agronomy

Article A Novel Compost for Rice Cultivation Developed by Rice Industrial By-Products to Serve Circular Economy

Kalliopi Kadoglidou, Argyris Kalaitzidis, Dimitrios Stavrakoudis , Aggeliki Mygdalia and Dimitrios Katsantonis *

Institute of plant Breeding and Genetic Resources, Hellenic Agricultural Organization—DEMETER, Thermi, Thessaloniki GR-57001, Greece * Correspondence: [email protected]; Tel.: +30-2310-471-544



Received: 18 July 2019; Accepted: 12 September 2019; Published: 15 September 2019


Abstract: Rice is the major staple crop worldwide, whereas fertilization practices include mainly the application of synthetic fertilizers. A novel compost was developed using 74% of rice industrial by-products (rice bran and husks) and tested in rice cultivation in Greece’s main rice producing area. Field experimentation was conducted in two consecutive growing seasons (2017 and 2018) and 1 comprised six fertilization treatments, including four compost rates (C1: 80, C2: 160, C3: 320 kg ha− 1 of nitrogen all in split application, C4: 160 kg ha− of nitrogen in single application), a conventional treatment, as well as an untreated control. A total of 21 morpho-physiological and quality traits were evaluated during the experimentation. The results indicated that rice plants in all compost treatments had greater height (8%–64%) and biomass (32%–113%) compared to the untreated control. In most cases, chlorophyll content index (CCI) and quantum yield (QY) were similar or higher in C3 compared 1 to the conventional treatment. C2 and C3 exhibited similar or greater yields, 7.5–8.7 Mg ha− in 1 1 2017 and 6.3–6.9 Mg ha− in 2018, whereas the conventional treatment resulted in 7.3 Mg ha− and 1 6.8 Mg ha− in the two years, respectively. No differences were observed in most quality traits that affect the rice commodity. The current study reveals that in sustainable farming systems based on circular economy, such as organic ones, the application of the proposed compost at the rate of 1 6 Mg ha− can be considered sufficient for the rice crop nutrient requirements.

Keywords: rice bran; husks; paddy rice residues; organic fertilizer; plant growth; renewable inputs

1. Introduction Conventional agriculture plays the most significant role in meeting the food demands of the growing human population. However, the massive application of chemical fertilizers has disturbed field management, increasing the problem of soil, ground water, and air pollution at a global scale. Consequently, an increase in fertilizer application and a rise in the final food product prices has been observed, whereas the concerns of the farmers and the consumers are evident. Recent efforts have targeted toward the development of a healthier and nutrient rich food of high quality in sustainable comportments to ensure bio-safety. In agriculture, alternate means of soil fertilization relies on the organic inputs to boost nutrient supply and maintain the field management. The use of composts and biofertilizers is within the scope of a sustainable agricultural system that provides an ecologically healthy and economically viable crop production, especially when they are derived by low-value by-products of the cultivated plants like rice (Oryza sativa L.). Rice is a highly nutritious cereal that can be used as the source of several bioactive compounds. Specifically, brown rice is an excellent source of complex carbohydrates, vitamins, minerals, phytosterols,

