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This paper examines the prioritization of management factors by farmers that lead to the success of their farm business. The research also examines the heterogeneity of producer prioritization of different success strategies. Using a hierarchical clustering approach, we found that each farmer group prioritizes either managing costs, managing output...
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This paper examines the prioritization of management factors by farmers that lead to the success of their farm business. The research also examines the heterogeneity of producer prioritization of different success strategies. Using a hierarchical clustering approach, we found that each farmer group prioritizes either managing costs, managing output...
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... It does not require any prior information of the number of clusters to be set while performing with the algorithm (Theodoridis and Koutroumbas, 2009). In addition, it is easy to implement, less complex, and often gives best results in some cases and can be used to rank the observations of multiple parameters comprehensively compared to the other clustering techniques (Etumnu and Gray, 2018;Klikocka and Tatarczak, 2015;Odong et al., 2011;Stefano and Arturo, 2020;Theodoridis and Koutroumbas, 2009;Wittek, 2014). However, sometimes it is difficult to make corrections after the splitting and/or merging decisions have made by the algorithm of the hierarchical clustering and often it is sensitive to outliers in case of multi-dimensional and big dataset (Bhagat et al., 2016). ...
Sodicity is a major soil constraint in many arid and semi-arid regions worldwide, including Australia, which adversely affects the ability of crops to take up water and nutrients from the soil, reducing yield. Reliable methods and tools are required for appropriate selection of traits, may provide a better understanding of crop responses to multiple stresses, especially in sodic soil. A novel strategy was developed using unmanned aerial vehicle (UAV)-thermal imaging and agglomerative hierarchical clustering-based techniques to evaluate and rank the physiological performance of 18 contrasting wheat genotypes grown on a moderately sodic and a highly sodic soil in north-eastern Australia. We obtained UAV-thermal imaging data at different times of the day (9:30, 12:00, and 15:00 hrs) close to flowering stage. Crop biophysical parameters (Leaf potassium concentration, normalized difference vegetation index, crop water uptake, stomatal conductance, plant moisture content, and aboveground biomass) were measured at close to flowering by destructive plant sampling and ground-based proximal sensing and yield was machine harvested at maturity. Canopy temperatures derived from thermal imagery between 28.9 and 35.4 °C were observed at the moderately sodic site, and between 36.2 and 41.0 °C at the highly sodic site from 9:30 to 15:00 hrs. Canopy temperature was consistently higher than corresponding ambient air temperatures indicating plant water stress at both sites. While the air temperature was not significantly different (p > 0.05) between the two sites, canopy temperature was significantly higher (p < 0.01) on highly sodic soil compared to moderately sodic soil, indicating greater water stress at the highly sodic site. This difference was most likely due to the adverse impacts of sodic soil constraints and not primarily due to environmental variations. Hence, our study revealed that sodic soil constraints can intensify plant water stress. Statistical analysis between canopy temperature (9:30, 12:00, and 15:00 hrs) and crop biophysical parameters showed close negative correlations at both moderately sodic (R² = 0.54 to 0.83) and highly sodic (R² = 0.30 to 0.89) sites. A closer correlation was observed at 15:00 hrs for both sites. Thus, high-resolution UAV-thermal imaging has potential to detect water-stressed plants on sodic soil. Agglomerative hierarchical clustering was used as an unsupervised machine learning tool for ranking of physiological performance of wheat genotypes. Results suggest that UAV-thermal imaging and AHC techniques can discriminate cultivars tolerant to sodicity. The study improves our understanding of crop physiological behaviour and can assist farmers in selection of water stress tolerant genotypes to sustain food security in sodic soil under water-limited environments.
