Accurate, high-resolution maps of for crop growth monitoring are strongly needed by precision agriculture. The information source for such maps has been supplied by satellite-borne radars and optical sensors, and airborne and drone-borne optical sensors. This article presents a novel methodology for obtaining growth deficit maps with an accuracy down to 5 cm and a spatial resolution of 1 m, using differential synthetic aperture radar interferometry (DInSAR). Results are presented with measurements of a drone-borne DInSAR operating in three bands—P, L and C. The decorrelation time of L-band for coffee, sugar cane and corn, and the feasibility for growth deficit maps generation are discussed. A model is presented for evaluating the growth deficit of a corn crop in L-band, starting with 50 cm height. This work shows that the drone-borne DInSAR has potential as a complementary tool for precision agriculture.

This article presents a novel method for predicting the sugarcane harvesting date and productivity using a three-band imaging radar. Taking advantage of working with a multi-band radar, this system was employed to estimate the above-ground biomass (AGB), achieving a root-mean-square error (RMSE) of 2 kg m⁻² in sugarcane crops, which is an unprecedented result compared with other works based on the Synthetic Aperture Radar (SAR) system. By correlating the field measurements of the ripening index (RI) with the AGB measurements by radar, an indirect estimate of the RI by the radar is obtained. It is observed that the AGB reaches its maximum approximately 280 days after planting and the maximum RI, which defines the harvesting date, approximately 360 days after planting for the species IACSP97-4039. Starting from an AGB map collected by the radar, it is then possible to predict the harvesting date and the corresponding productivity with competitive average errors of 8 days and 10.7%, respectively, with three months in advance, whereas typical methods employed on a test site achieve an average error of 30 days with three months in advance. To the best of our knowledge, it is the first time that a multi-band radar is employed for productivity prediction in sugarcane crops.

Screen filters are widely used to retain suspended solids. Their performance depends not only on the nominal aperture size but also on the structural characteristics of the filter element, including material properties, weave pattern, and filtration rate. Although manufacturers typically specify filtration grade using mesh size or micron rating, these nominal values sometimes fail to reflect actual retention efficiency under field conditions. This study evaluated how filtration rate influences the retention efficiency of inorganic particles in eleven woven screen filter elements with different materials and configurations. Tests were conducted under two filtration rates and using particles of different size classes to determine the actual filtration threshold. The removal efficiency was determined by measuring total suspended solids (TSS). Eight of the eleven filters achieved more than 85% efficiency for at least one particle class, while three failed to meet this criterion. Higher filtration rates tended to reduce particle retention, particularly in synthetic filters. Nylon and polypropylene elements often exceeded their nominal filtration grades but were more sensitive to flow variations. Stainless steel filters exhibited consistent performance aligned with specifications. The findings emphasize the importance of experimental validation and support more informed filter selection based on particle size and hydraulic operating conditions.