Agronomy 2019, 9, 553; doi:10.3390/agronomy9090553 www.mdpi.com/journal/agronomy Agronomy 2019, 9, 553 2 of 18 and dietary fibers [1]. However, because of the global preference for consumption of milled rice, most nutritional parts of the grain are lost during the milling process by the removal of the pericarp, the seed shell, and the embryo of the grain, known as rice bran (RB), which contains rice bran oil and holds approximately 10% of the overall rice yield [2]. RB is rich in protein, vitamins, essential minerals, and antioxidant compounds [3]. Previous studies indicated the possible use of RB as a natural fertilizer containing 2.5% nitrogen, 3% phosphorus, 2.3% potassium, and 1% magnesium, whereas the C/N ratio is approximately 19 [4]. It is estimated that the world annual production of RB amounts to 76 million tons [5,6]. Another notable product derived from the de-husking process in rice mills is the seed shells, known as husks or hulls. These are parts of the rice seed (palea and lemma) and they represent 20%–22% of the milling process’s residuals [7]. Rice husks (RH) are composed of 28% cellulose, 28.6% hemicelluloses, 24.4% lignin, and 18.4% extractive matter [8]. According to Vadivel and Brindha [9], the global production of RH is very significant and falls in the range of 20 million tons annually. Therefore, the utilization of the RH is of high importance. Since RH are inedible by humans, but suitable for animal feed [10], they can be used in various non-food applications. The most important uses of RH are the production of energy (fuel) and ethanol, the pyrolysis for silicon dioxide production [7], the smoking of foods, and the acceleration of the bioremediation process into the soil [11]. Ogbo and Odo [12] confirmed the suitability of RH as a carrier for biofertilizer production. Moreover, Evans and Gachukia [13] reported that parboiled fresh husks can be used as a low cost perlite substitute in greenhouse substrates without any significant reduction in plant growth or quality, while at rates up to 40% (v/v) no significant reduction was observed impacting plant tissue N (without N depletion). Extracts from RH act not only against phytopathogenic fungi, such as root rot seedling rice [14], but also against algae [15] and bacteria [16]. Expanding the positive effects of RH on rice straw, Iranzo et al. [17] found that the characteristics (physical, chemical, microbiological properties) of the rice straw were complementary to those of the sewage sludge for their application as a compost. Despite the fact that the activity of RB and RH were investigated intensively, especially the antioxidant activity of RB and the phytochemical of RH, their simultaneous exploitation in sustainable farming systems has not yet been deeply investigated. The aim of the current study is to investigate the potential use of a natural fertilizer, produced by rice by-products such as a combination of RB and RH, in rice cultivation through the evaluation of agronomic and physiological parameters, as well as of rice productivity and quality indices, serving the principals of circular economy. Extending the research outcomes, this natural RB fertilizer can be utilized in organic rice cultivation.

2. Materials and Methods

2.1. Site and Climatic Conditions Two field experiments were conducted in two consecutive years, 2017 and 2018, at the Experimental Station of Kalochori, Thessaloniki, Greece (40◦36058.75” N, 22◦49051.16” E). The soil consisted of 22% 1 clay, 50% silt, 28% sand, with 2.84% organic matter, electrical conductivity 1.3 dS m− and pH 7.5. Temperature and relative humidity were constantly recorded throughout both cultivation periods, in order to compare the annual meteorological datasets. Table1 presents the monthly averages of temperature and relative humidity during the two growing seasons of the experimentation, with the values being the norm of a typical Mediterranean climate. Agronomy 2019, 9, 553 3 of 18

Table 1. Monthly temperature and relative humidity during the rice growing seasons in 2017 and 2018 at the experimental site. Minimum, maximum, and average values of each year are reported, averaged over each month.

Temperature ( C) Relative Humidity (%) Year Month ◦ Agronomy 2019, 9, x FOR PEER REVIEWMinimum Maximum Average Minimum Maximum Average 3 of 18 June 18 32 25 50 84 61 AugustJuly 18 19 34 34 24 26 60 5398 9679 73 2017 August 18 34 24 60 98 79 SeptemberSeptember 14 14 32 32 21 21 52 5297 9778 78 October 13 13 28 28 19 19 43 4389 8969 69 JuneJune 20 20 32 32 25 25 51 5191 9172 72 JulyJuly 19 19 33 33 26 26 50 5096 9673 73 2018 August 19 34 25 62 100 87 2018 SeptemberAugust 19 16 34 31 25 22 62 68 100 100 87 90 SeptemberOctober 16 11 31 26 22 18 68 51 100 95 90 79 October 11 26 18 51 95 79 2.2. Compost Preparation and Properties 2.2. Compost Preparation and Properties Initially, the compost formula was developed in preliminary experiments during 2016, where the compostingInitially, mixture the compost was placed formula under was a PolyVinyldeveloped Chloride in preliminary (PVC) PVCexperiments soil cover during sheet and2016, exposed where theto an composting aerobic digestion mixture in was heaps placed of approximately under a PolyVinyl 1.5 1.5 Chloride0.5 m2 (PVC)volume PVC Figure soil1 a.cover The sheet materials and × × 2 wereexposed mixed to an at aerobic a weekly digestion basis, whereas in heaps moisture of approximately was controlled 1.5 × 1.5 at × 40%–60% 0.5 m volume by watering Figure 1(a). with The tap materials were mixed at a weekly basis, whereas moisture was controlled at 40%–60% by watering water every 5 days. The temperature was checked to be never above 60–65 ◦C at the center of the pile with tap water every 5 days. The temperature was checked to be never above 60–65 °C at the center using a hand-held thermometer. A temperature of 60–65 ◦C was not surpassed, to avoid alterations of the pile using a hand-held thermometer. A temperature+ of 60–65 °C was not surpassed, to avoid that might take place in the microflora and losses of NH4 -N. The composting process was performed + alterationsfor at least 40that days, might while take the place C/N in ratiothe microflora was being and checked losses on of a NH frequent4 -N. The basis. composting process was performed for at least 40 days, while the C/N ratio was being checked on a frequent basis.

