Rice is usually an annual crop but can be renewed using the ratoon cropping method. Perennial cropping of rice requires less labor and water, while reducing climate risk and greenhouse gas emissions. Perennial rice cropping is a traditional cropping method but is rarely used because of the low yield. However, the additional yield achieved after harvesting the main crop has allowed its successful commercial application in the southern region of the United States of America and parts of southern China ( Sacks, 2013). Most studies on ratoon rice have focused on additional yield, and the yield is at most 50% of the main crop ( Negalur et al., 2017). A previous study reported a yield of up to 90% of the main crop using a special variety (PR23), but the fluctuations in yield were very large ( Zhang et al., 2014).

Recently, a breakthrough in increasing yield was achieved in Indonesia. Rice has limited growth period during winter; therefore, rapid growth is the key to success of ratoon cropping. Moreover, ratoon cropping from higher nodes of rice is important, because the carbon can be accessible to the main crop culm ( Balasubramanian et al., 1992). However, because tropical regions have no winter, the method used can be different. Fitri et al. (2019) looked at an updated method of traditional perennial rice cropping developed by Mr. Erdiman in 2010. The method was named “SALIBU,” a portmanteau of the Indonesian words “SALIN” (replication) and “IBU” (mother). Using SALIBU, the same or higher yield than that of the main crop was achieved. The mechanisms inducing the high yield have not been well studied, but a possible reason is that lower nodes can extend new roots and improve nutrient uptake from the soil ( Yamaoka et al., 2017). The implementation of SALIBU has been successful in different areas and at different elevations and groundwater levels in Indonesia ( Fitri et al., 2019), and has recently spread to Myanmar ( Yamaoka et al., 2017).

However, even if the similar conditions, in some cases, the yield is less than 50% of the main crop yield ( Pasaribu et al., 2018). This means the robustness of SALIBU cropping method is not enough. To adapt the SALIBU cropping method to areas with different growing conditions, we should evaluate the performance of each management practice, and modify the practices to suit the conditions. We aimed to adapt the SALIBU method to direct seeding triple-cropping of rice in the Mekong Delta, so that we evaluated the effect size of each practice and that robustness. Here, we found that the most effective (positive) management practice under poor conditions had an adverse effect (negative) under standard conditions. Furthermore, we found that the practice has a robust negative effect on the yields under both poor and standard conditions.

The pot experiment was conducted in a fine net house at Can Tho University (Can Tho city, Vietnam) from December 2018 to June 2019. We used 38 cm × 58 cm wide and 30 cm high containers. All containers were filled up to 20 cm with paddy soil. The soil was collected from topsoil (about 25 cm) of a paddy field at TL2 Hamlet, Thuan Hung village, Thot Not district, Can Tho city, Vietnam, just after natural flooding of the Mekong River and used on the day it was collected. The soil was well mixed in advance. Germinated seeds (Jasmin 85 variety from Can Tho University, popular in the Mekong Delta) were used. Jasmin is an Indica and has characteristics unsuitable for ratoon cropping of rice ( Negalur et al., 2017). These disadvantages will amplify the effects of the practices. We used urea (46% N), single superphosphate (16% P ₂O ₅), and potassium chloride (61% K ₂O) as fertlizers; the applied amount of those contents (kg ha ^-1) used for each treatment are given in the following section.

SALIBU management consists of cutting near the ground and nine special management practices in addition to the conventional cropping management practice of rice transplanting ( Yamaoka et al., 2017). The practice of early harvesting (physiological maturity; 25% green color husk) is conventional in Mekong Delta triple-cropping cultivation. The rest of the practices are as follows. (1) Pre-fertilization: 25 kg ha ⁻¹ N and 46.75 kg ha ⁻¹ P ₂O ₅ at seven days before harvesting. (2) Cutting twice: all rice was harvested 25 cm above the ground, then cut again beneath the first node above ground on day seven (or day zero for control plants) after harvesting (rice straws were returned to the ground). The recommendation is to cut 3–5 cm above ground; we kept only the node below ground. (3) Late irrigation: irrigation was started on day 14 (or day seven for control plants) after harvesting (the water table was about 5 cm until irrigation started). (4) Adjusting: the practice consisted of (a) hand weeding, (b) dividing hills into two or three tillers and replanting to fill the space, (c) pushing the rice plants into the soil if the root came up on soil surface, (d) removing excess plants to keep original plant density, and (e) draining from day 29 to 43 after harvesting (though (e) is not “adjusting”, it is technically inseparable because “adjusting” requires draining). We did the pot experiment using an L ₁₆ orthogonal array design ( Oda et al., 2019). We set the pots randomly in the fine net house.

The standard conditions were based on the standard of direct seeding triple-cropping rice in the Mekong Delta: the plant density was 230 kg ha ⁻¹ dry weight (about 173 seeds per pot), fertilizer was applied three times on day seven (27.6 kg ha ^-1 N, 45.2 kg ha ^-1 P ₂O ₅, 3.68 kg ha ^–1 K ₂O), 20 (36.7 kg ha ^-1 N), and 42 (27.6 kg ha ^-1 N, 3.68 kg ha ^-1 K ₂O) after seeding, with alternate wet and dry water management (15 to 5 cm; from seven days after seeding to 10 days before harvesting).

