Published by Gbaf News
Posted on May 19, 2018
It all started in 2016 in rural Sutton (Quebec) when Ramen Dutta, now CTO of Motorleaf, had trouble finding friends to water his plants while he was away on vacation.
With a US$2.85 million round of financing, artificial intelligence start-up Motorleaf can revolutionize greenhouse growers’ crop planning, achieving major productivity gains and reducing greenhouse gas (GHG) emissions. The financing round comprised notably Radicle Growth, Desjardins Capital, Real Ventures, Fluxunit and BDC Capital. With their support, Motorleaf can be a game changer in this agri-food sector niche in industrialized countries.
Motorleaf develops yield-predicting algorithms and indoor growth sensors. Using these advanced technologies that monitor plant growing conditions, greenhouse vegetable and tomato producers can make better business decisions and reduce costs, energy in particular, as well as water consumption, a critical factor in many regions around the world.
“We’re ready to distribute our technology so farmers can meet their fullest potential and acquire an innovative cost-cutting tool within the controlled-environment agriculture sector,” said Alastair Monk, co-founder and CEO of Motorleaf.
Predicting the amount of vegetables from a harvest is currently a time-consuming process. Agronomists count samples of vegetables, leaves and flowers in a small area and that sample then serves to estimate the expected yield of the entire grow operation. Often imprecise, farmers are unsure if they will produce enough vegetables to meet contract obligations or know how much labour they will need to package their produce. If they produce too much, farmers try to sell their perishable goods quickly at rock-bottom prices. Using Motorleaf’s artificial intelligence and machine-learning algorithms, the digital agronomist software can acquire data from indoor growing conditions. In turn, the algorithms learn growing patterns in the greenhouse, which then can predict the size of future harvests.
Cutting harvest prediction errors by half
Harvest yield-predicting algorithms are the latest technology born from Montreal’s booming artificial intelligence sector. With this financing round, Motorleaf aims to further develop its software and sensors so that its equipment can acquire additional data from common indoor climate control and irrigation systems. Farmers can now adopt this technology with a small addition of Motorleaf equipment, but without the need for dramatic changes to their greenhouse infrastructure.
“Better yield prediction is only the beginning for Motorleaf’s added value to this sector,” says Alastair Monk. “We’re ultimately producing dynamic grower protocols, which help manage everything from light and nutrients to predicting greenhouse diseases before they happen, and optimized growing conditions that increase return on investment – all based on real-time data.”
Initial trials of the technology since October 2017 in a 70-acre California greenhouse cultivating tomatoes demonstrated its value to farming. Client SunSelect reduced its error in predicting weekly tomato yield by half, resulting in significant cost savings for the grower. As a result of the improved predictability using Motorleaf’s technology, SunSelect has since abandoned manual yield predictions in favour of Motorleaf’s algorithms. See the SunSelect case study at https://bit.ly/2IxxeF9.
The province of Quebec has 900 greenhouses, half of which have an area of under 999 square metres
Data compiled by the Ministère de l’Agriculture, des Pêcheries et de l’Alimentation (MAPAQ) shows 900 greenhouses in 2016, including 356 specialized in vegetables, 388 in flowers and 156 mixed greenhouses, for a total area of 297.2 hectares (ha). The same data shows that the three regions with the largest greenhouse areas were Montérégie (77.8 ha or 26%), Laurentians (54.3 ha or 18%) and Laval(34.8 or 12%). As for the number of farms, Montérégie had 226 (or 25%), Laurentians 117 (or 13%), Chaudière-Appalaches 72 (or 8%), Centre-du-Québec 59 (or 7%), Laval and Lanaudière with 55 each (or 6%) and the Eastern Townships 51 (or 6%).
Inspired by dead plants
The idea for Motorleaf stems from the heartbreak of returning home to find your prized plants dried out. Living in rural Sutton, Ramen Dutta, CTO of the Montreal start-up, had trouble finding friends that could drive to his home and water his indoor plants while he was away on vacation. Being an agricultural engineer, he built an automated, sensor-controlled irrigation system that would become the foundation of Motorleaf’s technology.