(a) (b)

Figure 1. The materials during composting process (a) and the compost bin (b). Figure 1. The materials during composting process (a) and the compost bin (b). In 2017 and 2018, all raw materials were placed into a custom automatic composting bin of 1.5 MgIn capacity2017 and designed 2018, all raw and constructedmaterials were by DEMETER’splaced into a teamcustom to optimizeautomatic the composting process [Figure bin of1 1.5b]. TheMg capacity materials designed were mixed and thoroughly constructed every by DEMETER’s 5 days, the moistureteam to optimize was kept the between process 40%–60%, [Figure while1(b)]. The materials were mixed thoroughly every 5 days, the moisture was kept between 40%–60%, while the compost temperatures were ranging between 60–65 ◦C. The materials were left for at least 40 days theto complete compost thetemperatures composting were process, ranging when between the C/ N60–65 ratio °C. reached The materials a value lowerwere left than for 12. at least 40 days to completeThe raw the materials composting used process, for the compost when the consisted C/N ratio of reached rice milling a value industry lower by-products than 12. at a level of 74%The approximately. raw materials Theused compost for the compost consisted consisted of: 160 kgof RBrice (65.5%), milling 20industry kg RH by-products (8.2%), 40 kg at organic a level ofchicken 74% approximately. manure (CM) (16.4%),The compost 24 kg consisted zeolite (9.8%), of: 160 and kg 0.333RB (65.5%), kg of “Neudor 20 kg RHff Radivit”(8.2%), 40 commercial kg organic chickencompost manure accelerator (CM) (0.1%), (16.4%), containing 24 kg zeolite several (9.8%), species and of Bacillus0.333 kgspp. of “Neudorff and Aspergillus Radivit”spp. commercialto facilitate composthumification. accelerator In general, (0.1%), the co majorityntaining of several the species species of of the Bacillus microorganisms spp. and Aspergillus in the compost spp. to accelerator facilitate humification.belong to the genusIn general,Bacillus the, whichmajority transform of the spec nitriteies of to the nitrate, microorganisms whereas the moldin the fungi, compostAspergillus acceleratorsp., belong to the genus Bacillus, which transform nitrite to nitrate, whereas the mold fungi, Aspergillus sp., transforms and mineralizes cellulose, lignin, and oily matter. In addition, after the second week of the composting process two different species at the larval stage were recorded in the composting materials: (i) the black soldier fly, Hermetia illucens (Diptera: Stratiomyidae) and (ii) the domestic fly, Musca domestica (Diptera: Muscidae). Laboratory analysis of the raw materials was carried out, while the samples were collected before mixing and during the composting process. The results are reported in Table 2. Specifically, total organic carbon (C), total nitrogen (N), available phosphorus (P), potassium (K), calcium (Ca), Agronomy 2019, 9, 553 4 of 18

