Remote Sensing on Alfalfa as an Approach to Optimize Production Outcomes: A Review of Evidence and Directions for Future Assessments

Alfalfa (Medicago sativa L.) is one of the most relevant forage crops due to its importance for livestock. Timely harvesting critical secure adequate quality. However, farmers face challenges not only decide optimal time but predict optimum levels both production and Fortunately, remote sensing technologies can significantly contribute obtaining quality insights, providing scalability, supporting complex farming decision-making. Therefore, we aim develop a systematic review current scientific literature identify status research in alfalfa evaluate new perspectives enhancing prediction biomass (herein defined as crude protein fibers) alfalfa. Twelve papers were included database from total 198 studies initial screening process. The main findings (i) more than two-thirds focused on predicting biomass; (ii) half used terrestrial platforms, with 33% using drones 17% satellite sensing; (iii) no have satellites assessed traits; (iv) improved estimations obtained when data was combined environmental information; (v) direct relationship between quality, modeling them algorithmically improves accuracy estimation well; (vi) spectral wavelengths, dry better estimated regions near 398, 551, 670, 730, 780, 865, 1077 nm, wet 478, 631, 834, 933, 1034, 1538 traits identified narrow very specific wavelengths (e.g., 461, 667, 712, nm). Our might serve foundation guide further development handheld sensors assessing