CSBE/SCGAB Awards
Each year, the CSBE/SCGAB presents Awards and Grade of Fellows to celebrate and encourage excellence within the Canadian bioengineering community. Please consider nominating a member.

John Ogilvie Research Innovation Award

The CSBE/SCGAB John Ogilvie Research Innovation Award is to acknowledge outstanding contributions to research, in any field of research relevant to CSBE/SCGAB, by an individual or team of researchers (which may include graduate or undergraduate students). The Research Innovation Award is not intended to acknowledge the cumulative impact of a career’s worth of research contributions; rather, it is intended to recognize the innovation or ingenuity of a single research project. The research team (individual or group of researchers) is required to prepare a brief nomination that clearly explains why the research is innovative.

Recipients of the CSBE/SCGAB John Ogilvie Research Innovation Award will be selected by the CSBE/SCGAB Awards Committee. Up to three Research Innovation Awards may be awarded each year. All members of a research team must be members of CSBE/SCGAB in good standing. Individuals may be awarded the Research Innovation Award multiple times throughout their career, however, not in consecutive years.

Le Prix John Ogilvie pour l'innovation en recherche de la CSBE/SCGAB vise à reconnaître les contributions exceptionnelles à la recherche, dans tout domaine de recherche pertinent pour la CSBE/SCGAB, d'une personne ou d'une équipe de chercheurs (qui peut comprendre des étudiants diplômés ou de premier cycle). Le Prix d'innovation en recherche ne vise pas à reconnaître l'impact cumulatif de la valeur d'une carrière de contributions à la recherche, il vise plutôt à reconnaître l'innovation ou l'ingéniosité d'un seul projet de recherche. L'équipe de recherche (individu ou groupe de chercheurs) doit préparer une brève mise en candidature qui explique clairement pourquoi la recherche est innovatrice.

Les récipiendaires du Prix John Ogilvie pour l'innovation en recherche seront choisis par le Comité des prix CSBE/SCGAB. Jusqu'à trois bourses d'innovation en recherche peuvent être attribuées chaque année. Tous les membres d'une équipe de recherche doivent être membres en règle de la CSBE/SCGAB. Les personnes peuvent se voir décerner le Prix de l'innovation en recherche à plusieurs reprises au cours de leur carrière, mais pas au cours d'années consécutives.

Nomination Form

JohnOgilvie.doc

2024 John Ogilvie Research Innovation Award

 

P. Goel, P. Daggupati, and R. Rudra

Non-point source (NPS) pollution, mainly from agricultural runoff, poses a significant threat to water bodies, demanding effective mitigation measures. Conventional approaches to mitigating NPS pollution through uniform application of best management practices (BMPs) lack effectiveness due to overlooking critical seasonal variations and specific storm events. To tackle this, a novel approach integrating temporal and spatial aspects of NPS pollution was developed, identifying threshold precipitation events and critical source areas (CSAs) within watersheds. A threshold precipitation event is defined as the maximum storm intensity in which the sediment or phosphorus generated in a watershed is below seasonal tolerance limits of sediment and phosphorus. The proposed approach was tested across diverse agricultural watersheds in southern Ontario utilizing an event based Agricultural Non-Point Source (AGNPS) model which was calibrated against streamflow, sediment, and phosphorus data. The findings reveal that frequent early spring storms occurring every 5 years in upland watersheds and every 12 years in lowland watersheds lead to sediment and phosphorus runoff. Notably, summer storms with return periods of up to 100 years did not result in sediment and phosphorus runoff. Additionally, critical source areas are dispersed throughout the watersheds, with climate-induced hydrological shifts favoring winter occurrences, while late winter and early spring remain primary periods of concern. This study highlights the importance of targeted BMP placement and adaptation strategies to address evolving hydrological patterns and NPS pollution dynamics.

