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Evaluation of Soil Hardness in Paddy Fields by Cone Penetrometer as a Simple Soil Physical Diagnosis Method

To enable quantitative soil physical diagnosis by cone penetrometer, this study investigated time-course changes in the three-dimensional (3D) distribution of soil hardness and quantified the effect of land leveling on soil compaction. The most important result is that the 3D distribution of soil hardness in the field can be mapped quickly. One person could survey 1 ha to 60 cm depth in 90 min. The method allows several fields to be screened in a short time. The results of cluster analyses based on the horizontal distribution of soil hardness show that the distribution did not change significantly throughout the year. Although absolute values can change, this method can be used to measure soil hardness at any time of the year. Measurement of soil hardness by depth can detect the range or position of the plow pan. Comparison of the distribution of soil physical properties between fields revealed that field management affects hardness, especially in the plow layer and plow pan.


Introduction
In Japan, in response to decreases in the price of rice and in rice consumption, paddy fields have been converted to upland fields to grow maize, wheat, and vegetables (MAFF 2016a). In consequence, the importance of soil physical diagnosis has increased (Anzai 2016). Japanese agriculture continues to contract as farmers age and the working population decreases (MAFF 2016a, MAFF 2017. In response, work efficiencies have been improved through increases in the scale of management (Shimizu 2017), such as field consolidation and the use of larger machinery (MAFF 2015), reducing time and effort. This move toward extensive agriculture requires simple and quick techniques for soil physical diagnosis of large areas in less time.
In addition, according to the Fifth Assessment Report of the IPCC (2013), extreme precipitation events over most of the mid-latitude land masses and over wet tropical regions will very likely become more intense and more frequent by the end of this century as the global mean surface temperature increases. In Japan, extreme weather already causes problems (JMA 2018a): heavy rain and drought both cause a great deal of damage to crops every year.
One way to reduce damage is to improve soil physical properties (Anzai 2016).
Soil physical properties in farmland are typically evaluated to a depth of about 20 cm in the topsoil and to about 60 cm in the subsoil. On-site measurement methods include the use of cylinder intake rate (Fukumoto 2013), disk permeameters (Perroux and White 1988), and infiltration meters (Reynolds andElrick 1991, Savadogo et al. 2017) to evaluate permeability to water. However, they are slow, and water is needed.

Yamanaka System Hardness Sensors (Fujiwara Scientific
Company, Japan) are commonly used in Japan for measuring soil hardness (Komatsu et al. 2007), and criteria for the diagnosis of soil hardness are often based on readings of these sensors. A study of 280 paddy field sites in Chiba prefecture found a positive correlation between the Yamanaka hardness index (YHI) values of soil compaction and the logarithm of penetration resistance measured by a cone penetrometer (Arihara and Watanabe 1993). However, to measure soil hardness with Yamanaka System Hardness Sensors, we have to dig a cross-section more than 60 cm deep. Since this takes time and effort, few cross-sections can be investigated in a day.
A cone penetrometer offers an easy and quick way to measure soil penetration resistance since it does not require special techniques or skills (EBSSAMM 1986). Since its measurements are continuous through the soil profile, it allows the soil bearing capacity, related to the running of tractors or combines, to be qualitatively evaluated, and the position of the plow layer to be determined from the irregular shape of the plot (EBSEAM 1997).
A DIK-5530 digital cone penetrometer (Daiki Rika Kogyo Co., Ltd., Kounosu, Saitama, Japan; Table 1) can display successive values of soil compaction in 1-cm increments to depths of up to 90 cm. With its Global Positioning System (GPS) receiver, it can record the location at the same time. Since it takes only 60 to 90 s per sampling, it is possible to collect data at more sampling points than with a Yamanaka System Hardness Sensor or by measuring water permeability within the same period. Soil physical properties differ even over short distances, so sampling at multiple points improves the resolution.
Systems for the automatic measurement of soil hardness have been developed (Carrara et al. 2007, Tekin et al. 2008, Fountas et al. 2013. Naderi-Boldaji et al. (2012) developed an on-the-go horizontal penetrometer using sensors mounted on tines drawn by a tractor. Being tractor drawn, the penetrometer can take measurements quickly with little effort. However, action of the tines destroys the soil structure, and continuous surveying is difficult.
Since the plow pan plays an important role in paddy fields in preventing water leakage, it cannot be disturbed during sampling. As a cone penetrometer can be used simply by stabbing the rod below the ground surface, it can also be used to collect data with minimal disturbance.
Spatial statistics, geostatistical analysis, and spatial econometrics can be used to measure spatial variations (Mase 2010, Furutani 2011, Tsutsumi and Seya 2012, Seya and Tsutsumi 2014, Arbia 2016. Preparation for mapping can be facilitated through the use of a global navigation satellite system (GNSS). Current systems include the US Global Positioning System (GPS), the Russian Global Navigation Satellite System (GLONASS), the European Union's Galileo, and the Chinese BeiDou Navigation Satellite system. Regional navigation satellite systems include the Navigation Indian Constellation (previously Indian Regional Navigational Satellite System) and the Japanese Quasi-Zenith Satellite System (QZSS).
The QZSS provides highly precise, GPS-compatible, stable positioning services in the Asia-Oceania region (Cabinet Office 2018).
As paddy fields have grown larger through field consolidation, guidelines for leveling precision have been devised for paddy field management. Judging from the optimal water depth for rice growth, Yamaji (1989) concluded that the target value of leveling  (Oshita 2000). Through leveling by a 53.8-kW (73PS) tractor using a technique developed for automatic precision laser-leveling, in a 1-ha field, an elevation range of 16 cm was improved to ± 2.5 cm (s.d. = 15.8 mm) over 92% of the field (Kimura et al. 1999). In a study of the effect of unevenness in a paddy field on tiller development of direct-seeded rice in Niigata Prefecture, one laser-leveling operation improved the leveling precision from s.d. = 18 mm to 11 mm, and the proportion of measurement points within ± 2.0 cm was increased from 80% to 94% (Sasaki et al. 2002). The annual use of a heavier tractor should improve leveling precision because soil hardness is not increased. In Yamagata prefecture, Seino et al. (1998)  This paper reports a study designed to develop a technique to enable the quantitative evaluation of soil hardness by cone pene-

