imported from one place to the next. In the United States, as in the rest of the world, there are many farmers who not only grow and share what they grow to local markets. Many farmers also sell to other parts of the world. In an effort to influence policy in other places, the American president has chosen this method to push forth certain global policies. At the same time, the president and his advisors recognize that such efforts might cause problems for farmers in the United States. This is why the president has provided a sixteen billion dollar package that is intended to help offset the worst effects of this problem. Those who observe agriculture in the United States and worldwide are watching this issue carefully. It is unclear what effects such subsidies and tariffs will have on the income of farmers. These funds should continue to have an impact on the world of agriculture this year as well as the new few years and even beyond.

Food Safety

Food safety is an area of major concern for farmers and all those involved in agriculture. Farmers need to be aware of the potential for contamination as they work in the fields and as food is transported from one place to the next. Even a minor problem such as an e coli outbreak can lead to serious costs that farmers must be prepared to absorb. Experts estimate that such costs vary by the kind of farm and the type of material being grown and produced. In general, these costs range from about a third of a percent for those growing artichokes to more than two percent of profits for farmers bringing watermelon to market. These costs may continue to grow as farmers face increased regulations in the future. It’s imperative for all those who are involved in farming to be aware of all upcoming regulations that may impact their current farming methods. Doing so can help ward off any potential problems and keep all of their produce safe from any form of contamination.

Hemp Production

The 2018 Farm Bill made it legal for farmers to produce and sell all forms of hemp. This substance can be used to create many items as well as for those who want to smoke it at home. The hemp market is one that is poised to see enormous growth in the United States. In 2017, the entire market production of in the United States was estimated at $820 million. Experts who watch this industry anticipate much further growth in this field in the coming year as a result of making it legal to grow and use hemp. Farmers can now choose to make this crop part of their overall kind of crops and set aside a specific area of the farm to bring it to market. Experts caution that any farmer who is thinking about doing so make sure they understand the ramifications of this new law and exactly what it means for all those who choose to make this crop their own.

Interaction With Clients

Direct interaction with clients is a must for all workers and business owners. The same is true for farmers. Farmers have increasingly come to understand the need to speak to their consumers directly. Using social media makes this process easier. Farmers can create a website and help people find them. For certain farmers, this process has been incredibly useful. For example, those who run farms that grow pick-your-own crops want to make sure that anyone who is going to visit them understands what kind of crops are on offer before they arrive. Studies indicate that forty percent of all farmers are on Facebook. Many others are making use of different social media such as Twitter and Instagram to connect with people locally and around the world. Social media accounts can also make it clear that farmers serve a vitally important role in the region’s economy and the life of the community. Knowing who’s growing one’s food makes people feel more connected to the land.

Corn Takes Center Stage

Corn has long been one of the most popular of all American crops. It continues to assume a major role in American agriculture. In the United States, officials at the FDA state that there should be about 89.8 million acres of corn planted in the country. This is up from 86.7 million acres in the previous year. Corn plays a major role not only in the United States. The amount of corn grown in the United States also helps to feed the rest of the world. Foreign governments and the people they serve will continue to rely on this crop from the United States in order to help them put food on the table.

Water Use

Water is the foundation of many agricultural crops in the U.S. and worldwide. Water access continues to be one of the many issues that farmers will face this coming year. Agriculture consumes eighty percent of all water use in the United States. Farmers are looking for ways to help them reduce their consumption of water for their crops. In many instances, they are choosing to harvest more water on their fields. They’re also reusing the water that they use. For example, the use of so-called dirty water can help by providing water for their animals and then get used to help water the crops when the animals are done drinking.

Article by

Linchpin Team in Chicago, Raleigh, and Wake Forest.


5 trends to watch »


As the snow flies across the upper Midwest, the forecast for 2020 is starting to become clearer. Agtech is making it easier than ever to collect and share data, and this is great news for farmers, landowners and investors. More robust data collection and improved data transparency can help ensure that American farmland is being maintained with care, as farmers work to sustain healthy soils and deliver strong yields, year after year.

