Factors underlying the prevalence of Pythium infection of corn seeds following seed treatment application of tebuconazole

Microbial communities are essential for soil health, but fungicide application may have significant effects on their structure. It is difficult to predict whether non-target pathogens of applied fungicides in the soil will cause crop damage. Tebuconazole is a triazole fungicide that can be used as a seed treatment and thereby introduced to the soil. However, seed-applied tebuconazole has a potential risk of causing poor emergence of corn (Zea mays) seedlings. Using soil with a history of poor corn seedling emergence, we demonstrate through TA-cloning and isolation that the poor emergence of corn seedlings from tebuconazole-coated corn seeds was primarily due to infection by surviving soil pathogens, specifically Pythium species that are not targeted by tebuconazole, rather than the phytotoxic effects of tebuconazole. Bioassay tests on tebuconazole amended media showed that tebuconazole can suppress soil fungi while allowing Pythium to grow. Pythium species primarily contributing to the corn seed rot were more pathogenic at cooler temperatures. Furthermore, the non-target biocontrol agent of Trichoderma spp. was strongly inhibited by tebuconazole. Taken together, the non-target effects of tebuconazole are likely not significant under favorable plant growing conditions, but are considerable due to low-temperature stress.

Farmer response and financial feasibility of corn seed production in Southeast Sulawesi

To support the growth and development of corn in Southeast Sulawesi, information of farmer response and financial feasibility of corn seed production in South East Sulawesi are needed. The paper aims to determine farmers’ response and financial feasibility of corn seed production in Southeast Sulawesi, The results of this study are expected to be input for local governments in developing community-based seed breeders and can be useful for corn seedling businesses. The study was conducted in marc 2017 in Pangan Jaya Village, Lainea District, Konawe Selatan Regency, Southeast Sulawesi Province. The study was carried out by involving 20 farmers, 10 people for the production of corn seed production technology and 10 non-cooperator farmers who carried out according to the patterns and habits of farmers (feed corn production).. The data collected consists of (1) corn seed production data based on the results of corn seed reall production (2) farmer and non-breeder farm input data, consisting of expenditures for the purchase of production facilities and labor costs. The results of research were (1) Farmers’ response obtained, 83% of farmers gave a good perception of the breeding business of corn seeds. it means that corn breeding business is very likely to be cultivated and developed further. (2) Corn seed production business in Southeast Sulawesi is financially profitable and feasible to be developed with a B/C value of 2.15 and MBCR 4.4. These results indicate that the corn seed production business has good development prospects In order to support the continuous supply and fulfill of the need for quality corn seeds in Southeast Sulawesi, it is necessary to develop breeding of corn seeds, especially in areas of corn development centers. Market support is very much needed for the marketing of seed production. Market certainty will provide opportunities for the growth of new breeders, and will ensure the sustainability of corn seed breeding business at the farm level.

Automated Mini-Channel Platform for Studying Plant Root Environments

Plants are crucial to our lives because they provide us with building materials, oxygen, and food. A season’s crop yield can be significantly affected by local environmental factors. In particular, improving fundamental understanding of plant root interactions with their local soil environment, or rhizosphere, will help improve crop yield. Studying such interactions is challenging because roots are underground, making it difficult to observe interactions and to manipulate the local soil environment. The goal of this study was to develop an automated mini-channel platform to investigate how plant roots respond to changes in their environment using corn as a model plant. Considering the size of corn seedling roots, mini-channel devices were fabricated in soft lithography using master molds produced with a 3D printer and polydimethylsiloxane (PDMS). Our use of a 3D printer instead of photolithography allowed for a broader range of PDMS mold designs, such as including embedded rubber gaskets built into the mold. Then, corn seedlings were grown inside the transparent mini-channel devices, and they were found to consume an observable amount of nitrate over time. Image processing was employed to measure the contour length of the roots for quantitative characterization of root growth. Then, an automated platform was developed to measure the growth rate of the corn seedling roots and the consumed nitrate over time. The automated platform maintained the level of growth medium in the channel device, and was equipped with a digital camera to image the root growing in the channel, electrochemical sensors to measure changes in nitrate concentration in the channel, and sensors to measure temperature and humidity. Therefore, the platform could automatically measure root growth while simultaneously measuring root environment. The platform’s adaptable design, simple fabrication, and low cost make it simple to replicate and use to study different plants and environmental stimuli.

Influence of spatial planting arrangement of winter rye cover crop on corn seedling disease and corn productivity

Despite numerous environmental benefits associated with cover crop (CC) use, some farmers are reluctant to include CCs in their production systems because of reported yield declines in corn. There are numerous potential reasons for this yield decline, including seedling disease. A winter rye CC can serve as a ‘green bridge’ for corn seedling pathogens. We hypothesized that proximity of corn seedling roots to decaying rye CC roots contributes to corn seeding disease. An experimental field plot and an on-farm study were conducted over two years to evaluate growth, development, and disease severity of corn seedlings planted at various distances from decaying winter rye CC plants. The experimental field plot study was conducted in a no-till corn-soybean rotation with five replications of a winter rye CC treatments seeded as (i) no CC control, (ii) broadcast, (iii) 19-cm drilled rows, and (iv) 76-cm drilled rows. The on-farm study was no-till corn-soybean rotation with four replications of a winter rye cover crop seeded as 38-cm drilled rows, 76-cm drilled rows, and no CC control. The corn was planted on 76-cm rows shortly after rye was terminated. With multiple seeding arrangements of winter rye, corn was planted at different distances from winter rye. Corn radicle root rot severity and incidence, shoot height, shoot dry weight, corn height and chlorophyll at VT, ear parameters, and yield were collected. Soil samples were taken in the corn row and the interrow at winter rye termination, corn planting, and corn growth stage V3 to estimate the abundance of Pythium clade B members present in soil samples. Our results showed that increased distance between winter rye residue and corn reduced seedling disease and Pythium clade B populations in the radicles and soil, and increased shoot dry weight, leaf chlorophyll, plant height, and yield. This suggests that physically distancing the corn crop from the winter rye CC is one way to reduce the negative effects of a winter rye CC on corn.

