Decoding the effects of drought stress on popcorn (Zea mays var. everta) flowering combining proteomics and physiological analysis.

Under conditions of soil water limitation and adequate irrigation, we conducted an investigation into the growth dynamics, gas exchange performance, and proteomic profiles of two inbred popcorn lines-L71, characterized as drought-tolerant, and L61, identified as drought-sensitive. Our goal was to uncover the mechanisms associated with tolerance to soil water limitation during the flowering. The plants were cultivated until grain filling in a substrate composed of perlite and peat within 150cm long lysimeter, subjected to two water conditions (WC): i) irrigated (WW) at lysimeter capacity (LC - 100%), and ii) water-stressed (WS). Under WS conditions, the plants gradually reached 45% of LC and were maintained at this level for 10 days. Irrespective of the WC, L71 exhibited the highest values of dry biomass in both shoot and root systems, signifying its status as the most robust genotype. The imposed water limitation led to early senescence, chlorophyll degradation, and increased anthocyanin levels, with a more pronounced impact observed in L61. Traits related to gas exchange manifested differences between the lines only under WS conditions. A total of 1838 proteins were identified, with 169 differentially accumulated proteins (DAPs) in the tolerant line and 386 DAPs in the sensitive line. Notably, differences in energy metabolism, photosynthesis, oxidative stress response, and protein synthesis pathways were identified as the key distinctions between L71 and L61. Consequently, our findings offer valuable insights into the alterations in proteomic profiles associated with the adaptation to soil water limitation in popcorn.

Revealing the differential protein profiles behind the nitrogen use efficiency in popcorn (Zea mays var. everta).

We investigated the proteomic profiles of two popcorn inbred lines, P2 (N-efficient and N-responsive) and L80 (N-inefficient and nonresponsive to N), under low (10% of N supply) and high (100% of N supply) nitrogen environments, associated with agronomic- and physiological-related traits to NUE. The comparative proteomic analysis allowed the identification of 79 differentially accumulated proteins (DAPs) in the comparison of high/low N for P2 and 96 DAPs in the comparison of high/low N for L80. The NUE and N uptake efficiency (NUpE) presented high means in P2 in comparison to L80 at both N levels, but the NUE, NUpE, and N utilization efficiency (NUtE) rates decreased in P2 under a high N supply. DAPs involved in energy and carbohydrate metabolism suggested that N regulates enzymes of alternative pathways to adapt to energy shortages and that fructose-bisphosphate aldolase may act as one of the key primary nitrate responsive proteins in P2. Proteins related to ascorbate biosynthesis and nitrogen metabolism increased their regulation in P2, and the interaction of L-ascorbate peroxidase and Fd-NiR may play an important role in the NUE trait. Taken together, our results provide new insights into the proteomic changes taking place in contrasting inbred lines, providing useful information on the genetic improvement of NUE in popcorn.

Driving Sustainable Popcorn Breeding for Drought Tolerance in Brazil.

Drought currently affects several regions worldwide and tends to be more frequent due to climate change. It might compromise food security and the economic structure related to agribusiness. Popcorn has a crucial role in the Brazilian economy, but the cultivars that adapt to water stress, the most prejudicial abiotic stress for crop productivity, are unknown to date. This deficit of popcorn varieties adapted to heat and drought stresses will become more limiting with climate change. Given this scenario, knowing the genetic basis of agronomic traits under stress conditions is essential in promoting crop productivity and plant adaptation to abiotic stresses. Under two contrasting water conditions (WC) and different crop seasons (CS), we aimed to generate information about the combining ability of 10 popcorn progenitors and 15 hybrids through a partial diallel-mating design. The water stress was initiated at the male pre-anthesis stage. Significant genotype*crop seasons (G*CS), genotype*water condition (G*WC), and genotype*crop seasons*water condition (G*CS*WC) interactions were present. Regardless of CS and WC, non-additive effects controlled grain yield (GY), grain number per row (GN), ear length and diameter (ED), and 100-grain weight, while additive effects were present for popping expansion (PE). For each CS, regardless of WC, the cause-effect of GN (2018) and ED (2020) on GY seems to be an opportunity for indirect selection. Utilizing genetically broad-based hybrids is also a good opportunity for obtaining superior genotypes for GY and PE as it is possible to select inbred lines for both of these traits. We recommend the L76 × L61 hybrid for the Brazilian agribusiness context due to its greater productivity and dominance deviations.