La pollution diffuse (SNP), principalement due au ruissellement agricole, constitue une menace importante pour les masses d'eau et exige des mesures d'atténuation efficaces. Les approches conventionnelles visant à atténuer la pollution due aux SNP par l'application uniforme des meilleures pratiques de gestion (BMP) manquent d'efficacité parce qu'elles ne tiennent pas compte des variations saisonnières critiques et des tempêtes spécifiques. Pour remédier à ce problème, une nouvelle approche intégrant les aspects temporels et spatiaux de la pollution due aux SNP a été développée, en identifiant les seuils de précipitations et les zones sources critiques (CSA) dans les bassins versants. Un seuil de précipitations est défini comme l'intensité maximale d'une tempête au cours de laquelle les sédiments ou le phosphore générés dans un bassin versant sont inférieurs aux limites de tolérance saisonnières des sédiments et du phosphore. L'approche proposée a été testée dans divers bassins versants agricoles du sud de l'Ontario à l'aide d'un modèle AGNPS (Agricultural Non-Point Source) basé sur les événements et étalonné par rapport aux données sur le débit, les sédiments et le phosphore. Les résultats révèlent que les tempêtes fréquentes du début du printemps, qui se produisent tous les 5 ans dans les bassins versants des hautes terres et tous les 12 ans dans les bassins versants des basses terres, entraînent un ruissellement de sédiments et de phosphore. En particulier, les orages d'été dont la période de retour peut atteindre 100 ans n'ont pas entraîné d'écoulement de sédiments et de phosphore. En outre, les sources critiques sont dispersées dans les bassins versants, les changements hydrologiques induits par le climat favorisant les événements hivernaux, tandis que la fin de l'hiver et le début du printemps restent les principales périodes de concentration des sédiments et du phosphore.

2021 John Ogilvie Research Innovation Award

ramesh

Contribution: Safe Use of Untreated or Partially Treated Wastewater in Agriculture                                                            

Dr. Shiv Prasher 

Field lysimeters, 1.0 m height x 0.45 m diameter, were used to determine the fate, transport, and translocation of heavy metals in irrigation water in potatoes and spinach plants grown on a sandy soil. Plantain peel biochar (1% w/w) was incorporated in the top 0.1 m of soil. Control and biochar treatments were replicated three times in a completely randomized. Results showed that all heavy metals accumulated in the topsoil. No heavy metals were detected in the leachate. Heavy metals also translocated to all parts of the potato plant, including roots, peel, flesh, and shoots. Biochar amendment significantly reduced (p<0.05) Cd, Cu, Cr, Pb and Zn in the flesh. In spinach, biochar amendment reduced Zn uptake by 42%. Yields, however, were not significantly different between the treatments.

2021 John Ogilvie Research Innovation Award

jianramesh

Contribution: Mathematical Models Of Stored-Grain Ecosystems For Management Of Stored Grains                                                

Digvir Jayas and Fuji Jian

Globally, more than 3.2 Gt (billion tonnes) of grains, pulses and oilseeds (hereinafter collectively referred to as grains) are produced annually and stored at many points after harvesting, prior to being delivered to processors and domestic and international consumers. Post-harvest losses range from 2% in North America to 30% in developing countries. When spoilage occurs in an individual storage bin, 100% of the grain can become unfit for human consumers and sometimes even unfit as animal feed. Drs. Jayas and Jian have been working together for over 15 years towards the development of mathematical models as management tools for reducing quantitative and qualitative losses in stored grains. Our major contributions are to model insect movement and detection in grains and for drying of grains.

2023 John Ogilvie Research Innovation Award

jianramesh

Contribution: Method to Rapidly Detect Insects in Granular Materials                                           

Digvir Jayas and Fuji Jian

The detection of low levels of insect infestation in grain was identified as the top priority research needed because detection of low levels of infestation by using sampling is a slow, inaccurate, and expensive process (take more than 6 hours and recover less than 30% of insects). In that period, grain may be filled in large bins and ships thus contaminating large quantities and increasing the cost of fumigation. Their research has investigated many techniques based on soft x-rays, thermal imaging, hyperspectral imaging, electronic nose, mechanical separation, and microwaves for rapid detection of insects. A device was developed and evaluated (a US Patent 10,582,713 B2 entitled “Method to Rapidly Detect Insects in Granular Materials”) to rapidly detect insects in granular materials. The developed device detects insects in grains in less than 5 min with high accuracy (>80% insect recovery) using a household microwave. Prototypes of the developed units were given to Canadian Grain Commission and Poulin’s Pest Control for field evaluation. Both confirmed that the device was efficient and effective in detecting low-level insect infestation. Other methods can also detect low-level insect infestations but are much more costly than the device based on household microwave. They expect the device will be used in Canada and globally.    

