Single seed precise sowing of maize using computer simulation

Zhao, Longgang; Han, Zhongzhi; Yang, Jinzhong; Hua, Qi

doi:10.1371/journal.pone.0193750

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…This is closely related to the application and implementation of the Seed Law of the People's Republic of China [26] and the promotion of people's seed quality consciousness. With the single seed sowing technology popularized and applied to maize, high-quality seeds are an important prerequisite for applying this technology to obtain high yield [35]. The sample coating rate, namely the percentage of samples with coated seed obviously increased from 2013 to 2018.…”

Section: Discussionmentioning

confidence: 99%

A Comparative Analysis of the Hybrid Maize (Zea mays L.) Seed Quality in China from 2013 to 2018

Yue

et al. 2019

Agronomy

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In this study, a comparative analysis of seed quality indicators of 1196 hybrid maize seed samples from the main maize-producing areas in China from 2013 to 2018 was carried out. The results showed that the maize seed quality in China had changed obviously in the past six years, and was mainly as follows: The percentage of samples with coated seed in 2015–2018 was higher than 62.8% in 2013 and all exceeded 97%; the sample rate of packaging according to seed number was from 24.5% in 2013 to 58.6% in 2018, and the percentage of samples which met the prescribed quality standards was from 89.2% in 2013 to 98.4% in 2018. Principal component analysis indicated that standard germination energy (SGE), standard germination percentage (SGP), cold test germination percentage (CTGP), accelerated aging test germination percentage (AATGP), and mean field seedling emergence (FSE) were the primary predictors of seed germination and seedling emergence. Meanwhile, combining other statistical methods, regression models of SGE, SGP, CTGP, and AATGP were established to predict the field seedling emergence. Furthermore, seed bulk density and total starch content were correlated with seed vigor, which needs to be further studied. This study offered a theoretical basis and data support to better understand the changes of maize quality in China over the past six years, and provided an important reference to further improve the maize seed quality in the future.

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Section: Discussionmentioning

confidence: 99%

A Comparative Analysis of the Hybrid Maize (Zea mays L.) Seed Quality in China from 2013 to 2018

Yue

et al. 2019

Agronomy

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“…Several researchers have carried out studies to promptly monitor and quantify crop emergence, such as plant counting [5,9], emergence rate [7,10,11], canopy coverage [12][13][14], and crop growth uniformity [7,15]. The number of crops reflects the emergence rate and is the primary prerequisite for measuring crop yield [16].…”

Section: Introductionmentioning

confidence: 99%

Automatic Monitoring of Maize Seedling Growth Using Unmanned Aerial Vehicle-Based RGB Imagery

et al. 2023

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Accurate and rapid monitoring of maize seedling growth is critical in early breeding decision making, field management, and yield improvement. However, the number and uniformity of seedlings are conventionally determined by manual evaluation, which is inefficient and unreliable. In this study, we proposed an automatic assessment method of maize seedling growth using unmanned aerial vehicle (UAV) RGB imagery. Firstly, high-resolution images of maize at the early and late seedling stages (before and after the third leaf) were acquired using the UAV RGB system. Secondly, the maize seedling center detection index (MCDI) was constructed, resulting in a significant enhancement of the color contrast between young and old leaves, facilitating the segmentation of maize seedling centers. Furthermore, the weed noise was removed by morphological processing and a dual-threshold method. Then, maize seedlings were extracted using the connected component labeling algorithm. Finally, the emergence rate, canopy coverage, and seedling uniformity in the field at the seedling stage were calculated and analyzed in combination with the number of seedlings. The results revealed that our approach showed good performance for maize seedling count with an average R2 greater than 0.99 and an accuracy of F1 greater than 98.5%. The estimation accuracies at the third leaf stage (V3) for the mean emergence rate and the mean seedling uniformity were 66.98% and 15.89%, respectively. The estimation accuracies at the sixth leaf stage (V6) for the mean seedling canopy coverage and the mean seedling uniformity were 32.21% and 8.20%, respectively. Our approach provided the automatic monitoring of maize growth per plot during early growth stages and demonstrated promising performance for precision agriculture in seedling management.

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“…The high-speed precision seeding technology of corn under automatic driving requires the seeding device to maintain a high ground speed over 8 km•h −1 . At the same time, the quantitative seeds are sown according to the planting spacing, row spacing uniformity and sowing depth required by agronomy, and the planting technology of deep fertilization, which can not only improve the uniformity of corn sowing, enhance the rationality between light, water, and fertilizer during the growth of corn, but also improve the efficiency of corn sowing and thus increase the yield per acre [19][20][21]. When the operation starts, the unit accelerates to stability, decelerates to stop at the field head, and stops at high and low speeds, which leads to the instability of the motor.…”

Section: Introductionmentioning

confidence: 99%

The Development of an Electric-Driven Control System for a High-Speed Precision Planter Based on the Double Closed-Loop Fuzzy PID Algorithm

Wang

Zhang

et al. 2022

Agronomy

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In order to solve the problems of traditional seeders, such as low seeding efficiency, tangled straw, a large amount of clay, easy ridge breakage in sowing operations, low qualified rate of high-speed seeding, and poor uniformity, this paper takes the pneumatic corn planter as the research object, the Beidou automatic driving unit as the carrier, the CAN (Controller Area Network) bus as the communication medium, and the double closed-loop fuzzy PID (proportion-integral-derivative) algorithm as the control core and designs a high-speed precision corn seeding control system based on Beidou navigation. It solves the problems that exist in traditional planters. In the bench experiment, the stability of the system is judged by comparing the motor control accuracy with ordinary PID and measuring the motor response time of the system at different speeds. The bench test results show that when the theoretical seeding speed is 0~34 r · min−1, the response time of the motor is shortened by 0.51 s compared with the ordinary PID control, and the error between the actual speed and the target value is less than 0.35%. The field experiment results show that when the unit runs for 5~13 km · h−1, the qualified rate of average planting spacing is greater than 95.81%, the reseeding rate is less than 10.11%, and the coefficient of variation is less than 16.72%, which complies with the standard of a corn sowing operation.

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Single seed precise sowing of maize using computer simulation

Cited by 7 publications

References 6 publications

A Comparative Analysis of the Hybrid Maize (Zea mays L.) Seed Quality in China from 2013 to 2018

A Comparative Analysis of the Hybrid Maize (Zea mays L.) Seed Quality in China from 2013 to 2018

Automatic Monitoring of Maize Seedling Growth Using Unmanned Aerial Vehicle-Based RGB Imagery

The Development of an Electric-Driven Control System for a High-Speed Precision Planter Based on the Double Closed-Loop Fuzzy PID Algorithm

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