• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.258-267
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• 2020

The agrivoltaic can produce electricity and grow crops on fields at the same time. It is necessary to analyze the cultivation environment and evaluate the crop productivity under agrivoltaic because the shading point changes according to structure of agrivoltaic and sun's position. Two types of "fixing" and "tracing" agrivoltaic were installed, and a rice cultivation experiment was conducted in the fields under each agrivoltaic and without shading (control). "Hyunpoombyeo" was transplanted on June 7, 2019, and grown with fertilization of 9.0-4.5-5.7 kg/10a (N-P-K). Fifteen weather stations were installed under each agrivoltaic to measure solar radiation and temperature, and yield and yield-related elements were investigated by points. The accumulated solar radiation during the rice growing season in fixing was no much difference between points, and that in tracing was much difference between points. However, the average solar radiations of two agrivoltaics were similar. The mean temperature, yield, and yield-related elements showed a significant difference for the shading rate, and decreased with increasing the shading rate except ripening grain rate and 1000 grain weight of fixing agrivoltaic. In the relationship between shading rate and yield, fixing and tracing were fitted to a logistic equation and a simple linear equation, respectively, and showed a high correlation (tracing: R2 = 0.62, fixing: R2 = 0.73). The shading rate variation by point for two types was large despite similar yield variation. Thus, it needs to be more closely examined the relationship of the shading rate for a specific period rather than the shading rate during the whole growing season.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.279-288
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• 2021

Low-density transplanting is a cultivation technology that reduces labor and production costs. In this study, the growth and yield of several varieties with different tillering characteristics were analyzed in order to establish an appropriate planting density for low-density transplanting. Varieties with Low-Tillering (LT), Medium-Tillering (MT), and High-Tillering (HT) were planted at a density of 37-80 hills/3.3 m². As the planting density decreased, the number of tillers per hill increased, but the number of tillers per square meter of hill decreased, especially for the LT variety. Decreasing density extended the tillering stage, which was longest in the LT variety. As the planting density decreased, SPAD(Soil plant analysis development, chlorophyll meter) values just before heading increased while canopy light interception decreased. Such changes were much greater in the LT variety than in the MT and HT varieties. The heading date tended to be delayed by 0-2 days as the planting density decreased, and there was no difference in the length of the period from first heading to full heading. As the number of spikelets per panicle increased, the number of spikelets per square meter did not differ according to the planting density. Decreasing planting density did not affect the grain weight; nevertheless, the yield ultimately decreased because of the decreasing ripening rate. The optimal planting density for stable low-density transplanting cultivation was determined to be over 50 hills/3.3 m2. In addition, these results suggest that LT varieties should be avoided, since these showed large decreases in growth and yield with decreasing planting density.

• Journal of Practical Agriculture & Fisheries Research
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• v.18 no.1
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• pp.79-91
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• 2016

Quality factors which characterize 11 kinds of farm-manufactured apple Jangachi and commercial Jangachi, have been studied in order to provide a guideline to improve the quality and marketing strategy of farm-manufactured pickled apples. Moisture content ranged from 74% to 84% and 81% to 91% in Doenjang Jangachi and vinegar Jangachi, respectively; 38% to 64% in Kochujang Jangachi; 57% to 64% in radish Kochujang Jangachi. Moisture content was 89% in Doenjang Jangachi. Even though moisture content of apple Kochujang Jangachi indicated 48% which is lower than that of radish Jangachi, it was higher than that of a persimmon pickled in Kochujang (38%) and that of Japanese apricot Jangachi (49%). pH and titratable acidity, two indicators used to determine the appropriate ripening period of Jangachi, were pH 3.4~5.6, 0.03~0.14%, respectively. The pH ranged from 5.2 to 5.6 in radish Jangachi; 3.4 to 4.1 in Cucumber Jangachi. pH of persimmon Jangachi, Japanese apricot Jangachi and apple Jangachi showed 4.1, 3.5 and 4.1, respectively. Compared with the pH of traditional Jangachi (3.03~5.36), pH of all of the above Jangachi fall into an appropriate range. The brix of apple Jangachi (30%) was 12% to 18% higher than that of Kochujang radish Jangachi, but it was relatively lower than that of persimmon Jangachi (39%) and that of Japanese apricot Jangachi (49%). Salinity of Jangachi varied depending on which