SOURCE Desjardins Capital
It all started in 2016 in rural Sutton (Quebec) when Ramen Dutta, now CTO of Motorleaf, had trouble finding friends to water his plants while he was away on vacation.
With a US$2.85 million round of financing, artificial intelligence start-up Motorleaf can revolutionize greenhouse growers’ crop planning, achieving major productivity gains and reducing greenhouse gas (GHG) emissions. The financing round comprised notably Radicle Growth, Desjardins Capital, Real Ventures, Fluxunit and BDC Capital. With their support, Motorleaf can be a game changer in this agri-food sector niche in industrialized countries.
Motorleaf develops yield-predicting algorithms and indoor growth sensors. Using these advanced technologies that monitor plant growing conditions, greenhouse vegetable and tomato producers can make better business decisions and reduce costs, energy in particular, as well as water consumption, a critical factor in many regions around the world.
“We’re ready to distribute our technology so farmers can meet their fullest potential and acquire an innovative cost-cutting tool within the controlled-environment agriculture sector,” said Alastair Monk, co-founder and CEO of Motorleaf.
Predicting the amount of vegetables from a harvest is currently a time-consuming process. Agronomists count samples of vegetables, leaves and flowers in a small area and that sample then serves to estimate the expected yield of the entire grow operation. Often imprecise, farmers are unsure if they will produce enough vegetables to meet contract obligations or know how much labour they will need to package their produce. If they produce too much, farmers try to sell their perishable goods quickly at rock-bottom prices. Using Motorleaf’s artificial intelligence and machine-learning algorithms, the digital agronomist software can acquire data from indoor growing conditions. In turn, the algorithms learn growing patterns in the greenhouse, which then can predict the size of future harvests.
Cutting harvest prediction errors by half
Harvest yield-predicting algorithms are the latest technology born from Montreal’s booming artificial intelligence sector. With this financing round, Motorleaf aims to further develop its software and sensors so that its equipment can acquire additional data from common indoor climate control and irrigation systems. Farmers can now adopt this technology with a small addition of Motorleaf equipment, but without the need for dramatic changes to their greenhouse infrastructure.
“Better yield prediction is only the beginning for Motorleaf’s added value to this sector,” says Alastair Monk. “We’re ultimately producing dynamic grower protocols, which help manage everything from light and nutrients to predicting greenhouse diseases before they happen, and optimized growing conditions that increase return on investment – all based on real-time data.”
Initial trials of the technology since October 2017 in a 70-acre California greenhouse cultivating tomatoes demonstrated its value to farming. Client SunSelect reduced its error in predicting weekly tomato yield by half, resulting in significant cost savings for the grower. As a result of the improved predictability using Motorleaf’s technology, SunSelect has since abandoned manual yield predictions in favour of Motorleaf’s algorithms. See the SunSelect case study at https://bit.ly/2IxxeF9.
The province of Quebec has 900 greenhouses, half of which have an area of under 999 square metres
Data compiled by the Ministère de l’Agriculture, des Pêcheries et de l’Alimentation (MAPAQ) shows 900 greenhouses in 2016, including 356 specialized in vegetables, 388 in flowers and 156 mixed greenhouses, for a total area of 297.2 hectares (ha). The same data shows that the three regions with the largest greenhouse areas were Montérégie (77.8 ha or 26%), Laurentians (54.3 ha or 18%) and Laval(34.8 or 12%). As for the number of farms, Montérégie had 226 (or 25%), Laurentians 117 (or 13%), Chaudière-Appalaches 72 (or 8%), Centre-du-Québec 59 (or 7%), Laval and Lanaudière with 55 each (or 6%) and the Eastern Townships 51 (or 6%).
Inspired by dead plants
The idea for Motorleaf stems from the heartbreak of returning home to find your prized plants dried out. Living in rural Sutton, Ramen Dutta, CTO of the Montreal start-up, had trouble finding friends that could drive to his home and water his indoor plants while he was away on vacation. Being an agricultural engineer, he built an automated, sensor-controlled irrigation system that would become the foundation of Motorleaf’s technology.
SOURCE Desjardins Capital
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