From major equipment manufacturers’ forays into robotics to the emergence of new startups looking to improve farmer awareness of field activity, here’s what to watch for in the year ahead.

1: Farming as a Service will continue to grow

Farming as a Service (FaaS) is the term commonly used to refer to subscription and pay-per-use farming services. While this may sound like software engineer jargon, it really just refers to custom farming. If you’re a landowner and you need someone to perform specific services for you and manage the equipment, you’re engaging in the FaaS ecosystem. And that’s not a bad thing.

Given the degree of uncertainty around marketing and commodity rates, FaaS has been a boon to farmers and farmland owners who are looking to establish fixed costs and goals upfront. One of my favorite local FaaS companies is a startup called Sabanto that uses autonomous tractors to perform planting and other row crop operations.

Sabanto is the kind of FaaS company that’s currently working to find out what it takes to provide autonomous farm services to growers in the near year or two. New models for farmland management and technology are almost here, and FaaS leaders are gearing up to meet the needs of data-driven operations as the industry continues to make farming more efficient.

2: The rise of data transparency and analytics

The global agricultural robots market was recently valued at $4.1 billion. Major equipment manufacturers like John Deere keep rolling out new models and new machines, like its new crop-spraying drone. There’s also new software that’s changing the data game by bringing AI into the fields to improve monitoring and data collection.

But the rise of data transparency and analytics in farming goes beyond improved equipment capabilities. While agricultural tools get smarter and data delivery gets easier, it’s increasingly common for farmland owners and tenants to sign leases that require data delivery and provide deadlines for that information.

3: AgTech investment opportunities are multiplying

The landscape for farmland investors is changing alongside the rest of the modernizing agricultural industry. Startups like FarmTogether aim to help more investors get the benefits of having farmland in their investment portfolios, and they’re working to make sure more people understand the variety of ways this can be structured.

As the continued interest in agtech companies provides traditional investment opportunities, the new equity-based arrangements will continue to change the farmland investment game.

4: Landowner empowerment is on the rise

Data is power, and its rise is fueling landowner empowerment in agriculture. Having the input receipts in hand from the past five years running is invaluable, and farmland owners are beginning to understand just how valuable it can be to have a complete view of their farmland health, especially when it comes to soil health.

With increased technology and online tools, remote landowners—those do not live near their land—are getting their first glimpse of what’s going on by numbers. Transparent data sharing can help landowners and farmers align their goals, and it can help farmland owners get a more robust understanding of what’s often a landowner’s greatest asset.

Knowing your soil will need inputs next season (or a multi-year nutrient application) has a real financial impact for landowners: if a landowner knows they’ll be investing in these types of improvements in advance of signing their next cash lease, they’ll be able to set a fair price and outline who will pay for these improvements. Data delivery and literacy will have a huge impact on the bottom line for savvy farmland owners in 2020.

5: The popularity of digital leasing grows

There’s no reason today that anyone should still rent their farmland off of a handshake agreement. In the age of online accountability, new farmland rental and sales platforms help farmland owners and farmers manage their leases, records, and references digitally. 

While it may seem daunting to change standard practices in an industry that’s as old as our species, the dial is moving away from verbal agreements. The new standard is that every farmland rental agreement should include requirements around tillage, data delivery, and insurance, among other things, and digital leases make exchanging this information easier than ever before.

For farmland owners who live remotely, digital leases are an easy way to secure a rental agreement and establish a higher standard communication that can improve their relationships with their farmland tenants.

Digital agtech drives the agricultural industry forward

While farming is a very traditional space, it’s not immune to the power of technological advances. In 2020, farmland owners and farm farmers will have to find new ways to build trust and credibility within their communities to stay competitive.

To accomplish this, both groups will need to have the right tools on hand and the ability to market themselves by building an online presence to grow their reputations. The agtech industry is rising to meet these challenges in the year ahead.

