Fall ArmywormMachine learning, a variation of artificial intelligence that includes the development of algorithms that independently learn new information, has innumerable applications. An example of this can be found in Africa, where the fall armyworm pest in Uganda has ravaged crop yields. Amid the destruction, a new machine learning-based app created by a Ugandan developer has the potential to stop the spread of the crop-destroying pest.

Agriculture in Uganda and the Fall Armyworm

Approximately 22% of Uganda’s GDP comes from agriculture, with most Ugandans working in the agricultural sector, often engaging in subsistence farming. With the nation’s economic performance relying on successful agricultural harvests and the population’s everyday food source coming from their own crop yields, any invasion of pests in Uganda can have serious consequences.

In 2016, Uganda experienced its first invasion of the fall armyworm pest, the larva of the armyworm moth. A native of the tropical regions of the western hemisphere, the fall armyworm pest eats through crops for nourishment before its transformation into a moth. By mid-2017, the fall armyworm had been detected throughout Uganda and was estimated to have caused $192 million USD in maize crop losses alone. In some regions, up to 75% of crop yields were lost.

Despite the severe threat posed by the fall armyworm pest in Uganda, local developers have created a machine learning-based tool to assist Ugandan farmers with detecting the presence of the fall armyworm in their crops and preventing its spread.

Machine Learning to Protect Crops

In the aftermath of the arrival of the fall armyworm pest, Nazirini Siraji, a Ugandan woman from the city of Mbale, began work on a modern solution to the age-old problem of pest invasions. After attending one of Google’s Codelabs events, Siraji used Google’s TensorFlow platform to develop her Farmers Companion App. TensorFlow is an open-source machine learning tool that enables developers like Siraji to create digital solutions powered by artificial intelligence.

The Farmers Companion App enables farmers to use mobile technology to identify this specific pest on their crops and their lifecycle stage. Using this information, the app notifies the user about the threat level faced by their crops and the extent to which the fall armyworm has the potential to spread. The app also recommends specific pesticide treatments that can be used based on the situation of the farmer’s crops.

According to Google, the app has already been deployed in the agricultural lands surrounding Mbale, where Siraji partners with local farmers in utilizing her Farmers Companion App.

Big Tech Meets Local Developer

The global expansion of the internet has been accompanied by a rise in local innovation aimed at solving local issues. In Africa, pest invasions have been responsible for countless crop shortages and famines, which exacerbates problems of instability and poverty. While invasions from pests like the fall armyworm will inevitably occur in the future, they will not happen again without opposition from new technology.

John Andrikos
Photo: Flickr

AI Increases Food SecurityArtificial Intelligence seems like a far-off concept reserved for science fiction. In truth, AI is present in modern life and the advancements in this technology are being used to combat global poverty. Most prominently, computer scientists and engineers are improving the ways that AI increases food security globally. The need for utilizing technology in food security is essential to protect more than 800 million people suffering from hunger worldwide.

Predicting Threats to Food Security

A vital step to protect food security is looking ahead and responding proactively to potential problems. The Nutrition Early Warning System (NEWS) works by gathering massive amounts of data from vast sources to forecast developing situations affecting food supply. NEWS is a perfect example of how AI increases food security with constant improvements in its system to enhance response times to price changes, poor weather conditions for food development and other global crop issues.

The effectiveness of machine learning far surpasses human data collection and these types of technology have already seen success. Through the algorithms created by AI technology, a forecasted drought prevented many Colombian farmers from planting crops that would not have been fruitful. This prediction saved the farmers millions of dollars by avoiding crop loss during the dry spell. Preserving large amounts of money to spend during opportune times is another way AI increases food security and stabilizes supply.

AI Optimizes Agricultural Procedures and Production

People living in rural areas that work in farming communities are usually the most susceptible to extreme poverty. AI can improve working conditions and modernize agriculture to protect vulnerable populations and provide them with upward economic mobility through technology education and increased crop production.

AI robotics is revolutionizing agriculture and crop harvesting robots as well as AI-enhanced drones are increasing production and keeping workers safe. Robotic weed control allows for the proper and safe distribution of herbicides that can be harmful to humans. This also prevents herbicide resistance. In Argentina, drones inspect wheat crops for harmful infections and pests. AI increases food security by diagnosing soil conditions as well. This technology allows workers to implement the necessary strategies for correcting nutrient deficiencies.

The most important aspect of these technologies is that they provide benefits but will not reduce the need for actual workers. Though education in these fields can be expensive, the skills learned will add value and mobilize people out of extreme poverty.