The poor conditions were as follows: low plant density (nine plants per pot), no fertilization (except the pre-fertilization treatment), continuous flooding water management (0 to 5 cm, from seven days after seeding to 10 days before harvesting), and late harvesting (seeded 10 days before the standard condition plants and harvesting on the same day of harvesting as the standard conditions). These conditions are known to negatively affect ratoon cropping of rice ( Negalur et al., 2017).

We recorded the number of plants and ratoon tillers at the harvesting time. We immediately oven-dried the sample then weighed the grain and straw. We analyzed the effect of the practices using the mean value and Cohens’ d effect size using the following formula ( Cohen, 1992): d = M 1 − M 2 S D 1 2 + S D 2 2 2 where, d is the effect size, M ₁ is the mean of treatment, M ₂ is the mean of un-treatment, and SD is standard deviation.

The p value of the significance test is affected by the sample size and cannot be used to assess the effect. Measuring effect sizes allows for evaluation involving variance and is not affected by the sample size. Data were processed using Microsoft Excel 2016.

The ratoon rice yield was proportional to straw biomass. The harvest index under poor conditions was higher than that under standard conditions ( Figure 1). Importantly, straw biomass was proportional to the number of ratoon tillers under both conditions ( Figure 2). The ratoon rice yield is determined by the number of ratoon tillers, and the relationship between the number of ratoon tillers and the yield is consistent with those reported in a previous study ( Pasaribu et al., 2018). The number of ratoon tillers was also in proportion to the number of plants under poor conditions ( Figure 3), although it is important to note that under poor conditions, half of the pots had no ratoons.

We examined the effect of management practices such as pre-fertilization, cutting twice, late irrigation, and adjusting on the number of ratoon tillers.

Importantly, the effect of cutting twice was positive under poor conditions but was negative under standard conditions. In other words, there is an interaction between the practice and the condition. The average cutting heights (length of the first node) of the standard condition plants were 5.5 cm (cutting twice) and 4.0 cm (harvesting time), and those of the poor conditions were 6.8 cm and 3.0 cm, respectively. The extensions of nodes were smaller under standard conditions than those under poor conditions. There is no consensus about the ideal cutting height ( Negalur et al., 2017), although previous studies were not carried out using the SALIBU method.

Furthermore, late irrigation had a negative effect on the number of ratoon tillers under both conditions ( Table 1). This might be a drawback of the pot experiment method due to decreased percolation; however, this is unlikely because the SALIBU method is successful in the lowlands ( Fitri et al., 2019).

Effect sizes provide an evaluation involving variance and are not affected by the sample size. The effect sizes of Cohen’s d < 0.2, 0.5, 0.8, and 1.2, and d > 2.0 correspond to small, medium, large, very large, and huge, respectively ( Cohen, 1992; Sawilowsky, 2009). Figure 4 shows the relationship of the effect sizes between the conditions. The effect on ratoon tillers ( Figure 4, left) and on yield ( Figure 4, right) was similar but the effect on tillers was high under poor conditions. Pre-fertilization, cutting twice, and late irrigation had medium to large effect sizes. When the effect is near the 1:1 line, the effect is independent of the condition and is robust. A non-robust effect signifies an interaction between the practice and the conditions. Positive large effects were shown under poor conditions only.

For the effects of SALIBU management on ratoon tillers, we found an interaction between cutting twice and the cultivation conditions (standard and poor). However, the poor conditions consisted of four factors, which are as follows: low plant density, no fertilization, continuous flooding water management, and late harvesting. Therefore, which of the factors interacts with cutting twice should be clarified. The extensions of nodes by cutting twice shows the reason; although, we cannot say the meaning.

Late irrigation has a robust negative effect. We can erase the negative effect by simply removing the practice. On the other hand, early irrigation may have a positive effect. In this way, an agricultural cropping method may include negative management practices if the effects are not evaluated. Our method is useful for screening positive practices in cropping methods.

Adjusting has a robust small effect and therefore, implementation should depend on a cost-benefit analysis. In contrast, pre-fertilization has a small effect under standard conditions, but has a large effect under poor conditions. The difference shows an interaction between the practice and the condition; however, this is reasonable because the plants under poor conditions were unfertilized.

SALIBU achieved more yield than the main crop and enables the perennial cropping; however, its adaptability is unclear. Although evaluating each practice in a cropping method under different conditions is difficult because of the huge number of potential combinations, we overcame this difficulty by using an orthogonal array design pot experiment and duplicating the experiment under standard and poor conditions. Our results show that the SALIBU cropping method includes practices with unstable, negative, or small effect sizes. Improving the use of these practices could improve the method. Practices with unstable effects should be used when known to have a positive effect under a specific condition. Negative effects can be excluded by excluding the practice. Small effect practices should be used depending on the outcome of a cost-benefit analysis. Perennial ratoon rice cropping will be possible for Mekong Delta triple-cropping rice without the nine special management practices of the original SALIBU cropping method, because most of the effects of practices under standard conditions are small or negative. The triple-cropping is different with the Indonesian rice cropping; therefore, SALIBU practices should be evaluated for the Indonesian rice cropping.

Figshare: Salibu Effect. https://doi.org/10.6084/m9.figshare.9937928.v1 ( Oda et al., 2019)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).