Article by
Corbett Kull, co-founder and CEO of Tillable


ITC and World Bank publish new report on addressing non-tariff measures in Pakistan »


(Geneva) – A new report published by the International Trade Centre (ITC) and the World Bank Group reveals that more than half of Pakistani exporters struggle with domestic and foreign regulatory barriers.
Trade regulations in areas such as testing, certification and licensing are challenging for 60% of Pakistan’s agricultural exporters.

This is largely because most countries have stringent regulations in place to protect human health and the environment. The survey found that 47% of companies that export manufactured goods also have difficulty with these regulations. Destination countries, particularly in Asia and Europe, are responsible for most of the reported barriers. In addition, domestic rules – from export inspections and tax refunds to export certification – also create difficulties. About 45% of the measures that cause problems for Pakistani exporters originate in Pakistan.

The report’s recommendations focus on greater transparency, upgraded quality and customs infrastructure, streamlined procedures and better enforcement of quality compliance. It also recommends digital solutions, such as an integrated trade portal to give exporters the guidance and information they need to succeed.

“Pakistan has the potential to increase its exports by up to $12 billion by 2024 from its current figure of $24 billion. But market frictions such as regulatory obstacles and lack of information transparency put up to $7 billion of this untapped export potential at risk – especially for small businesses looking to trade more across borders’, stated Dorothy Tembo, acting Executive Director of the International Trade Centre. “There is however great scope for Pakistan to streamline processes, improve quality management and work with exporters to provide consistent, transparent and timely information.”

The most demanding measures are conformity assessment requirements such as testing and product certification, the survey finds. The report, based on a survey of approximately 1200 exporters, identifies the toughest trade hurdles facing Pakistani businesses. The report suggests ways for the government and the private sector to crank up competitiveness by addressing issues such as export inspections, tax refunds and export certification.

“For Pakistani exporters that are trying to introduce new products, access to export intelligence and information on what it takes to reach a new market is very valuable, particularly for new, small exporters that lack the scale to invest in information searching,” said Gonzalo Varela, Senior Economist at the World Bank in Pakistan. “Digital trade portals, easily accessible to everyone regardless of location or gender, can be a step in making non-tariff measures more transparent, and compliance less costly.”

The report contributes to the development of Strategic Trade Policy Framework (STPF) spearheaded by the Ministry of Commerce with the assistance of the World Bank under Pakistan Trade and Investment Policy Program (PTIPP). The PTIPP program is a collaborative effort between the Ministry of Commerce, the Australian Department of Foreign Affairs and Trade and the World Bank Group aimed at supporting Pakistan’s efforts to increase regional trade and investment, with a particular focus on strengthening links to other South Asian markets.


Notes for the Editor
Invisible Barriers to Trade: Pakistan – Business Perspectives. is based on a survey of almost 1,200 Pakistani traders identifies the biggest challenges and suggests ways to strengthen the country’s quality and customs infrastructure. Additional interviews were also conducted with representatives of various public agencies and business associations.

Download link

Non-tariff measures are official regulations, other than customs tariffs, related to cross-border trade in goods.

Procedural obstacles are practical challenges that traders may experience while attempting to comply with these measures.

About ITC – The International Trade Centre is the joint agency of the World Trade Organization and the United Nations. ITC assists small and medium-sized enterprises in developing and transition economies to become more competitive in global markets, thereby contributing to sustainable economic development within the frameworks of the Aid-for-Trade agenda and the United Nations’ Sustainable Development Goals.
For more information, visit

About The World Bank in Pakistan
Pakistan has been a member of the World Bank since 1950. Since then, the World Bank has provided $40 billion in assistance. The World Bank’s program in Pakistan is governed by the Country Partnership Strategy for FY2015-2020 with four priority areas of engagement: energy, private sector development, inclusion, and service delivery. The current portfolio has 46 projects with a net commitment of $9.1 billion.

For more information, visit:


Sustainability increases if ethanol is made from sugarcane juice: Study »


Sugarcane cultivation has benefitted from entrenched policies that incentivised production for decades


Sugarcane — a cash crop that requires large amounts of water and land to cultivate — has enjoyed immense political patronage and while it was responsible for making India become the second-largest producer of sugar, the country has witnessed a tremendous challenge to its resources.

