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University of Technology Sydney (UTS) 2015

Development of new non-destructive imaging techniques for estimating crop growth and nutrient status

Ali, Mahdi Mousa

Titre : Development of new non-destructive imaging techniques for estimating crop growth and nutrient status

Auteur : Ali, Mahdi Mousa

Université de soutenance : University of Technology Sydney (UTS)

Grade : Doctor of Philosophy (PhD) 2015

Résumé partiel
Leaf dimensions and pigments are the important traits in plants that play a key role in estimating light interception, absorption and food production. In predictive research, these parameters are a useful data source for devising crop management techniques such as cultivation, pruning and fertilisation. Destructive and non-destructive techniques are commonly used for estimating crop growth and nutrient status. Although, destructive methods are more accurate, these are expensive, laborious and impracticable for large fields. In contrast, various non-destructive techniques have been developed for predicting crop N requirements that are relatively fast and less expensive. However, lack of consistency in accurately predicting the true N levels of different crop species under variable environments require further exploration of this area. In the present study, a new and relatively more efficient technique has been proposed for measuring leaf dimensions, chlorophyll, and N and phosphorus (P) content. In the initial study, leaf images from a range of plant species were collected using a handheld portable digital scanner (Pico Life). Edge detection and filtering algorithms were applied to identify the leaf section of the image against the background. Data of forty leaves that vary in shape and size (from grasses to broad leaf plant species) were collected and processed using a new algorithm as well as the Li-Cor 3100. Data indicated high accuracy of the proposed algorithm for estimating leaf area, length, width and perimeter. It was verified by a strong correlation (R²=0.999) between leaf area measured by Li-Cor 3100 and by digital scanner. After successful application of the digital scanner for estimating leaf size and dimensions, the images collected by this scanner were used for predicting chlorophyll, P and N content of tomato, broccoli and lettuce leaves. The plants were grown under controlled conditions using nutrient solution and at early reproductive growth (after 8 weeks of growth) these were exposed to various N levels for seven weeks.

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Page publiée le 19 juillet 2017