Department of Practical Course Education, Cheongju National University of Education, Cheongju, Republic of Korea.
Department of Agricultural Engineering, National Institute of Agricultural Sciences, Jeonju, Republic of Korea.
PLoS One. 2022 Aug 30;17(8):e0273845. doi: 10.1371/journal.pone.0273845. eCollection 2022.
Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, 'Suziblue' and 'Star', to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf's position and time, whereas 'Star' did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities.
设施栽培已经从温室发展到利用人工智能（AI）的智能农场，人工智能模拟大数据以实现最大产量。然而，智能农场中的人工智能大数据研究还不够完善，作物内部品种之间的差异的影响还不清楚。因此，使用 SAPD 计测试了两个蓝莓品种“苏兹蓝莓”和“星”对光的反应，以证明同一物种内的品种之间的环境反应可能不同。结果表明，基于叶片的位置和时间，这两个品种的 SPAD 值有显著差异，而“星”没有。这表明光的效果取决于品种，这意味着其他性状和其他作物可能表现出类似的差异。这些结果是基于一个简单的实验。然而，足以说明不仅要对每个作物，而且要对每个品种的环境响应进行特征描述，以收集智能农业的数据来提高模型的准确性；从而最大限度地提高这些设施的效率，这一点非常重要。