Producing ethanol from sugarcane juice instead of molasses can help India meet its nutrition requirements and make resources like land and water more sustainable, said a July 24, 2020 study published in journal Environmental Research Letters.

The first-of-its-kind comprehensive analysis of India’s sugar industry — by researchers from Stanford University, United States — showed how the country must now move towards a more sustainable cultivation of sugarcane.

The country’s use of sugar dated back to the 1950s, when it was used for meeting the population’s basic calorie requirements.

These requirements, however, are now fulfilled, with poor populations receiving a full calorie intake as well, according to Rosamund Naylor, co-author and William Wrigley Professor in Stanford’s School of Earth, Energy & Environmental Sciences.

The Union government is, thus, becoming more concerned about nutrition because illness, disabilities and death are caused by micro-nutrient deficiency, prevalent among a large section of the Indian population.

Sugarcane cultivation — which benefitted from entrenched policies that incentivised production for decades — uses up more land and water, and, thus, reduces the use of these resources for foods that are rich in micro-nutrients, said the study.

Most populations can buy sugar at subsidised rates, but do not have access to adequate protein and micro-nutrients that are needed for cognitive growth, said Naylor.

A shift to using the crop as a source of energy generation can, thus, be beneficial for not just increasing access to nutrients, but also help in transitioning to renewable energy.

The Union government’s goal of increasing the ethanol-to-blending rate to 20 per cent by 2030 from a current six per cent can be achieved if it uses sugarcane juice to create ethanol, the study said.

A national biofuel policy that encourages ethanol production from sugarcane juice will help free up land and irrigation water, allowing for the cultivation of food crops that are rich in micro-nutrients.

India’s biofuel policy only recently allowed the use of sugarcane juice in ethanol production, in addition to molasses, the study pointed out.

“If the energy industry continues to use molasses as the bioethanol feedstock to meet its target, it would require additional water and land resources and result in the production of extra sugar,” said co-author Anjuli Jain Figueroa, a post-doctoral researcher in Earth system science.

Using sugarcane juice, however, can allow for the target to be met without needing water and land beyond current levels, said Figueroa.

Government spending to subsidise sugar can also be alleviated, allowing the government to sell sugar below cost, if sugarcane juice is used to produce ethanol, the study pointed out.

To illustrate their point of sugarcane cultivation using up more resources, the researchers focused their analysis on Maharashtra, one of the country’s largest sugarcane producers.

The study found sugarcane occupied only four per cent of Maharashtra’s total cropped area, but guzzled 61 per cent of the state’s irrigation water in 2010-11.

“This resulted in about a 50 percent reduction of river flow over that period,” said co-author Steven Gorelick, the Cyrus Fisher Tolman Professor at Stanford Earth. Gorelick also pointed out that the state — which is prone to floods — will find future water management challenging.

There are no reliable sugarcane maps either, pointed out lead author Ju Young Lee, a PhD student in Earth system science. “Using remote sensing data, I am developing current time-series sugarcane maps in Maharashtra – an important step forward,” she said.

The study also pointed out how institutionalised political interests in sugar production have threatened the country’s food, water and energy security over time.





The agricultural sector in Pakistan with its five subsectors; major crops, minor crops, livestock, fisheries and forestry has 18.9 percent of contribution in the GDP. While, the livestock is the major contributing sector with 11.11 percent of share in GDP, thus plays an important role in the economic growth of the country. However, the livestock population in 2018 was 196.5 million heads in Pakistan as compared to 191.5 million heads in 2017 (Economic Survey of Pakistan, 2016-17 and 2017-18).

As the livestock population is increasing, so are the feed requirements. But fodder cultivation in Pakistan is on the decline since time immemorial and seems like its importance is not being recognized.