marinating material was used. Salinity in the descending order according to each marinating material demonstrated Kanjang (6% to 13%), Doenjang (7%), Kochujang (3% to 4%). Salinity of apple Jangachi was 3.28% which was relatively lower than that of commercial Jangachi which used either Kanjang or Doenjang as its marinating material. Chromaticity test shows that the brightness value of apple Jangachi (54.70) was similar to that of cucumber Jangachi (50.86, 56.02); the redness value and yellowness of apple Jangachi (16.21 and 26.78) were higher than the redness value (7.27 to 11.23) and the yellowness value (10.62 to 14.69) of radish Kochujang Jangachi. Sensory Characteristics value of apple Jangachi, along with radish and cucumber Jangachi in its color, odor and taste (7.00, 7.50, 7.00, respectively) placed high on the list implying higher preference. However, overall preference value of apple Jangachi was 6.83 which was lower than that of Japanese apricot Jangachi or that of radish Jangachi. The result can be explained by the tendency of people preferring crispy Jangachi and points out that the texture of apple Jangachi needs to be improved to gain popularity. Furthermore, for increased sales of apple Jangachi as a niche product, more rigorous market testing is required.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.346-358
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• 2023

Due to the acceleration of climate change or global warming, it is important to predict rice productivity in the future and investigate physiological changes in rice plants. The research aimed to explore how rice adapts to climate change by examining the response of nitrogen absorption and nitrogen use efficiency in rice under elevated levels of carbon dioxide and temperature, utilizing the SPAR system for analysis. The temperature increased by +4.7 ℃ in comparison to the period from 2001 to 2010, while the carbon dioxide concentration was held steady at 800 ppm, aligning with South Korea's late 21st-century RCP8.5 scenario. Nitrogen was applied as fertilizer at rates of 0, 9, and 18 kg 10a^-1, respectively. Under conditions of climate change, there was an 81% increase in the number of panicles compared to the present situation. However, grain weight decreased by 38% as a result of reduction in the grain filling rate. BNUE, indicative of the nitrogen use efficiency in plant biomass, exhibited a high value under climate change conditions. However, both NUEg and ANUE, associated with grain production, experienced a notable and significant decrease. In comparison to the current conditions, nitrogen uptake in leaves and stems increased by 100% and 151%, respectively. However, there was a 25% decrease in nitrogen uptake in the panicle. Likewise, the nitrogen content and NDFF (Nitrogen Derived from Fertilizer) in the sink organs, namely leaves and roots, were elevated in comparison to current levels. Therefore, it is imperative to ensure resources by mitigating the decrease in ripening rates under climate change conditions. Moreover, there seems to be a requirement for follow-up research to enhance the flow of photosynthetic products under climate change conditions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.188-196
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• 2023

Wheat (Triticum aestivum L.) is an important crop in Korea, with a per capita consumption of 31.6 kg in 2019. In the southern region, wheat is grown after paddy rice, and it is harvested during the rainy season in mid-June. This timing, in combination with high humidity and untimely rainfall, activates the enzyme alpha-amylase, which breaks down starch in the wheat grains. As a result, sprouted grains have lower quality and value for flour. However, seeds that absorb water before sprouting are expected to maintain better quality. The aim of the study was to identify the critical period during wheat maturation when rainfall has the greatest impact on grain quality, to prevent price declines due to quality deterioration. Two wheat cultivars, Jokyoung and Hwanggeumal, were grown in a speed breeding room, and artificial rainfall was applied at different times after heading (30, 35, 40, 45, 50, and 55 days). The proportion of vitreous grains decreased from 40 to 55 days after heading (DAH). Both cultivars had chalky grain sections from 35 DAH, with Hwanggeumal having a higher proportion of vitreous grains. Starch degradation was observed using FE-SEM (Field Emission Scanning Electron Microscope) at 40 DAH for Jokyoung and 50 DAH for Hwanggeumal. Color measurements indicated increased L and E values from 40 DAH, with rain treatment at 55 DAH leading to a significant increase in L values for both cultivars. Ash content increased at 45 DAH, whereas SDSS decreased at 35 DAH. Overall, grain quality from 40 DAH until harvest was found to be affected to the greatest extent by direct exposure of the spikes to moisture. Red wheat showed better quality than white wheat. These findings have implications for the cultivation of high-quality wheat and can guide future research efforts in this area.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.18
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• pp.88-123