GNSS receiver
The study used a DIK-5530 digital cone penetrometer (Table 1)      As in Experiment 1, 3D-distribution maps of soil hardness were created, and the average and s.d. of soil hardness by depth before and after leveling were plotted. Although the total weight of the equipment (~6.5 t) and the length, width, tire position, and wheel base are known (Table 4), and speed and acceleration during leveling can be calculated from the GNSS data, methods to estimate soil compaction have not been developed yet, so the degree of soil

Creating 3D distribution maps of soil hardness in a field
compaction cannot yet be calculated. The field was divided into a 10-m mesh, and the number of tractor passes was recorded.    (Saegusa 1997). In humic Andosols, 1500 kPa measured by cone penetrometer is equivalent to 20-21 mm on the YHI (EBSEAM 1997). The range of soil hardness that inhibits root growth and moisture permeability in this study ranged from 1300 to 2500 kPa (Fig. 4). When YHI > 20 mm ( > 1300 kPa, Fig. 4), the steepness of the regression curve makes it hard to assess the magnitude of the soil hardness quantitatively. Use of the cone penetrometer, in contrast, makes it possible to locate the plow pan. reduce field permeability of soil growing direct-seeded rice. Soil hardness decreased in the order of low soil water content / high compaction > high soil water content / high compaction > high soil water content / low compaction. Although the relationship between soil hardness and precipitation must be clarified, the average soil hardness of Y1 and Y4 might be relatively low.