  1. Fodder Production

Fodder production is the major limiting factor for livestock production in our country. In terms of Total Digestible Nutrients (TDN) we are short by about 25.65 million tones and in terms of Digestible Protein (DP) about 1.58 million tones.

  1. Less Area under Cultivation

Fodder crops are cultivated only on an area of 2.0 million ha in Pakistan which is far behind to meet the fodder requirements of the country. On the other hand, wheat is the largest sown crop and today constitutes 66 percent of the total area of food grains.

  1. Competition of Fodder Crops with Major Crops

The four major crops of Pakistan; wheat, rice, sugarcane and cotton, covered about 66 percent of the total cropped area. Major fodder crops grown during winter include berseem, lucerne, oats, barley and mustard; while during summer these are maize, sorghum, S.S. Hybrids, millet guar, and cowpeas. These crops cover 16 to 19% of the total cropped area in the country. The rabi fodder crops come in competition with wheat as both share the same sowing season while the Kharif fodder crops come in competition with major summer crops like cotton, sugarcane and rice.

  1. Lack of Quality and Quantity of Seed

Lack of good quality seed is another problem being faced today because private and government sectors are not as involved in the seed business of fodder crops as they are in case of wheat, cotton, etc. Along with these, the country only has one institute which solely works on fodder improvement namely Fodder Research Institute, Sargodha. This shows the level of concern of the government for the livestock sector.

  1. Fodder Scarcity Periods

There are months in which fodder availability is surplus but the country faces two scarcity periods as well; one from November to December and the other from May to June. It happens because farmer divides fodder into groups of winter and summer according to the appropriateness of sowing and harvesting. He has to grow the required fodder according to the weather conditions to get a better yield. Therefore, in the scarcity periods he either has to feed his animals a cheap low-quality fodder or keep them underfed. This ultimately results in the loss of health and the production of animals.

According to FAO worldwide comparison, developed countries with 25 percent of livestock are producing 63 percent milk and 66 percent meat. While only 37 percent milk and 34 percent of meat is being produced by the developing countries (including Pakistan) with 75 percent livestock. As in Pakistan, the daily milk average of a local cow is 8-10 liters a day against 35-40 liters of an American cow.

All of these problems along with the lack of appreciation of the government for fodder research are the main limiting factors for livestock production in Pakistan. A consistent supply of adequate and nutritious fodder is essential to bridge this gap and to exploit the livestock sector for economic growth and rural uplift as eight million families are involved in livestock raising.


  1. Production and Availability of Seed of Fodder Crops

Farmers usually have small landholdings and they do not grow fodder crops for seed production. Therefore, they depend on the market for seed every season. The government should involve private sectors in the seed production business and have them follow certain strategies to overcome the shortage issue of quality and quantity of seed in the country.

  1. Fodder Conservation

Conservation of fodder in the form of hay, silage and haylage is crucial. Because during March-April, the country has surplus fodder and usually most of it goes into waste rather than being stored.

For the consistent supply and to avoid scarcity periods, we need to focus on preserving fodder and forages on a long term basis by promoting and adopting new techniques like silage and haylage making which can ensure livestock is fed a balanced diet throughout the year.

  1. Adoption of Inter-Cropping System

Inter-cropping of fodder crops with

  • grain crops such as Wheat or rice or
  • non-food crops like cotton or sugarcane

are effective ways of increasing area under fodder crops. Also, Fodder-fodder inter-cropping has proved to be more productive than single fodder cropping.   Intercropping of maize fodder and cowpea significantly increased its production and quality of silage.

  1. Research Activities

Fodder sector has always been overlooked by the government despite its importance in the livestock sector. The government needs to focus on providing present institutes with the resources and funding they need to research in this area.

Fodder production technologies should be made for every region of the country and implemented by the government authorities. Research activities for quality and anti-quality parameters should be given equal importance as yield.

We are in the dire need to focus on developing new, better and resilient fodder crop varieties. The powers-that-be has to take the initiative to open more institutes that would work on developing high yielding and multi-cut fodder varieties and make sure good quality seed is distributed nationwide.

