title: Automated aerial seed planting using biodegradable polymers

authors: Cozens, Wade

subjects: Biodegradable

abstract: The purpose of the thesis was to undertake a preliminary product design to assess the feasibility of using drone technology to aid reforestation for automated seed planting. This product would be able to increase productivity and reduce labour costs, especially when applied in difficult to reach terrains around New Zealand. Ultimately, the final product would be a weaponised drone or a swarm of drones that can fire plastic seed capsules into soil to a specific depth to prevent predation and ensure optimal germination conditions. The proof of concept hinges on the success of three objectives: Assessing and controlling the capsule’s biodegradability in soil. A method of mass manufacturing projectile seed capsules that can be delivered at high velocity and the ability of it to be fired into soil to a specific depth to ensure safe germination.  

Novatein was blended with poly(butylene adipate terephthalate) (PBAT) to aid sheet extrusion and improve water resistance. Biodegradability was tested by measuring the ability of bacteria and fungi to metabolise the polymer blends into CO2 by enclosing samples in soil at 25 °C. PBAT showed very little biodegradation under these conditions, where approximately 3 % of the theoretical carbon content of the sample was converted to CO2. Novatein reached 20 %, and the blends were intermediate, based on the amount of PBAT present. It was concluded that PBAT can effectively control the rate and extent of biodegradation in blends with Novatein. 

A method for mass manufacturing seed capsules was evaluated by compression moulding spheres to test mouldability and manufacturing lap welded samples to quantify weld strength. Blends of Novatein and PBAT were successfully moulded and welded above the glass transition temperature of the material; optimal parameters were 105 °C with a three minute hold time. Lap welds were tested by varying the compression force and sheet thickness and thereby reducing the weld times to approximately eight seconds. Welded samples were tested for tensile and peel strength, where 0.68 mm thick sheets, welded at 750 N compression force, yielded the highest tensile strength (88 % that of an un-welded samples). Thicker sheets (1.52 mm) welded at 900 N compression force, resulted in the highest peel force. Producing capsules capable of penetrating soil would benefit from thicker sheets using sufficient pressure to prevent peeling at the seam. 

Finally, seed capsule delivery was assessed using empirical modelling in combination with controlled soil conditions. Models created by Young and Lorenz used a dynamic cone penetrometer (DCP) to measure the soil’s penetration resistance to predict the penetration depth of a known projectile. These models were developed for considerably heavier projectiles (> 2.2 kg) and penetration depths much greater than considered here. Considering the DCP measures the soils resistance to penetration at a depth of one meter, a comparison to a 10th scale model was investigated. Contrary to expected, the standard DCP predicted the penetration depth of high velocity projectiles to a reasonably accuracy (~20 %) using two different types of homogenous sand, tested at three moisture contents. The scaled model failed to account for soil types, which was shown to have significant influence during high velocity testing. The work here highlighted the importance of considering realistic forestry soil, despite the accuracy of the prediction in homogenous sand.

Although an integrated product has not been developed, this project has shown that a strategy exists for controlling the rate of biodegradation of Novatein/PBAT. A plausible method for mass manufacturing seed capsules was demonstrated using compression moulding of Novatein blends. Penetration depth was predicted accurately for homogenous soil, this requires further research into applying the model to realistic top soil conditions. The final stage of the larger project is to integrate a firing mechanism with a drone for automated delivery of seed capsules produced from vacuum forming.

text: Automated aerial seed planting using biodegradable polymers The purpose of the thesis was to undertake a preliminary product design to assess the feasibility of using drone technology to aid reforestation for automated seed planting. This product would be able to increase productivity and reduce labour costs, especially when applied in difficult to reach terrains around New Zealand. Ultimately, the final product would be a weaponised drone or a swarm of drones that can fire plastic seed capsules into soil to a specific depth to prevent predation and ensure optimal germination conditions. The proof of concept hinges on the success of three objectives: Assessing and controlling the capsule’s biodegradability in soil. A method of mass manufacturing projectile seed capsules that can be delivered at high velocity and the ability of it to be fired into soil to a specific depth to ensure safe germination.  

Novatein was blended with poly(butylene adipate terephthalate) (PBAT) to aid sheet extrusion and improve water resistance. Biodegradability was tested by measuring the ability of bacteria and fungi to metabolise the polymer blends into CO2 by enclosing samples in soil at 25 °C. PBAT showed very little biodegradation under these conditions, where approximately 3 % of the theoretical carbon content of the sample was converted to CO2. Novatein reached 20 %, and the blends were intermediate, based on the amount of PBAT present. It was concluded that PBAT can effectively control the rate and extent of biodegradation in blends with Novatein. 