The FAO AI Systems Used for Food Security

The Food and Agriculture Organization (FAO) has implemented two programs in which AI increases food security and improves agriculture sustainability; the FAO’s WaPOR portal and the Agriculture Stress Index System (ASIS). Both systems monitor water usage in agriculture in different ways.

  • The FAO’s WaPOR portal monitors water in the Near East and African regions. It does this through open-source technology that gathers massive amounts of data. Simultaneously, the AI analyzes the data to determine the best water use for different crops and regions and uploads the information in real-time.
  • ASIS works similarly to NEWS. It is a satellite system that works as an early detection system for droughts or other water shortages. ASIS breaks down the information from a global standpoint to each country and region. Doing this allows people to be proactive in their preparation for impending droughts by improving water usage and shoring up logistics of moving aid to an area troubled by food shortages, thereby preventing hunger.

The Future of Food Security

As time progresses, AI will improve and become more common, eventually becoming cheaper and more accessible worldwide. With the rapid advancement in this technology and what is already in place to sustain food security using AI, a hunger-free world is a closer reality.

– Zachary Kunze
Photo: Flickr

Crop Pests and DiseasesThe global climate is changing and food demands are increasing. As a result, the threat of crop pests and diseases could mean widespread hunger, especially for at-risk populations. The nature of many agricultural pests and pathogens compound this problem. They are hard to detect, widespread, and highly specified.

Containing these diseases can only happen once they’ve become detectable. Consequently, this often means that large amounts of crops have been damaged past the point of recovery and containment. One disease alone can cause financial losses in the hundreds of millions. A single outbreak of Karnal bunt fungus in north Texas caused a $250 million loss in revenue in 2001.

More Food, More Pests?

The world’s food supply faces increased biological threats due to climate change, increased travel between countries, and increases in large-scale food production. The need for food increases each year as well, with a predicted nine billion people in need by 2050. Mass agriculture of staple crops, such as wheat, rice, palm, cassava and various fruit and vegetables, face dangers unique to each crop:

  • Cassava Mosaic Virus: This virus produces ‘s’ shaped stalks, stunted plant growth, and low yields.

  • Coconut Rhinoceros beetle: The ‘Coconut’ Red Rhinoceros Beetle (X. glabratus) spreads fungus called Raffaelea Lauricola that kills redbay and avocado trees, effectively starving their pollinators.

  • Wheat Rust: This fungus is caused by Puccinia triticina (Brown Leaf Rust), and it reduces wheat kernel yield and size. It is a prolific spreader that is present in major wheat-growing sites worldwide.

  • Citrus Greening: This virus is rampant in the southeastern U.S. as well as citrus and other orchards worldwide. As of 2019, the disease has reduced Florida citrus production by 75%.

Additionally, the loss of staple foods to crop pests and diseases can contribute to livestock malnutrition. Roughly 36% of the world’s crops are grown for feeding livestock. In some developing countries, these animals are essential to meeting a minimum caloric intake. Thus, famine in developing countries can commonly be exacerbated by a secondary loss in crop-dependent food supplies, such as cattle or goats.

However, a potential solution to the malnutrition of both humans and livestock lies in an unforeseen place.

Teaching Old Dogs New Tricks

dog’s sense of smell is consistently strong, with some odors detectable in parts per trillion. The scent abilities of our four-legged canine friends have an ancient history of benefits. This includes successful applications in hunting, national security, border patrol, medicine and agriculture. This skill also makes them well suited for training in detecting crop pests and diseases.

Dogs have a particular knack for new scents, described as a form of neophilia. “This technology is thousands of years old – the dog’s nose; we’ve just trained dogs to hunt new prey: the bacteria that causes a very damaging crop disease,” says U.S. Department of Agriculture researcher Timothy Gottwald.

Agricultural scientists approve of this new application (detection of crop pests and diseases) of a canine’s olfactory system. Equally important to note is the cost-saving potential of training dogs over traditional identification and lab processing, as money is a pivotal issue in developing countries when eradicating crop diseases.

Conclusion

Food security, the increase in crop pests and diseases and the costs of testing for agricultural diseases is a dynamic problem combination in need of unique solutions. To date, dogs have been successful in identifying crop diseases such as clubroot, wheat rust and citrus greening. They have also shown promise in early and accurate detection. These early successes imply that training our canine companions can be a worthwhile and life-saving venture for millions of food-insecure peoples in the future.

Katrina Hall
Photo: Flickr