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• 1975

To obtain useful fundamental informations for improving cultural practices of barley, an investigation was made on the influences of different fertilizer level and seeding rate as well as seeding date on yield and yield components and their balancing procedure using barley variety Suwon ＃ 18, and at the same time, 8 varieties including Suwon ＃ 18 were also tested to clarify the varietal responses in terms of their yield and yield components under different seeding date at Crop Experiment Station, Suwon, during the period of 1969 and 1970. The results obtained were summarized as follows; 1. Days to emergence of barley variety Suwon ＃ 18 at Suwon, took 8 to 19 days in accordance with given different seeding date (from Sept. 21 to Oct. 31). Earlier emergence was observed by early seeding and most of the seeds were emerged at 15$0^{\circ}C$ cumulated soil temperature at 5cm depth from surface under the favorable condition. 2. Degree of cold injury in different seeding date was seemed to be affected by the growth rate of seedlings and climatic condition during the wintering period. Over growth and number of leaves less than 5 to 6 on the main stem before wintering were brought in severe cold damage during the wintering period. 3. Even though the number of leaves on the main stem were variable from 11 to 16 depending upon the seeding date. this differences were occurred before wintering and less variation was observed after wintering. Particularly, differences of the number of main stem leaves from September 21 to October 11 seeding date were occurred due to the differences of number of main stem leaves before wintering. 4. Dry matter accumulation before wintering was high in early seeded plot and gradually decreased in accordance with delayed seeding date and less different in dry matter weight was observed after wintering. However, the increment rate of this dry matter was high from regrowth to heading time and became low during the ripening period. 5. Number of tillers per $\m^2$ was higher in early seeding than late one and dense planting was higher in the number of tillers than sparse planting. Number of tillers per plant was lower in number and variation in dense planting, and reverse tendency was observed in sparse planting. By increasing seedling rate in early seeding date the number of tiller per plant was remarkably decreased, but the seeding rate didn't affect the individual tillering capacity in the late seeding date. 6. Seedlings were from early planting reached maximum tillering stage earlier than those from the late planting and no remarkable changes was observed due to increased seeding rate. However. increased seeding rate tends to make it earlier the maximum tillering stage early. 7. Stage of maximum tillering was coincided with stage of 4-5 main stem leaves regardless the seeding date. 8. Number of heads per $\m^2$ was increased with increased seeding rate but considerable year variation in number of heads was observed by increased fertilizer level. Therefore, it was clear that there is no difficulties in increasing number of heads per $\m^2$ through increasing both fertilizer level and seeding rate. This type of tendency was more remarkable at optimum seeding time. In the other hand, seeding at optimum time is more important than increasing seeding rate, but increasing seeding rate was more effective in late seeding for obtaining desirable number of heads per $\m^2$. 9. Number of heads per $\m^2$ was decreased generally in all varieties tested in late seeding, but the degree of decrease by late seeding was lower in Suwon ＃ 18. Yuegi, Hangmi and Buheung compared with Suwon ＃ 4, Suwon ＃ 6, Chilbo and Yungwolyukak. 10. Highly significant positive correlations were obtained between number of head and tillers per $\m^2$ from heading date in September 21 seeding, from before-wintering in October 1 seeding and in all growth period from October 11 to October 31 seeding. However, relatively low correlation coefficient was estimated between number of heads and tillers counted around late March to early April in any seeding date. 11. Valid tiller ratio varied from 33% to 76% and highest yield was obtained when valid tiller ratio was about 50%. Therefore, variation of valid tiller ratio was greater due to seeding date differences than due to seeding rate. Early seeding decreased the valid tiller ratio and gradually increased by delaying seeding date but decreased by increasing seeding rate. Among the varieties tested Suwon ＃ 18, Hangmi, Yuegi as well as Buheung should be high valid tiller ratio not only in late seeding but also in early seeding. In contrast to this phenomena, Chilbo, Suwon ＃ 4, Suwon ＃ 6 and Yungwolyukak expressed low valid tiller ratio in general, and also exhibited the same tendency in late seeding date. 12. Number of grains per spike was increased by increasing fertilizer level and decreased by increasing seeding rate. Among the seeding date tested. October 21 (1969) and October 11 (1970) showed lowest number of grains per spike which was increased in both early seeding and late seeding date. There were no definite tendencies observed along with seeding date differences in respective varieties tested. 