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The identification of traits associated with drought tolerance in popcorn is a contribution to support selection of superior plants under soil water deficit. The objective of this study was to choose morphological traits and the leaf greenness index, measured on different dates, to estimate grain yield (GY) and popping expansion (PE), evaluated in a set of 20 popcorn lines with different genealogies, estimated by multiple regression models. The variables were divided into three groups: morpho-agronomic traits—100-grain weight (GW), prolificacy (PR), tassel length (TL), number of tassel branches, anthesis-silking interval, leaf angle (FA) and leaf rolling (FB), variables related to the intensity of leaf greenness during the grain-filling period, at the leaf level, measured by a portable chlorophyll meter (SPAD) and at the canopy level, calculated as the normalized difference vegetation index (NDVI). The inbred lines were cultivated under two water conditions: well-watered (WW), maintained at field capacity, and water stress (WS), for which irrigation was stopped before male flowering. The traits GY (55%) and PE (28%) were most affected by water restriction. Among the morpho-agronomic traits, GW and PR were markedly reduced (&gt, 10%). Under dry conditions, the FA in relation to the plant stalk tended to be wider, the FB curvature greater and leaf senescence accelerated (&gt, 15% at 22 days after male flowering). The use of multiple regression for the selection of predictive traits proved to be a useful tool for the identification of groups of adequate traits to efficiently predict the economically most important features of popcorn (GY and PE). The SPAD index measured 17 days after male flowering proved useful to select indirectly for GY, while, among the morphological traits, TL stood out for the same purpose. Of all traits, PR was most strongly related with PE under WS, indicating its use in breeding programs. The exploitation of these traits by indirect selection is expected to induce increments in GY and PE.

Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.

Maize tassels play a critical role in plant growth and yield. Extensive RGB images obtained using unmanned aerial vehicle (UAV) and the prevalence of deep learning provide a chance to improve the accuracy of detecting maize tassels. We used images from UAV, a mobile phone, and the Maize Tassel Counting dataset (MTC) to test the performance of faster region-based convolutional neural network (Faster R-CNN) with residual neural network (ResNet) and a visual geometry group neural network (VGGNet). The results showed that the ResNet, as the feature extraction network, was better than the VGGNet for detecting maize tassels from UAV images with 600 × 600 resolution. The prediction accuracy ranged from 87.94% to 94.99%. However, the prediction accuracy was less than 87.27% from the UAV images with 5280 × 2970 resolution. We modified the anchor size to [852, 1282, 2562] in the region proposal network according to the width and height of pixel distribution to improve detection accuracy up to 89.96%. The accuracy reached up to 95.95% for mobile phone images. Then, we compared our trained model with TasselNet without training their datasets. The average difference of tassel number was 1.4 between the calculations with 40 images for the two methods. In the future, we could further improve the performance of the models by enlarging datasets and calculating other tassel traits such as the length, width, diameter, perimeter, and the branch number of the maize tassels.

Medium and small seed companies require information on maize parental seed production to make rational choices on what germplasm to introduce into their seed and breeding pipelines. The objective of this study was to generate public data on the appropriate hybrid seed production information of five female lines (T21, T26, T28, T33 and T38) and one line (T10) as a male hybrid parent. The effect of female and male sowing date and sowing density on hybrid seed production characteristics including flowering time, flowering duration, distance between tassel and stigmas and effective seed yield was determined. Recommendations to stagger male and female sowing to achieve flowering synchrony for the hybrid parents were complemented with data of seedling growth stages. The results were similar for T21, T26, T28, and T38, sowing the female and T10 on a row proportion of 4 females:1 male, and on a second date, when the coleoptiles of the female plants are halfway to emerge, sowing the missing male row to complete the 4:2 ratio. T33 is a late flowering line, therefore it is desirable to sow T33 first and T10 five days later, or when the T33 coleoptile begins to emerge. Plant densities did not cause differences in most plant characteristics. Line T21 showed good female parental traits. While this study provides a knowledge framework for seed production technology for these single cross hybrids, data specific to seed production regions need to be generated by seed companies to define the best regimes for hybrid production.

During the process of maize seed production, in order to ensure the genetic purity of parental forms of hybrid maize, an important work performed is the removal of male inflorescences from plants on mother rows. Hand detasseling has high precision but is labor-intensive. Mechanical detasseling offers the possibility to cover large acreages in a short period of time, but the number of leaves removed has a varying influence on plant performance and seed yield. The aim of this study was to simulate three types of damages on plants similar to those induced through mechanical detasseling and to assess the effects for five inbred lines during the course of three years. Results show that when tassels alone were removed, the average seed yield decreased an average of 4&ndash, 21%. When two leaves were removed with the tassel, yield decreased an average of 22&ndash, 31%, while when plants were cut above the main ear, seed yield decreased an average of 31&ndash, 66%. Environmental conditions influenced seed yield, especially high temperatures during flowering. Yield response to tassel and leaves removal varied between the inbred lines. Genotype controls maize ear and kernel characters, while environmental factors exercise a strong influence on seed yield, due to the succession of years with contrasting weather conditions in a key phenophase. Within the trend of full mechanization in agriculture, identification of inbred lines that cope better with plant damage can assist in optimizing seed production.