La détection de faibles niveaux d'infestation d'insectes dans les céréales a été identifiée comme recherche prioritaire nécessaire, car la détection de faibles niveaux d'infestation par échantillonnage est un processus lent, imprécis et coûteux (il prend plus de 6 heures et permet de récupérer moins de 30 % des insectes). Pendant cette période, les grains peuvent être remplis dans de grandes cellules et dans des navires, ce qui contamine de grandes quantités et augmente le coût de la fumigation. Leurs recherches ont porté sur de nombreuses techniques basées sur les rayons X, l'imagerie thermique, l'imagerie hyperspectrale, le nez électronique, la séparation mécanique et les micro-ondes pour la détection rapide des insectes. Un dispositif a été mis au point et évalué (brevet américain 10,582,713 B2 intitulé "Method to Rapidly Detect Insects in Granular Materials") pour détecter rapidement les insectes dans les matériaux granulaires. Le dispositif mis au point détecte les insectes dans les grains en moins de 5 minutes avec une grande précision (>80 % de récupération des insectes) en utilisant un four à micro-ondes domestique. Des prototypes des appareils mis au point ont été remis à la Commission canadienne des grains et à Poulin's Pest Control pour une évaluation sur le terrain. Tous deux ont confirmé que l'appareil était efficace et performant pour détecter les infestations d'insectes de faible intensité. D'autres méthodes peuvent également détecter de faibles infestations d'insectes, mais elles sont beaucoup plus coûteuses que l'appareil basé sur les micro-ondes domestiques. Ils espèrent que cet appareil sera utilisé au Canada et dans le monde entier.

2020 John Ogilvie Research Innovation Award

ramesh

Contribution: Research in soil and water engineering                                                             

Ramesh Rudra Ph.D., P.Eng. is the recipient of the CSBE/SCGAB John Ogilvie Research Innovation Award for his outstanding contributions to research in soil and water engineering. Dr. Rudra is a professor of Water Resources Engineering at the School of Engineering, University of Guelph. He obtained the B. Sc. in Agricultural Engineering in 1970 from the Punjab Agricultural University (India) and M.S. in Agricultural Engineering in 1976 and Ph.D. in Agricultural Engineering in 1980 from the Pennsylvania State University (USA).

The focus of Dr. Rudra’s research program has been on the development of agricultural nonpoint source pollution control practices for Ontario’s climatic conditions, including mechanics and modelling of processes of drainable water quantity and quality at plot, field, and watershed scale. His contributions include innovative ways of introducing the concept of temporal variations in soil hydraulic and erosion characteristics, targeting approaches for agricultural watershed management, mutli-tier approaches to watershed management, and modelling and monitoring procedures to identify sources of runoff, erosion and pollution from agricultural watersheds.

Ramesh’s research group introduced the application of modelling approaches for agricultural non-point source pollution management during 1980’s and SWAT modeling in the Canadian Great Lakes basin in early 2000. The modelling approaches and the SWAT model are currently used by many conservation authorities in Ontario and many other public and private sectors in Canada. His recent research work has focused on winter hydrology of Ontario, variable source hydrology, effect of climate change on precipitation and temperature regimes, and nutrient management.

Dr. Rudra has supervised over 120 Highly Qualified Personnel (M.Sc, M.Eng., Ph.D. and Post-Doctoral Research Fellows), published more than 200 refereed publications, ten book chapters, one book, and more than 550 presentations at national and international conferences, workshops and symposia. For his exceptional services to CSBE and significant contributions to soil and water engineering field in Canada, Dr. Rudra received the CSBE’s Maple Leaf Award in 2018. He was elected to the grade of Fellow by CSBE in 2005. Ramesh was also made a Fellow of the Indian Society of Agricultural Engineers in 2012.