Search

The advancement of digital agriculture combined with computational tools and Unmanned Aerial Vehicles (UAVs) has opened the way to large-scale data collection for the calculation of vegetation indices (VIs). These vegetation indexes (VIs) are useful for agricultural monitoring, as they highlight the inherent characteristics of vegetation and optimize the spatial and temporal evaluation of different crops. The experiment tested three coffee genotypes (Catuaí 62, E237 and Iapar 59) under five water regimes: (1) FI 100 (year-round irrigation with 100% replacement of evapotranspiration), (2) FI 50 (year-round irrigation with 50% evapotranspiration replacement), (3) WD 100 (no irrigation from June to September (dry season) and, thereafter, 100% evapotranspiration replacement), (4) WD 50 (no irrigation from June to September (water stress) and, thereafter, 50% evapotranspiration replacement) and (5) rainfed (no irrigation during the year). The irrigated treatments were watered with irrigation and precipitation. Most indices were highest in response to full irrigation (FI 100). The values of the NDVI ranged from 0.87 to 0.58 and the SAVI from 0.65 to 0.38, and the values of these indices were lowest for genotype E237 in the rainfed areas. The indices NDVI, OSAVI, MCARI, NDRE and GDVI were positively correlated very strongly with photosynthesis (A) and strongly with transpiration (E) of the coffee trees. On the other hand, temperature-based indices, such as canopy temperature and the TCARI index correlated negatively with A, E and stomatal conductance (gs). Under full irrigation, the tested genotypes did not differ between the years of evaluation. Overall, the index values of Iapar 59 exceeded those of the other genotypes. The use of VIs to evaluate coffee tree performance under different water managements proved efficient in discriminating the best genotypes and optimal water conditions for each genotype. Given the economic importance of coffee as a crop and its susceptibility to extreme events such as drought, this study provides insights that facilitate the optimization of productivity and resilience of plantations under variable climatic conditions.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, specifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irrigation system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes), and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; and TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices, and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE, and GNDVI had higher yield and morphophysiological measurement correlations. The drought resistance index indicated that genotypes Aliança, BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

Future predictions due to climate change are of decreases in rainfall and longer drought periods. The search for new tolerant crops is an important strategy. The objective of this study was to evaluate the effect of water stress on the physiology and productivity of crops with potential for growing in the off-season period in the Cerrado, and evaluate correlations with the temperature of the canopy obtained by means of thermography. The experiment was conducted under field conditions, with experimental design in randomized blocks, in a split-plot scheme and four replications. The plots were: common bean ( Phaseolus vulgaris) ; amaranth ( Amaranthus cruentus ); quinoa ( Chenopodium quinoa ); and buckwheat ( Fagopyrum esculentum ). The subplots were composed of four water regimes: maximum water regime (WR 535 mm), high-availability regime (WR 410 mm), off-season water regime (WR 304 mm) and severe water regime (WR 187 mm). Under WR 304 mm, the internal concentration of CO 2 and photosynthesis were reduced by less than 10% in amaranth. Common bean and buckwheat reduced 85% in photosynthesis. The reduction in water availability increased the canopy temperature in the four crops and, in general, common bean was the most sensitive species, while quinoa had the lowest canopy temperatures. Furthermore, canopy temperature correlated negatively with grain yield, biomass yield and gas exchange across all plant species, thus thermal imaging of the canopy represents a promising tool for monitoring crop productivity for farmers, For the identification of crops with high water use management for research.

Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean ( Glycine max L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought.

Quinoa stands out as an excellent crop in the Cerrado region for cultivation in the off-season or irrigated winter season. Here, we tested the effects of different water regimes on the agronomic characteristics, physiology, and grain quality of different elite quinoa genotypes under field conditions. The experiment was conducted under field conditions at Embrapa Cerrados (Planaltina, DF, Brazil). The experimental design was in randomized blocks, in a split-plot scheme, with four replications. The plots were composed of 18 quinoa genotypes and modified BRS Piabiru (the currently used genotype), and the split-plots were divided into 4 different water regimes. The following variables were evaluated: productivity and productivity per unit of applied water (PUAA), plant height, flavonoids, anthocyanins, gas exchange, chlorophyll, leaf proline, and relative water content. Our results showed that water regimes between 309 and 389 mm can be recommended for quinoa in the Cerrado region. CPAC6 and CPAC13 presented the highest yield and PUAA under high and intermediate WRs, and hence were the most suitable for winter growth under irrigation. CPAC17 is most suitable for off-season growth under rainfed conditions, as it presented the highest PUAA under the low WRs (247 and 150). CPAC9 stood out in terms of accumulation of flavonoids and anthocyanins in all WRs. Physiological analyses revealed different responses of the genotypes to water restriction, together with symptoms of stress under lower water regimes. Our study reinforces the importance of detailed analyses of the relationship between productivity, physiology, and water use when choosing genotypes for planting and harvest in different seasons.