Results and Discussion
Soil moisture content changes with both location and depth in the field, and therefore soil hardness does too. Values measured by cone penetrometer cannot separate the effect of soil hardness due to dryness and softness due to plasticity (Yamanaka and Matsuo 1962). Softer points than surrounding points might have a higher moisture content.
Although the absolute values of soil hardness depended on the season, hardness tended to be higher at the field margins than in the middle of the field (Fig. 2-1, 2-2 and 2-3), likely owing to the regular use of heavy machinery to work the headland.
To investigate how the horizontal distributions of soil hardness per 1 cm depth were grouped, hierarchical cluster analyses were performed for each season (Figure 6). The horizontal distributions were separated into two groups (1-14 or 15 cm and ≥ 15 or 16 cm) in all seasons. The 1-14-or 15-cm group was subdivided into 1-9 or 10 cm and ≥ 10 or 11 cm, effectively the plow layer and the boundary zone between there and the plow pan, respectively. The > 15-or 16-cm group tended to be subdivided into ~15-20 cm and > 20 cm, effectively the plow pan and the subsoil layer, respectively. These groupings did not change notably throughout the year.
To investigate the differences in the horizontal distributions of soil hardness per 1 cm depth before and after plowing, cluster analysis was conducted with the Y1 and Y4 data (Figure 7), which correspond to wheat cultivation. The horizontal distributions were separated into two groups (1-19 or 20 cm and ≥ 20 or 21 cm) in both years. The 1-19 or 20-cm group was subdivided into 1-12 or 13 cm and ≥ 13 or 14 cm, effectively the plow layer and plow pan, respectively. This cutoff (~19 or 20 cm) was deeper than that in the The locations of sampling points before and after soil leveling are shown in Figure 8. The route of the leveler shows that all four sides of the field received multiple passes, in particular the righthand side. In direct-seeded paddy fields, leaks in the levees are easy to see (Kanmuri et al. 2012). As this field has drainage points on the right-hand side, it is possible that the operator paid careful attention to leveling so as to stop all leaks.
The number of tractor passes was integrated into the 10-m mesh in Figure 9. The number ranged from 16 to 74, with an average of 29.6 and a median of 25. Nearly 2 / 3 of the field (65%) received 16 to 30 passes. The right-hand side of the field received many passes.
As the laser leveler is wider than the tractor (Table 4), some areas might have received even more.
Representative contour plots of soil hardness in Field I before and after land leveling are shown in Figure 10-1, 10-2 and 10-3. To separate the influence of the first cultivation, differences were also plotted. As in Experiment 1, although the absolute values of soil hardness depended on leveling, the hardness tended to be higher on the field margins than in the middle. In the difference plots, the plow layer ( < 16 cm) was most affected by compaction during leveling, especially on the right-hand side of the field. In the range of the plow pan (16-21 cm), the effects of compaction remained at the upper-right side ( Fig. 10-1, 10-2 and 10-3). As the field drainage is placed along this side, the results show the extra work by the tractor.
The average and s.d. of soil hardness by depth are plotted in Figure 11. The s.d. shows a bulge (peak, 16 cm; range, 11-21 cm) in both fields. After leveling, there was another bulge (peak, 2 cm; range, 1-9 cm), likely due to increased compaction of the surface layer by the leveler. Since soil is leveled when dry, the compaction The s.d. plots were evaluated more precisely to estimate the possibility that the reference plane had been lowered by leveling.
In I1 (before leveling), bulges peaked at 3, 16, and 24 cm; in I2 (after leveling), bulges peaked at 2, 16, and 27 cm (Fig. 11). If the The effects of differences in field management methods on the 3D distribution of soil hardness were compared between Field Y (Y1 in Fig. 2-1, 2-2 and 2-3) and Field I (I1 in Fig. 10-1, 10-2 and 10-3). In Field I, soil hardness ranged from 337.5 to 675.0 kPa from 4 to 60 cm with no sudden increase with depth. Although the field margins were compacted to prevent leakage, no hydroponic soil layer could be seen. In Field Y, soil hardness ranged from 0 to 1013.0 kPa to 10 cm, and was softer than in Field I. But from 15 cm, the plow pan could be seen, and soil hardness increased to 25 cm and remained high to 60 cm. The contrast in soil hardness from the surface soil via the plow pan into the subsoil was greater in Field Y than in Field I.
Comparison of Y1 in Figure 3 with I1 in Figure 11 shows that the distributions of soil hardness were affected by the planting method. In Field Y, the average values of soil hardness in the subsoil were all larger than the overall average, and soil hardness increased rapidly from the plow layer via the plow pan to the sub-   Since puddling of the soil blocks soil pores with fine particles, the water is less likely to leak in transplanting culture, and the plow pan develops harder. On the other hand, direct sowing involves only pressing on the soil surface, and a plow pan doesn't develop, so the subsoil is little affected by the pressure. Kanmuri et al. (2012) showed that three-step compaction of the field surface steadily reduced the irrigation water requirement to 20 mm / d. To achieve this condition, the soil hardness at 5 cm depth must be about 20 mm on the YHI or water cannot pass. As shown in I2 in Figure 11, the soil hardness at around 2 cm depth was greater after leveling. In the case of direct-sowing, it is therefore important to harden the soil surface so as to prevent leakage.
This method was thus able to quantitatively evaluate the impact of the difference in planting method on soil hardness.

Conclusions
The most important result of this study is that the 3D distribution of soil hardness in the field can be mapped much more quickly through the use of a cone penetrometer than by conventional tech- Differences in the distribution of soil hardness revealed the effects of field management on soil hardness. In particular, plotting the s.d. of soil hardness revealed differences in the position and structure of the pan. This methodology can also measure the effects of large machinery. For part of this study, a patent was applied for in August 2017.