A method for mass manufacturing seed capsules was evaluated by compression moulding spheres to test mouldability and manufacturing lap welded samples to quantify weld strength. Blends of Novatein and PBAT were successfully moulded and welded above the glass transition temperature of the material; optimal parameters were 105 °C with a three minute hold time. Lap welds were tested by varying the compression force and sheet thickness and thereby reducing the weld times to approximately eight seconds. Welded samples were tested for tensile and peel strength, where 0.68 mm thick sheets, welded at 750 N compression force, yielded the highest tensile strength (88 % that of an un-welded samples). Thicker sheets (1.52 mm) welded at 900 N compression force, resulted in the highest peel force. Producing capsules capable of penetrating soil would benefit from thicker sheets using sufficient pressure to prevent peeling at the seam. 

Finally, seed capsule delivery was assessed using empirical modelling in combination with controlled soil conditions. Models created by Young and Lorenz used a dynamic cone penetrometer (DCP) to measure the soil’s penetration resistance to predict the penetration depth of a known projectile. These models were developed for considerably heavier projectiles (> 2.2 kg) and penetration depths much greater than considered here. Considering the DCP measures the soils resistance to penetration at a depth of one meter, a comparison to a 10th scale model was investigated. Contrary to expected, the standard DCP predicted the penetration depth of high velocity projectiles to a reasonably accuracy (~20 %) using two different types of homogenous sand, tested at three moisture contents. The scaled model failed to account for soil types, which was shown to have significant influence during high velocity testing. The work here highlighted the importance of considering realistic forestry soil, despite the accuracy of the prediction in homogenous sand.

Although an integrated product has not been developed, this project has shown that a strategy exists for controlling the rate of biodegradation of Novatein/PBAT. A plausible method for mass manufacturing seed capsules was demonstrated using compression moulding of Novatein blends. Penetration depth was predicted accurately for homogenous soil, this requires further research into applying the model to realistic top soil conditions. The final stage of the larger project is to integrate a firing mechanism with a drone for automated delivery of seed capsules produced from vacuum forming.

year: 2019

title: Large-scale attribute selection using wrappers

authors: Gutlein, Martin

subjects: computer science

abstract: Scheme-specific attribute selection with the wrapper and variants of forward selection is a popular attribute selection technique for classification that yields good results. However, it can run the risk of overfitting because of the extent of the search and the extensive use of internal cross-validation. Moreover, although wrapper evaluators tend to achieve superior accuracy compared to filters, they face a high computational cost. The problems of overfitting and high runtime occur in particular on high-dimensional datasets, like microarray data.
We investigate Linear Forward Selection, a technique to reduce the number of attributes expansions in each forward selection step. Our experiments demonstrate that this approach is faster, finds smaller subsets and can even increase the accuracy compared to standard forward selection. We also investigate a variant that applies explicit subset size determination in forward selection to combat overfitting, where the search is forced to stop at a precomputed “optimal” subset size. We show that this technique reduces subset size while maintaining comparable accuracy.

text: Large-scale attribute selection using wrappers Scheme-specific attribute selection with the wrapper and variants of forward selection is a popular attribute selection technique for classification that yields good results. However, it can run the risk of overfitting because of the extent of the search and the extensive use of internal cross-validation. Moreover, although wrapper evaluators tend to achieve superior accuracy compared to filters, they face a high computational cost. The problems of overfitting and high runtime occur in particular on high-dimensional datasets, like microarray data.
We investigate Linear Forward Selection, a technique to reduce the number of attributes expansions in each forward selection step. Our experiments demonstrate that this approach is faster, finds smaller subsets and can even increase the accuracy compared to standard forward selection. We also investigate a variant that applies explicit subset size determination in forward selection to combat overfitting, where the search is forced to stop at a precomputed “optimal” subset size. We show that this technique reduces subset size while maintaining comparable accuracy.

year: 2009

title: The day ahead

authors: Webber, Warren

abstract: With a professional background in agriculture and veterinary science, and a decade of participation in water quality issues for the Rotorua Lakes catchments, Warren brings an intense personal, but non-vested interest, to issues of nutrient management on the land and in our waterways. Conference management (international and domestic) helps to pay the bills, but voluntary community interests take up much of his time. As an appointee to the Stakeholder Advisory Group (StAG) which considers land management and land use change policy issues on behalf of the Te Arawa Lakes Strategy Group, he is closely involved with the challenges of nutrient allocation and incentives for change.

text: The day ahead With a professional background in agriculture and veterinary science, and a decade of participation in water quality issues for the Rotorua Lakes catchments, Warren brings an intense personal, but non-vested interest, to issues of nutrient management on the land and in our waterways. Conference management (international and domestic) helps to pay the bills, but voluntary community interests take up much of his time. As an appointee to the Stakeholder Advisory Group (StAG) which considers land management and land use change policy issues on behalf of the Te Arawa Lakes Strategy Group, he is closely involved with the challenges of nutrient allocation and incentives for change.

year: 2013