13. Variation of 1000 grain weight due to fertilizer level applied, seeding date and seeding rate was not so high as number of grains per spike and number of heads per $\m^2$, but exhibited high year variation. Increased seeding rate decreased the 1000 grain weight. Among the varieties tested Chilbo and Buheung expressed heavy grain weight, while Suwon ＃ 18, Hangmi and Yuegi showed comparatively light grain weight. 14. Optimum seeding date in Suwon area was around October 1 to October 11. Yield was generally increased by increasing fertilizer level. Yield decrease due to early seeding was compensated in certain extent by increased fertilizer application. 15. Yield variations due to seeding rate differences were almost negligible compare to the variations due to fertilizer level and seeding date. In either early seeding or law fertilizer level yield variation due to seeding rate was not so remarkable. Increment of fertilizer application was more effective for yield increase especially at increased seeding rate. And also increased seeding rate fairly compensated the decrease of yield in late seeding date. 16. Optimum seeding rate was considered to be around 18-26 liters per 10a at N-P-K=10.5-6-6 kg/10a fertilizer level considering yield stabilization. 17. Varietal differences in optimum seeding date was quite remarkable Suwon ＃ 6, Suwon ＃ 4. Buheung noted high yield at early seeding and Suwon ＃ 18, Yuegi and Hangmi yielded higher in seeding date of October 10. However, Buheung showed late seeding adaptability. 18. Highly significant positive correlations were observed between yield and yield components in all treatments. However, this correlation coefficient was increased positively by increased fertilizer level and decreased by increased seeding rate. Significant negative correlation coefficients were estimated between yield and number of grains per spike, since increased number of heads per m2 at the same level of fertilizer tends to decrease the number of grains per spike. Comparatively low correlation coefficients were estimated between 1000 grain weight and yield. 19. No significant relations in terms of correlation coefficients was observed between number of heads per $\m^2$ and 1000 grain weight or number of grains per head.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.18
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• pp.1-27
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• 1975

Experiment I: A field experiment was conducted in an attempt to find the effect of top-dressing at heading time in different levels of nitrogen application and of different positioned leaf blades formed by the treatment of leaf defoliation at heading time on the ripening and the yield of rice. The results obtained are as follows: 1. Average number of ears per hill and average number of grains per ear in different levels of nitrogen application were increased as the amount of nitrogen applied was increased. while the rate of ripened grains the yield of rough rice and the weight of 1, 000 kernels of brown rice were decreased respectively as the amount of nitrogen applied was increased. 2. The rate of ripened grains and the weight of 1.000 kernels of brown rice in different levels of nitrogen, top-dressing at heading time were larger than those in control and increased. The yield of rough rice although statistically significant differences were not recognized, were numerically increased. 3. The rate of ripened grains, the yield of rough rice, the weight of 1, 000 kernels of brown rice and the rate of hulling in different treatments of leaf defoliation were remarkably decreased as the degree of leaf-defoliation became larger. 4. The rate of ripened grains, the yield of rough rice, the weight of 1, 000 kernels of brown rice and the rate of hulling in different combinations of number of remained leaves positioned differently, formed the order of $L_1(flag leaf)>L_2>L_3>L_4$ when only one leaf blade was remained, and were increased as the positions of leaves were higher when two leaf blades. were, remained. 5. In case of decrease in the number of leaf blades positioned differently, by the treatment of leaf. defoliation, rate of ripened grains, the yield of rough rice, the weight of 1, 000 kernels of brown rice and the rate of hulling were increased as the area of remained leaves became larger and the nitrogen content of a leaf blade was increased. 6. There was a tendency that the increase in the amount of fertilizer application made the rate of ripened grains and the weight of 1, 000 kernels of brown rice reduced in any number of remained leaf blades, but the application of top-dressing at heading. time resulted in the reverse tendency. The yield of rough rice showed a tendency to be increased as the amount of basal dressing and top-dressing increased and for the application of top-dressing at heading time, the yield of rough rice was less at the smaller number of those. 