Regional Heritability Mapping of Quantitative Trait Loci Controlling Traits Related to Growth and Productivity in Popcorn (Zea mays L.).

The method of regional heritability mapping (RHM) has become an important tool in the identification of quantitative trait loci (QTLs) controlling traits of interest in plants. Here, RHM was first applied in a breeding population of popcorn, to identify the QTLs and candidate genes involved in grain yield, plant height, kernel popping expansion, and first ear height, as well as determining the heritability of each significant genomic region. The study population consisted of 98 S1 families derived from the 9th recurrent selection cycle (C-9) of the open-pollinated variety UENF-14, which were genetically evaluated in two environments (ENV1 and ENV2). Seventeen and five genomic regions were mapped by the RHM method in ENV1 and ENV2, respectively. Subsequent genome-wide analysis based on the reference genome B73 revealed associations with forty-six candidate genes within these genomic regions, some of them are considered to be biologically important due to the proteins that they encode. The results obtained by the RHM method have the potential to contribute to knowledge on the genetic architecture of the growth and yield traits of popcorn, which might be used for marker-assisted selection in breeding programs.

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions.

Understanding the interaction between genotype performance and the target environment is the key to improving genetic gain, particularly in the context of climate change. Wheat production is seriously compromised in agricultural regions affected by water and heat stress, such as the Mediterranean basin. Moreover, wheat production may be also limited by the nitrogen availability in the soil. We have sought to dissect the agronomic and physiological traits related to the performance of 12 high-yield European bread wheat varieties under Mediterranean rainfed conditions and different levels of N fertilization during two contrasting crop seasons. Grain yield was more than two times higher in the first season than the second season and was associated with much greater rainfall and lower temperatures. However, the nitrogen effect was rather minor. Genotypic effects existed for the two seasons. While several of the varieties from central/northern Europe yielded more than those from southern Europe during the optimal season, the opposite trend occurred in the dry season. The varieties from central/northern Europe were associated with delayed phenology and a longer crop cycle, while the varieties from southern Europe were characterized by a shorter crop cycle but comparatively higher duration of the reproductive period, associated with an earlier beginning of stem elongation and a greater number of ears per area. However, some of the cultivars from northern Europe maintained a relatively high yield capacity in both seasons. Thus, KWS Siskin from the UK exhibited intermediate phenology, resulting in a relatively long reproductive period, together with a high green area throughout the crop cycle.

Research advances and applications of biosensing technology for the diagnosis of pathogens in sustainable agriculture.

Plant diseases significantly impact the global economy, and plant pathogenic microorganisms such as nematodes, viruses, bacteria, fungi, and viroids may be the etiology for most infectious diseases. In agriculture, the development of disease-free plants is an important strategy for the determination of the survival and productivity of plants in the field. This article reviews biosensor methods of disease detection that have been used effectively in other fields, and these methods could possibly transform the production methods of the agricultural industry. The precise identification of plant pathogens assists in the assessment of effective management steps for minimization of production loss. The new plant pathogen detection methods include evaluation of signs of disease, detection of cultured organisms, or direct examination of contaminated tissues through molecular and serological techniques. Laboratory-based approaches are costly and time-consuming and require specialized skills. The conclusions of this review also indicate that there is an urgent need for the establishment of a reliable, fast, accurate, responsive, and cost-effective testing method for the detection of field plants at early stages of growth. We also summarized new emerging biosensor technologies, including isothermal amplification, detection of nanomaterials, paper-based techniques, robotics, and lab-on-a-chip analytical devices. However, these constitute novelty in the research and development of approaches for the early diagnosis of pathogens in sustainable agriculture.

Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network.