Corn tassel is a by-product from hybrid corn seed production and a new source of phytochemicals including compounds with antioxidant activity. Four tassel development stages were evaluated in eight commercial corn varieties. Corn varieties and tassel developmental stages showed significant variations (P0.01) for all parameters. Total phenolic content and antioxidant activity were highest in field corn. KGW1, a purple waxy variety, had the highest anthocyanin content and carotenoid content at tassel development stages at 50% and 75% of pollen shed, whereas the tassel developmental stages at the 1st day of pollen shed and 50% of pollen shed had the highest of anthocyanin yield and carotenoid yield. The most suitable time for tassel harvest should be between the 1st day of pollen shed to 50% of pollen shed. Phytochemicals and antioxidants that are extracted from corn tassel can be used as a functional food supplement, natural pharmaceuticals and cosmetic products.

Corn tassel is a valuable co-product and an excellent source of phytochemicals with bioactive properties. The information on the genetic diversity in the tassel properties of waxy corn germplasm is important for creating new varieties that can have the potential for the commercial production of tassels as a co-product. Therefore, the objective of this study was to evaluate the potential of corn tassels in a set of waxy corn germplasm for the extraction of phenolic compounds with an antioxidant activity. The experiment was carried out under field conditions in the rainy season 2017 and the dry season 2017/2018. Fifty waxy corn genotypes were evaluated. Data were collected for the total anthocyanin content (TAC), total phenolic content (TPC) and the antioxidant activity was determined by the 2,2-diphenyl&minus, 1-picrylhydrazyl (DPPH) radical scavenging activity and Trolox equivalent antioxidant capacity (TEAC) assays. The season (S) had small effect on all of the parameters, accounting for 0.2&ndash, 8.7% of the total variance. The genotype (G) was the largest variance component in the TAC and DPPH radical scavenging activity, accounting for 83.5&ndash, 97.5% of the total variance. The G and S &times, G interaction contributed approximately equally to the total variance in the TPC and TEAC. Based on the TAC, TPC and antioxidant capacity variation, the genotypes were classified into seven groups. The tassels of corn genotypes belonging to three of these clusters (clusters E, F and G) had high levels of phytochemicals along with an antioxidant capacity. A significant correlation coefficient was found between the TAC and DPPH (r = 0.70 **). The TPC showed a moderate relationship with the DPPH and TEAC assays (r = 0.60 ** and 0.76 **, respectively). The information obtained from this study can be used for germplasm management and waxy corn breeding for enhancing levels of bioactive properties in waxy corn tassels.

Corn tassel is a byproduct from hybrid corn seed production. It is also a new source of phytochemicals, including compounds with antioxidant activity. The aim of this study was to evaluate the phytochemical content and antioxidant potential of different corn tassel development stages. A 4 &times, 8 factorial experiment consisting of four tassel development stages and eight commercial corn varieties was carried out with a randomized complete block design with three replications. Data were collected for tassel weight, concentration and yield of total phenolics, total anthocyanin concentration, total carotenoid concentration, and antioxidant activity, as determined by the 2,2-diphenyl-1-picrylhydrazyl(DPPH&bull, ) radical scavenging assay and Trolox equivalent antioxidant capacity(TEAC) assays. Corn varieties and tassel developmental stages showed significant variations (p &le, 0.01) in all parameters. P4546 presented the best variety for the total phenolic content (15.8 mg GAE/g DW sample), whereas Hibrix3 had the highest phenolic yield (6.78 kg GAE/ha). KGW1, a purple waxy variety, had the highest anthocyanin content (1528.0 &micro, g CGE/g DW sample), anthocyanin yield (753.0 g CGE/ha), carotenoid content (74.9 &micro, g/g DW sample), and carotenoid yield (53.7 g/ha). P4546 had the highest antioxidant activity: 92.4% for DPPH&bull, and 76.1 &micro, mol TE/g DW sample for the TEAC assay, respectively. The most appropriate time for tassel harvest to ensure the production of phytochemicals with high antioxidant activity should be from the 1st day of pollen shed until 50% of pollen shed. Phytochemicals and antioxidants that are extracted from corn tassel can be used as a functional food supplement, as natural pharmaceuticals, and in cosmetic products.