Background: A major limiting factor for plant growth is the aluminum (Al) toxicity in acidic soils, especially in tropical regions. The exclusion of Al from the root apex through root exudation of organic acids such as malate and citrate is one of the most ubiquitous tolerance mechanisms in the plant kingdom. Two families of anion channels that confer Al tolerance are well described in the literature, ALMT and MATE family., Results: In this study, sugarcane plants constitutively overexpressing the Sorghum bicolor MATE gene (SbMATE) showed improved tolerance to Al when compared to non-transgenic (NT) plants, characterized by sustained root growth and exclusion of aluminum from the root apex based on the result obtained with hematoxylin staining. In addition, genome-wide analysis of the recently released sugarcane genome identified 11 ALMT genes and molecular studies showed potential new targets for aluminum tolerance., Conclusions: Our results indicate that the transgenic plants overexpressing the Sorghum bicolor MATE has an improved tolerance to Al. The expression profile of ALMT genes revels potential candidate genes to be used has an alternative for agricultural expansion in Brazil and other areas with aluminum toxicity in poor and acid soils.

The feasibility of thermography as a technique for plant screening aiming at drought-tolerance has been proven by its relationship with gas exchange, biomass, and yield. In this study, unlike most of the previous, thermography was applied for phenotyping contrasting maize genotypes whose classification for drought tolerance had already been established in the field. Our objective was to determine whether thermography-based classification would discriminate the maize genotypes in a similar way as the field selection in which just grain yield was taken into account as a criterion. We evaluated gas exchange, daily water consumption, leaf relative water content, aboveground biomass, and grain yield. Indeed, the screening of maize genotypes based on canopy temperature showed similar results to traditional methods. Nevertheless, canopy temperature only partially reflected gas exchange rates and daily water consumption in plants under drought. Part of the explanation may lie in the changes that drought had caused in plant leaves and canopy structure, altering absorption and dissipation of energy, photosynthesis, transpiration, and partitioning rates. Accordingly, although there was a negative relationship between grain yield and plant canopy temperature, it does not necessarily mean that plants whose canopies were maintained cooler under drought achieved the highest yield.

Sugarcane (Saccharum spp.) is a monocotyledonous semi-perennial C4 grass of the Poaceae family. Its capacity to accumulate high content of sucrose and biomass makes it one of the most important crops for sugar and biofuel production. Conventional methods of sugarcane breeding have shown several limitations due to its complex polyploid and aneuploid genome. However, improvement by biotechnological engineering is currently the most promising alternative to introduce economically important traits. In this work, we present an improved protocol for Agrobacterium tumefaciens-mediated transformation of commercial sugarcane hybrids using immature top stalk-derived embryogenic callus cultures. The callus cultures are transformed with preconditioned A. tumefaciens carrying a binary vector that encodes expression cassettes for a gene of interest and the bialaphos resistance gene (bar confers resistance to glufosinate-ammonium herbicide). This protocol has been used to successfully transform a commercial sugarcane cultivar, SP80-3280, highlighting: (i) reduced recalcitrance and oxidation; (ii) high yield of embryogenic callus; (iii) improved selection; and (iv) shoot regeneration and rooting of the transformed plants. Altogether, these improvements generated a transformation efficiency of 2.2%. This protocol provides a reliable tool for a routine procedure for sugarcane improvement by genetic engineering. © 2017 by John Wiley & Sons, Inc., (Copyright © 2017 John Wiley & Sons, Inc.)

Background: Photosynthesis can be roughly separated into biochemical and photochemical processes. Both are affected by drought and can be assessed by non-invasive standard methods. Gas exchange, which mainly assesses the first process, has well-defined protocols. It is considered a standard method for evaluation of plant responses to drought. Under such stress, assessment of photochemical apparatus by chlorophyll fluorescence needs improvement to become faster and reproducible, especially in growing plants under field conditions. For this, we developed a protocol based on chlorophyll fluorescence imaging, using a rapid light curve approach., Results: Almost all parameters obtained by rapid light curves have shown statistical differences between control and drought stressed maize plants. However, most of them were affected by induction processes, relaxation rate, and/or differences in chlorophyll content; while they all were influenced by actinic light intensity on each light step of light curve. Only the normalized parameters related to photochemical and non-photochemical quenching were strongly correlated with data obtained by gas exchange, but only from the light step in which the linear electron flow reached saturation., Conclusions: The procedure developed in this study for discrimination of plant responses to water deficit stress proved to be as fast, efficient and reliable as the standard technique of gas exchange in order to discriminate the responses of maize genotypes to drought. However, unlike that, there is no need to perform daily and time consuming calibration routines. Moreover, plant acclimation to the dark is not required. The protocol can be applied to plants growing in both controlled conditions and full sunlight in the field. In addition, it generates parameters in a fast and accurate measurement process, which enables evaluating several plants in a short period of time.