An Adapted Weibull Function for Agricultural Applications

The Weibull function is applied extensively in the life sciences and engineering, but under-used in agriculture. The function was consequently adapted to include parameters and metrics that increase its utility for characterizing agricultural processes. The parameters included initial and final dependent variables (Y0 and YF, respectively), initial independent variable (x0), a scale constant (k), and a shape constant (c). The primary metrics included mode, integral average, domain, skewness and kurtosis. Nested within the Weibull function are the Mitscherlich and Rayleigh functions where c is fixed at 1 and 2, respectively. At least one of the three models provided an excellent fit to six example agricultural datasets, as evidenced by large adjusted coefficient of determination (RA2 ≥ 0.9266), small normalized mean bias error (MBEN ≤ 1.49 %), and small normalized standard error of regression (SERN ≤ 8.08 %). The Mitscherlich function provided the most probable (PX) representation of corn (Zea Mays L.) yield (PM = 87.2 %), Rayleigh was most probable for soil organic carbon depth profile (PR = 96.4 %), and Weibull was most probable for corn seedling emergence (PW = 100 %), nitrous oxide emissions (PW = 100 %), nitrogen mineralization (PW = 58.4 %), and soil water desorption (PW = 100 %). The Weibull fit to the desorption data was also equivalent to those of the well-established van Genuchten and Groenevelt-Grant desorption models. It was concluded that the adapted Weibull function has good potential for widespread and informative application to agricultural data and processes.

Weed and Corn Seedling Detection in Field Based on Multi Feature Fusion and Support Vector Machine

Detection of weeds and crops is the key step for precision spraying using the spraying herbicide robot and precise fertilization for the agriculture machine in the field. On the basis of k-mean clustering image segmentation using color information and connected region analysis, a method combining multi feature fusion and support vector machine (SVM) was proposed to identify and detect the position of corn seedlings and weeds, to reduce the harm of weeds on corn growth, and to achieve accurate fertilization, thereby realizing precise weeding or fertilizing. First, the image dataset for weed and corn seedling classification in the corn seedling stage was established. Second, many different features of corn seedlings and weeds were extracted, and dimensionality was reduced by principal component analysis, including the histogram of oriented gradient feature, rotation invariant local binary pattern (LBP) feature, Hu invariant moment feature, Gabor feature, gray level co-occurrence matrix, and gray level-gradient co-occurrence matrix. Then, the classifier training based on SVM was conducted to obtain the recognition model for corn seedlings and weeds. The comprehensive recognition performance of single feature or different fusion strategies for six features is compared and analyzed, and the optimal feature fusion strategy is obtained. Finally, by utilizing the actual corn seedling field images, the proposed weed and corn seedling detection method effect was tested. LAB color space and K-means clustering were used to achieve image segmentation. Connected component analysis was adopted to remove small objects. The previously trained recognition model was utilized to identify and label each connected region to identify and detect weeds and corn seedlings. The experimental results showed that the fusion feature combination of rotation invariant LBP feature and gray level-gradient co-occurrence matrix based on SVM classifier obtained the highest classification accuracy and accurately detected all kinds of weeds and corn seedlings. It provided information on weed and crop positions to the spraying herbicide robot for accurate spraying or to the precise fertilization machine for accurate fertilizing.

Effect of 6-Methoxy-2-benzoxazolinone (MBOA) on Pythium species and corn seedling growth and disease.

Corn yield reduction following a cereal rye cover crop has been attributed to, amongst other factors, allelochemicals released from decomposing cereal rye residue. The allelopathic effect of 6-Methoxy-2-benzoxazolinone (MBOA) was evaluated on corn seedling growth, mycelial growth of seven pathogenic species of Pythium and root rot of corn seedlings caused by Pythium species at 13 °C, 16 °C, and room temperature (22-23) °C using a plate assay. Mycelial growth of all Pythium spp. tested was slower with 0.25 mg/ml of MBOA compared to 0.125 mg/ml and 0.0625 mg/ml of MBOA and check (DV8 ++ with 0.5% DMSO). Therefore, no further tests were done with MBOA at 0.25 mg/ml. In general, MBOA reduced corn radicle length and did not cause root rot across all temperatures. However, greater root rot severity in corn was observed on corn seedlings grown in the presence of Pythium lutarium and P. oopapillum on media amended with MBOA compared to the check at all temperatures. Similarly, more root rot caused by P. torulosum, and P. spinosum was observed when MBOA was present at 16 °C compared to the check with no MBOA. These data suggest that corn seedling disease caused by Pythium species could be more severe when corn is planted following a cover crop of winter cereal rye due to the presence of allelochemicals that are released from the cover crop.