7. The productivity effect of the rate of ripened grains and the yield of brown rice covered by leaf blades was more than 50 per cent and that of the. weight of 1, 000 kernels of brown rice was not more than 1.0 percent. As the amount of nitrogen application increased the. effect of leaf blades on the rate of ripened. grains and the weight of 1, 000 kernels of brown rice was increased. The effect of leaf blades on the weight of brown rice was increased as the amount of basal dressing-application, but the effect was decreased as the amount of top-dressing at heading time increased, 8. The productivity effects of different positioned leaf blades on the rate of ripened grains, the yield of rough rice and the weight of 1, 000 kernels of brown rice were in order of $L_1(flag leaf)>L_2>L_3>L_4$ the productivity effects of $L_1$ and $L_2$ had a tendency to be increased as the amount of nitrogen applied was increased. Experiment II: A field experiment was done in order to disclose the effect of the time of nitrogen application on yield component and the effect of different positioned leaves formed by leaf defoliation at heading time on the rate of ripened grains and the yield of rice. The results obtained are as follows: 1. Average number of ears per hill was increased in the treatment of nitrogen application from basal dressing to 22 days before heading and in the treatment of application distributed weekly. Number of grains was increased in the treatment of nitrogen application from 36 days to 15 days before heading. The rate of ripened grains was, lower in the treatment of nitrogen application from top-dressing to 15 days before heading than in that of non-application, was higher in the treatment of nitrogen application within 8 days before heading, and was the lowest in that of application 29 days before heading. The yield of rough rice was the highest in the treatment of nitrogen application from 29 days to 22 days before heading. The weight of 1, 000 kernels of brown rice was a little high in the treatment of application from 29 days to 8 days before heading. 2. The rate of ripened grains the yield of rough rice, the weight of 1, 000 kernels of brown rice and the rate of hulling in different treatments of leaf defoliation were remarkably decreased as the degree of leaf defoliation got larger and there were highly significant differences among treatments. There was also a recognized interaction between the time of nitrogen application and leaf defoliation. 3. In relation to the rate of ripened grains, the weight of 1. 000 kernels of brown rice and the rate of hulling in different numbers of remained leaves positioned differently and their combinations, the yield components were in order of $L_1(flag leaf)>L_2>L_3>L_4$ when only one leaf was remained, which indicated that the components were increased as the leaf position got higher. When two laves were remained, the rate of ripened grains, the yield of rough rice and rate of hulling were high in case of the combinations of upper positioned leaves, and the increase in the weight of 1, 000 kernels of brown rice appeared to be affected most]y by flag leaf. When three leaf blades were remained similarly the components were increased with the combination of upper positioned leaf blades. 4. In case of decreased different positioned leaf blades by treatment of leaf defoliation, there was a significant positive regression between the leaf area, the dry matter weight of leaf blades and the nitrogen contents of leaf blades, and rate of ripened grains and the yield of rough rice, but there was no constant tendency between the former components and the weight of 1. 000 kernels of brown rice. 5. The closer the time of fertilizer application to heading time, the more the rate of ripened grains and the weight of 1, 000 kernels was decreased by defoliation, and the less were the remained leaf blades, the more remarkable was the tendency. The rate of ripened grains and the weight of 1. 000 kernels was increased by the top-dressing after heading time as the number of remained leaf blades. When the number of remained leaf blades was small the yield of rough rice was increased as the time of fertilizer application was closer to heading time. 6. Discussing the productivity effects of different organs in different times of nitrogen application, the productivity effect of a leaf blade on the rate of ripened grains was higher as the time of nitrogen application got later, and in the treatment of non-fertilization the productivity effect of a leaf blade and that of culm were the same. In the productivity effect on the yield of brown rice, the effect of culm covered more than 50 percent independently on the time of nitrogen application, and the tendency was larger in the treatment of non-fertilizer. The productivity effect of culm on the weight of 1. 000 kernels of brown rice was more than 90 percent, and the productivity effect of a leaf blade was increased as the time of application got later. 7. The productivity effect of a leaf blade in different positions on the rate of ripened grains, the yield of rough rice and the weight of 1, 000 kernels of brown rice had a tendency to be increased as the time of application got later and as the position of leaf blades got higher. In the treatment of weekly application through the entire growing period, the rate of ripened grains and the yield of rough rice were affected by flag leaf and the second leaf at the same level, the but the weight of 1, 000 kernels of brown rice was affected by flag leaf with more than 60 percent of the yield of total leaves.