Genomic selection models were investigated to predict several complex traits in breeding populations of Zea mays L. and Eucalyptus globulus Labill. For this, the following methods of Machine Learning (ML) were implemented: (i) Deep Learning (DL) and (ii) Bayesian Regularized Neural Network (BRNN) both in combination with different hyperparameters. These ML methods were also compared with Genomic Best Linear Unbiased Prediction (GBLUP) and different Bayesian regression models [Bayes A, Bayes B, Bayes Cπ, Bayesian Ridge Regression, Bayesian LASSO, and Reproducing Kernel Hilbert Space (RKHS)]. DL models, using Rectified Linear Units (as the activation function), had higher predictive ability values, which varied from 0.27 (pilodyn penetration of 6 years old eucalypt trees) to 0.78 (flowering-related traits of maize). Moreover, the larger mini-batch size (100%) had a significantly higher predictive ability for wood-related traits than the smaller mini-batch size (10%). On the other hand, in the BRNN method, the architectures of one and two layers that used only the pureline function showed better results of prediction, with values ranging from 0.21 (pilodyn penetration) to 0.71 (flowering traits). A significant increase in the prediction ability was observed for DL in comparison with other methods of genomic prediction (Bayesian alphabet models, GBLUP, RKHS, and BRNN). Another important finding was the usefulness of DL models (through an iterative algorithm) as an SNP detection strategy for genome-wide association studies. The results of this study confirm the importance of DL for genome-wide analyses and crop/tree improvement strategies, which holds promise for accelerating breeding progress.

Comparison of Selection Traits for Effective Popcorn (Zea mays L. var. Everta) Breeding Under Water Limiting Conditions.

Climate change is expected to intensify water restriction to crops, impacting on the yield potential of crops such as popcorn. This work aimed to evaluate the performance of 10 field cultivated popcorn inbred lines during two growing seasons, under well-watered (WW) and water stressed (WS) (ψsoil≥ -1.5 MPa) conditions. Water stress was applied by withholding irrigation in the phenological phase of male pre-anthesis. Additionally, two contrasting inbred lines, P7 (superior line) and L75 (low performer) were compared for grain yield (GY) and expanded popcorn volume (EPV), selected from previous studies, were tested under greenhouse conditions. In the field, no genotype x water condition x crop season (G×WC×CS) interaction was observed, whereas GY (-51%), EPV (-55%) and leaf greenness (SPAD index) measured 17 days after anthesis (DAA) (> -10%) were highly affected by water limitation. In general, root traits (angles, number, and density) presented G×WC×CS interaction, which did not support their use as selection parameters. In relation to leaf senescence, for both WS and WW conditions, the superior inbred lines maintained a stay-green condition (higher SPAD index) until physiological maturity, but maximum SPAD index values were observed later in WW (48.7 by 14 DAA) than in WS (43.9 by 7 DAA). Under both water conditions, negative associations were observed between SPAD index values 15 and 8 days before anthesis DBA), and GY and EPV (r ≥ -0.69), as well as between SPAD index 7, 17, and 22 DAA, and angles of brace root (AB), number of crown roots (NC) and crown root density (CD), in WS (r ≥ -0.69), and AB and CD, in WW (r ≥ -0.70). Lower NC and CD values may allow further root deepening in WS conditions. Under WS P7 maintained higher net photosynthesis values, stomatal conductance, and transpiration, than L75. Additionally, L75 exhibited a lower (i.e., more negative) carbon isotope composition value than P7 under WS, confirming a lower stomatal aperture in L75. In summary, besides leaf greenness, traits related to leaf photosynthetic status, and stomatal conductance were shown to be good indicators of the agronomic performance of popcorn under water constraint.

Thirteen years under arid conditions: exploring marker-trait associations in Eucalyptus cladocalyx for complex traits related to flowering, stem form and growth.

We present an association analysis for seven key traits related to flowering, stem form and growth in Eucalyptus cladocalyx, a tree species suitable for low rainfall sites, using a long-term progeny trial with 49 open-pollinated maternal families in the southern Atacama Desert, Chile. The progeny trial was carried out in an arid environment with a mean annual rainfall of 152 mm. Simple sequence repeats (SSR) from a full consensus map of Eucalyptus were used for genotyping 245 individual trees. Twenty-three significant marker-trait associations were identified, explaining between 5.9 and 23.7% of the phenotypic variance. The marker EMBRA101 located on LG10 at 56.5 cM was concomitantly associated with diameter at breast height and tree height. Nine SSR were significantly associated with stem forking and stem straightness, explaining between 5.9 and 14.8% of the phenotypic variation. To our knowledge, this is the first study reporting a SSR-based association mapping analysis for stem form traits in Eucalyptus. These results provide novel and valuable information for understanding the genetic base of key traits in E. cladocalyx for breeding purposes under arid conditions.