  1. Promoting the Adoption of Non-Conventional Fodder Crops

Rhode grass fodder, which was introduced in 2011 in Pakistan, can grow in saline soils. It has well adapted to Pakistan’s climate and soil and gives good results in salt-affected soils with underground salty water. It gives 50-70 tones yield per year, with less water and fertilizer, which is nearly double the yield as compared to alfalfa. The government should put efforts into extension work to educate the farmers about fodder cultivation and the importance and benefits of non-conventional fodder crops. The authorities should revisit the priority areas for the agriculture sector keeping in mind that the fodder crops have a direct impact on the economic gains from the livestock sector.

  1. Policymaking

Framers are rational and fixing support prices have always been a way to convince them to produce a certain crop. The government should put forward the price incentives for fodder crops so that the quantity of fodder can be increased to meet the national demand.

The policymakers emphasizing on enhancing the livestock production should not forget that targets can never be achieved until the feed of animals is taken solemnly.


University of Agriculture, Faisalabad




The open-burning of agriculture residues has many negative effects which include changes in the soil’s physical, chemical and biological properties by changing soil’s pH, nutrient availability and activity of microbes. Soil is one of the most vital natural resources. All micro-macro flora and fauna within the ecosystem meet their food demand from the soil. It is not possible to alter natural pedogenesis (soil formation) processes that are occurring in soil.

Burning of stubble promotes air pollution, contributes in global warming and climate change by releasing Greenhouse Gases like CO2, N2O etc. As a result smog is produced.

In Pakistan, smog has been affecting human health by causing diseases like asthma, emphysema, different allergies, irritation in eyes, and lung infection since many years now.

The ozone (O3) in smog also slows down plant growth and can cause widespread damage to forests, and to other crops.

Climate change is a major problem that the whole world is facing right now but developing countries like Pakistan are more affected by it as compared to developed countries because developed nations have taken specific adaptation measure. Some groups are at risk such as the poor due to climate change because it increases the food insecurity.


Why farmers burn rice residue?

Rice stubble has to be burned, detached, or added into the soil in order to prepare fields for the following wheat crop. The foremost favored residue management practice in Punjab, in terms of total rice area, is complete burning of rice residue, followed by the removal of rice residue. When farmers remove crop residue, it’s preponderantly as a result of to feed animals. Unlike wheat residue, rice straw cannot be utilized as fodder in the region.

Each practice has different cost implications. Few farmers who choose to use machines rather than burn their crop stubble, they use a harvester which piles the stubble behind it as it moves on so that it can be mixed with animal fodder or sold. The harvester can be rented. But it is costly for many small scale farmers and they cannot afford such an investment, or it does not make financial sense for them to invest in it. Mulching is a two-year-old process in Pakistan, and most farmers are not fully aware of the process and its consequences so they fear their next crop may be damaged.

Furthermore, complete residue removal is, on average, 33%-35% costlier to farmers than full burning of residue. They do not agree with using a great amount of cost on diesel usage. Then eventually they do not want to adopt modern methods. So, government should sponsor farmers to avoid residue burning practices.

What Government is doing?

Stubble burning, as well as burning of other waste have been banned in October by provincial government under Section 144 of the Code of Criminal Procedure. This clause, enacted in 1898 and amended in 1997, gives the government emergency powers to prevent actions that may cause harm or loss of life. Farmers though, do not take the ban seriously.

Zartaj Gul Wazir (the federal Minister of Climate Change to the provincial Punjab) Environment Protection Department says that, the consensus in Pakistan is the problem is India’s stubble burning.

The Government believes that stubble burning is almost non-existent in Pakistan as the ban is being fully implemented. But NASA satellite images do show more red spots denoting high heat emissions fires on the Indian side. On the Pakistani side, there are a few dispersed places where such spots are located.

So stubble burning is actually a problem in Pakistan, despite being the easy way out. Our soil is already low on fertility. By burning it we are continuously distressing it of its minerals, its nutrients and properties.

