The evaluation of a cultivation technology would be more efficient when the technology assessment is based on various approaches like conventional morphological approaches, the use of drone’s normalized difference vegetation index (NDVI) imaging, and participatory plant breeding (PPB). The recent study aimed to assess the effectiveness of the combination of morphological approaches, drone imaging, and participatory plant breeding in selecting the best corn cultivation technology package. This research conducted in a randomized complete block design (RCBD) with one factor from March to December 2021 at the Village Taroang, Takalar Regency, South Sulawesi, Indonesia. The factor is 40 cultivation technology packages. The treatments were replicated three times, thus having 120 experimental units. For plant participation, the investigations were conducted with 56 farmers on their corn fields through quantitative surveys in the targeted area. For NDVI, the observation was recorded 70 days after planting using a DJI Inspire two unmanned aerial vehicles equipped with a multi-spectral camera. Based on the results of the study, the combined strategy of different approaches like morpho-physiological, drone’s NDVI, and participatory plant breeding is found effective in evaluating the corn production technology. The yield, plant height, percentage of net yield, and cob weight were good selection criteria for the morphology approach in evaluating corn cultivation. The NDVI could be recommended in helping the morphology evaluation and PPB, especially in a large-scale evaluation. Based on a combined assessment of the different approaches, the maize cultivar Pioneer-27 combined with ‘Legowo’ spacing technology, NPK fertilizer ratio of 200:100:50, KNO3 at the rate of 25 kg, and application of biofertilizer 'Eco farming' @ 5 cc L-1, was recommended as the best corn production technology package in the Village Taroang, Takalar Regency, South Sulawesi, Indonesia.

Image-based phenotyping in selecting drought- and salinity-tolerant rice lines is a potential approach to complement other selection criteria. This study aimed to determine tolerance response and selection criteria on drought and salinity stresses based on a morphological and image-based phenotyping character. The experiment, set up in a screen house of the Department of Agronomy, Faculty of Agriculture, Hasanuddin University, Indonesia, consisted of a nested randomized complete group design. The nested replication included stressed environments with two factors and three repetitions. The level of environmental stresses comprised the first factor, i.e., normal (without NaCl and PEG), salinity (60 and 120 mM NaCl), drought (10% and 20% PEG), and combination of drought-salinity (10% PEG + 60 mM NaCl). The second factor entailed the rice genotypes. Observations of the morphological and image-based phenotyping characters ensued. The results indicated that salinity stress had a wider diversity than drought stress, while the multiple stresses had a relatively stable variety compared with single stress. Morphological and image-based phenotyping character increased precision in assessing the tolerance or adaptability of rice to drought stress, salinity, and its combination. The morphological characters that can serve as rice selection criteria in a combination of drought-salinity stress included the shoot and root fresh weights and the root length. As for the image-based phenotyping character, the shoot phenotype width can serve as the selection criterion. Image-based phenotyping characters, especially the shoot phenotype area, were recommended as criteria for precise selection in assessing rice genotypes’ potential tolerance and adaptability to drought stress, salinity, and its combinations.