The last decade has seen significant advances in the application of quantitative mass spectrometry-based proteomics technologies to tackle important questions in plant biology. This has included the use of both labelled and label-free quantitative liquid-chromatography mass spectrometry (LC-MS) strategies in model1,2 and non-model plants3. While chemical labelling-based workflows (e.g. iTRAQ and TMT) are generally considered to possess high quantitative accuracy, they nonetheless suffer from ratio distortion and sample interference issues4,5, while being less cost-effective and offering less throughput than label-free approaches. Consequently, label free quantification (LFQ) has been widely used in comparative quantitative experiments profiling the native6 and post-translationally modified (PTM-ome)7,8 proteomes of plants. However, LFQ shotgun proteomics studies in plants have so far, almost universally, used data-dependent acquisition (DDA) for tandem MS (MS/MS) analysis. Here, we systematically compare and benchmark a state-of-the-art DDA LFQ workflow for plants against a new direct data-independent acquisition (direct DIA) method9. Our study demonstrates several advantages of direct DIA and establishes it as the method of choice for quantitative proteomics on plant tissue. We also applied direct DIA to perform a quantitative proteomic comparison of dark and light grown Arabidopsis cell cultures, providing a critical resource for future plant interactome studies using this well-established biochemistry platform.