Gustavo Costa Rodrigues

Inexpensive biological tests for soil calcium deficiency and aluminum toxicity

Two relatively simple procedures based on 4-day seedling growth were developed for identifying soil calcium (Ca) deficiency and/or aluminum (Al) toxicity. Test A uses any large-seeded cultivar that a farmer might consider planting and reveals whether the cultivar will suffer from Ca deficiency by comparing root growth in untreated soil to that in soil receiving a minimal Ca addition (0.1 meq.100mL−1 soil), sufficient to eliminate possible deficiency. Al toxicity is detected by comparing root growth in a sample receiving the minimal Ca treatment with growth in the soil treated with enough lime to neutralize exchangeable Al. In test B, potential Al toxicity problems are detected for any widely-grown standard crop by comparing its growth with that of a different, Al-tolerant variety on soil samples receiving 0.1 meq.100mL−1 Ca. With this test Ca deficiency in the untreated sample is detected by an increase in root growth of the Al-tolerant variety resulting from a small addition of Ca. The tests agreed with diagnoses made by standard chemical methods in about 84% of the cases examined. The proposed tests can be carried out using simple, easily-available materials without the necessity of sending soils to an analytical laboratory.

Identification of candidate genes for drought tolerance in coffee by high-throughput sequencing in the shoot apex of different Coffea arabica cultivars

BackgroundDrought is a widespread limiting factor in coffee plants. It affects plant development, fruit production, bean development and consequently beverage quality. Genetic diversity for drought tolerance exists within the coffee genus. However, the molecular mechanisms underlying the adaptation of coffee plants to drought are largely unknown. In this study, we compared the molecular responses to drought in two commercial cultivars (IAPAR59, drought-tolerant and Rubi, drought-susceptible) of Coffea arabica grown in the field under control (irrigation) and drought conditions using the pyrosequencing of RNA extracted from shoot apices and analysing the expression of 38 candidate genes.ResultsPyrosequencing from shoot apices generated a total of 34.7 Mbp and 535,544 reads enabling the identification of 43,087 clusters (41,512 contigs and 1,575 singletons). These data included 17,719 clusters (16,238 contigs and 1,575 singletons) exclusively from 454 sequencing reads, along with 25,368 hybrid clusters assembled with 454 sequences. The comparison of DNA libraries identified new candidate genes (n = 20) presenting differential expression between IAPAR59 and Rubi and/or drought conditions. Their expression was monitored in plagiotropic buds, together with those of other (n = 18) candidates genes. Under drought conditions, up-regulated expression was observed in IAPAR59 but not in Rubi for CaSTK1 (protein kinase), CaSAMT1 (SAM-dependent methyltransferase), CaSLP1 (plant development) and CaMAS1 (ABA biosynthesis). Interestingly, the expression of lipid-transfer protein (nsLTP) genes was also highly up-regulated under drought conditions in IAPAR59. This may have been related to the thicker cuticle observed on the abaxial leaf surface in IAPAR59 compared to Rubi.ConclusionsThe full transcriptome assembly of C. arabica, followed by functional annotation, enabled us to identify differentially expressed genes related to drought conditions. Using these data, candidate genes were selected and their differential expression profiles were confirmed by qPCR experiments in plagiotropic buds of IAPAR59 and Rubi under drought conditions. As regards the genes up-regulated under drought conditions, specifically in the drought-tolerant IAPAR59, several corresponded to orphan genes but also to genes coding proteins involved in signal transduction pathways, as well as ABA and lipid metabolism, for example. The identification of these genes should help advance our understanding of the genetic determinism of drought tolerance in coffee.

Regimes hídricos e doses de fósforo em cafeeiro

This work aimed to study the vegetative and reproductive growth and yield of coffee plants under three water regimes and four phosphorus fertilization doses, on second year after pruning on cerrado soil. The cultivar used was Catuai Rubi, MG 1192, Coffea arabica L. with 7,143 plants ha-1. Water regimes were: all year round irrigation (I); after June 24th, 2007, irrigation was stopped for 70 days (SI70) and for 109 days (SI109). Treatments SI70 e SI109 were interrupted with a rainfall of 12 mm (October 1st, 2007), which visually caused flowering initiation. The four phosphorus doses were: 0 (P0), 100 (P100), 200 (P200) e 400 (P400) kg of P2O5 ha-1. The experiment was arranged in randomized complete block design for water regime with phosphorus doses as split plot and three replications. The highest doses of phosphorus (P200) and (P400) provided increases in branch length, leaf area, number of fruits and grain yield. Water regimes SI70 and SI109 provided higher cherry fruit percentage and the highest and lowest grain yield, respectively.

3D Plant Modeling: Localization, Mapping and Segmentation for Plant Phenotyping Using a Single Hand-held Camera

Functional-structural modeling and high-throughput phenomics demand tools for 3D measurements of plants. In this work, structure from motion is employed to estimate the position of a hand-held camera, moving around plants, and to recover a sparse 3D point cloud sampling the plants’ surfaces. Multiple-view stereo is employed to extend the sparse model to a dense 3D point cloud. The model is automatically segmented by spectral clustering, properly separating the plant’s leaves whose surfaces are estimated by fitting trimmed B-splines to their 3D points. These models are accurate snapshots for the aerial part of the plants at the image acquisition moment and allow the measurement of different features of the specimen phenotype. Such state-of-the-art computer vision techniques are able to produce accurate 3D models for plants using data from a single free moving camera, properly handling occlusions and diversity in size and structure for specimens presenting sparse canopies. A data set formed by the input images and the resulting camera poses and 3D points clouds is available, including data for sunflower and soybean specimens.

Flexible three-dimensional modeling of plants using low- resolution cameras and visual odometry

The three-dimensional reconstruction of plants using computer vision methods is a promising alternative to non-destructive metrology in plant phenotyping. However, diversity in plants form and size, different surrounding environments (laboratory, greenhouse or field), and occlusions impose challenging issues. We propose the use of state-of-the-art methods for visual odometry to accurately recover camera pose and preliminary three-dimensional models on image acquisition time. Specimens of maize and sunflower were imaged using a single free-moving camera and a software tool with visual odometry capabilities. Multiple-view stereo was employed to produce dense point clouds sampling the plant surfaces. The produced three-dimensional models are accurate snapshots of the shoot state and plant measurements can be recovered in a non-invasive way. The results show a free-moving low-resolution camera is able to handle occlusions and variations in plant size and form, allowing the reconstruction of different species, and specimens in different stages of development. It is also a cheap and flexible method, suitable for different phenotyping needs. Plant traits were computed from the point clouds and compared to manually measured reference, showing millimeter accuracy. All data, including images, camera calibration, pose, and three-dimensional models are publicly available.