Seeds and other agriculture inputs are so costly nowadays that it is inconceivable to buy more land solely to plough the stalks back in the ground and burning is much more favorable for farmers. If the government gives subsidies to farmers, circumstances can change.

Incorporation of rice straw in saline soil and other method:

Soil salinity is a significant issue of agriculture in Pakistan. Salt-affected soils alone occur on over six million hectares of area and above 70% of the tube-wells in saline areas are pumping out brackish water. Soil salinity badly affect soil, as salts are less likely to be leached from the soil in the areas where rainfall is and therefore, bad quality irrigation water with high levels of salts will impact soil poorly. It may result in soil dispersion, soil surface sealing, crusting, erosion, poor infiltration and poor seedbeds.

Salinity affects almost every aspect of plant growth and development from seed germination to vegetative and reproductive growth. Soil salinity imposes ion toxicity, deficiency of many nutrients, osmotic and oxidative stress in the plants, and thus restricts water uptake from soil.

The main approach to reducing paddy residue burning has been to seek alternatives for residue utilization and management both on and off the field. So rather than burning rice straw, its incorporation in saline soil have shown many good results. It is the best example of the triple bottom line as it is environmental friendly, socially progressive and economical.

A study shows that how rice straw amendments ameliorates the harmful effects of salinity in saline paddy soil. High concentrations of salt in soils affect plant growth by restricting it and have an enormous in?uence on nitrogen dynamics in the soil solution.

However, addition of rice straw is supposed to reduce the harmful impacts of salinity on nitrogen cycling, therefore affecting plant growth in a positive way. Adding raw rice straw in saline paddy soil decreased the bio-availability of salts. Bulk soil pH will decrease and nitrogen availability will increase with increasing rice straw in addition to saline paddy soil.

Another recent study found that mainly two selectively enriched bacterial species (Pseudomonas sp. and Paenibacillus sp.) Are needed to drive an effective degradation of plant polymers. Their findings can guide the design of a synthetic bacterial consortium that might improve the release of sugars from agricultural plant residues (i.e. saccharification) processes in bio refineries. Additionally, they can facilitate to expand our ecological understanding of plant biomass degradation in enriched bacterial systems.

So, farmers need awareness about the incorporation of rice stubble in saline soils and inoculating bacterial consortium for degradation. No doubt both are time consuming methods but they are very economical and results are extremely impressive. Government has to do the proper extension work for a farmer and convince them to apply biofertilizer. And as well as proper training also required on the usage of biofertilizer for farmers. We have to overcome these problems to get long term good results in order to reduce pollution.




  • The open-burning of agriculture residues change the soil’s physical, chemical and biological properties by changing soil’s pH, nutrient availability and activity of microbes.
  • Moreover, promotes air pollution, contributes in global warming and climate change by releasing Greenhouse Gases like CO2, N2O etc. and as a result smog is being produced.
  • It is impossible to change naturally occurring pedogenesis (soil formation)  processes. No other resource can be used instead of ‘soil’ in case it’s lost. Hence, it is high time that we should act more responsibly towards soil compared to other natural resources.
  • Soil salinity causes soil dispersion, soil surface sealing, crusting, erosion, poor infiltration and poor seedbeds and affects almost every aspect of plant growth and development from seed germination to vegetative and reproductive growth.
  • If farmers stop burning rice straw and start using it to ameliorate saline soil which is one of the major problem in the soils of Pakistan, it surely will improve soil properties, as raw rice straw addition to saline paddy soil decreased the bio-availability of salts.
  • It impacts the environment by reducing the pollution as well.
  • Recently, some species of bacteria have been found that can play a huge role in effective degradation of plant polymers.
  • Government should either subsidized farmers to avoid the burning of rice stubble or they should do the proper extension work for a farmer and convince them to apply biofertilizer.
  • If there will be no residue burning, undoubtedly crop quality will improve as the crop will get all required nutrients from soil. It will improve air and soil quality.
  • It will also improve soil biodiversity and also alleviate climate impacts and lower the health hazards caused by smog.