Agronomy 2019, 9, x FOR PEER REVIEW 4 of 18 transforms and mineralizes cellulose, lignin, and oily matter. In addition, after the second week of and magnesium (Mg) were determined by the following standard analytical methods: total organic the composting process two different species at the larval stage were recorded in the composting carbon content by the wet oxidation method [18], total nitrogen by macroKjeldahl method, available materials: (i) the black soldier fly, Hermetia illucens (Diptera: Stratiomyidae) and (ii) the domestic fly, phosphorus by Olsen’s method [19], whereas potassium and selected macro- and micronutrients by Musca domestica (Diptera: Muscidae). atomic emission spectrometry with inductively coupled plasma (ICP-AES). The pH of the mature Laboratory analysis of the raw materials was carried out, while the samples were collected compost ranged between 6.3 and 7.8, whereas the electrical conductivity was 0.73 dS m−1. before mixing and during the composting process. The results are reported in Table2. Specifically, total organic carbon (C), total nitrogen (N), available phosphorus (P), potassium (K), calcium (Ca), Table 2. Laboratory analysis of the main raw materials (RH, RB, CM, and zeolite), the initial and magnesium (Mg) were determined by the following standard analytical methods: total organic composting mixture at 0 days, and the composting mixture at 20 and 40 days (mature compost), carbonutilized content in 2017 by and the 2018 wet experimentation. oxidation method [18], total nitrogen by macroKjeldahl method, available phosphorus by Olsen’s method [19], whereas potassium and selected macro- and micronutrients by Laboratory analysis before, during, and at the end of the atomic emission spectrometry with inductively coupled plasma (ICP-AES). The pH of the mature 1 compost ranged between 6.3 and 7.8, whereas the electricalcomposting conductivity process was 0.73 dS m− . C/N Material TOC% TΝ% P % Κ % Ca % Mg % Table 2. Laboratory analysis of the main raw materialsratio (RH, RB, CM, and zeolite), the initial composting RHmixture (raw material) at 0 days, and the47.05 composting 0.29 mixture 162.2 at 20 and 400.04 days (mature0.13 compost), 0.11 utilized in0.04 2017 RBand (raw 2018 material) experimentation. 41.02 2.37 17.3 1.99 1.78 0.80 0.83

CM (raw material) 40,60Laboratory 4.00 Analysis 10,15Before, During, 4.25 and at the 4.50 End of the Composting 3.50 Process0.12 Zeolite (raw material) - - - 0.009 1.52 2.17 0.63 Material TOC% TN% C/N Ratio P % K % Ca % Mg % Composting RH (raw material)44.05 47.05 2.26 0.29 19.5 162.2 2.20 0.04 2.31 0.13 3.08 0.11 0.93 0.04 mixture/0RB (raw days material) 41.02 2.37 17.3 1.99 1.78 0.80 0.83 CompostingCM (raw material) 40,60 4.00 10,15 4.25 4.50 3.50 0.12 34.70 2.15 16.1 2.81 2.14 3.75 1.30 mixture/20Zeolite (raw days material) - - - 0.009 1.52 2.17 0.63 Composting mixture/0 days 44.05 2.26 19.5 2.20 2.31 3.08 0.93 CompostingComposting mixture /20 days 34.70 2.15 16.1 2.81 2.14 3.75 1.30 Composting mixture (Mature compost)/40 25.3025.30 2.65 2.65 9.5 9.5 2.65 2.65 2.00 2.00 2.60 2.60 1.12 1.12 (Maturedays compost) /40 days TOC, total organic carbon; TN, total nitrogen; C/N ratio, carbon/nitrogen ratio; P, phosphorous; K, potassium; TOC, total organic carbon; TN, total nitrogen; C/N ratio, carbon/nitrogen ratio; P, phosphorous; K, Ca, calcium; Mg, magnesium. potassium; Ca, calcium; Mg, magnesium. 2.3. Experimental Setup 2.3. Experimental Setup The size of each experimental plot area was 11 m2 (5 2.5 m), whereas the experiment was The size of each experimental plot area was 11 m2 (5 × ×2.5 m), whereas the experiment was arranged in a randomized complete block design (Figure2), with five replications for each treatment arranged in a randomized complete block design (Figure 2), with five replications for each treatment and six fertilization treatments. and six fertilization treatments.

Figure 2. Experimental setup (RGB image taken by drone). Differences between fertilization Figure 2. Experimental setup (RGB image taken by drone). Differences between fertilization treatments treatments in biomass and green color are visible from early stages. in biomass and green color are visible from early stages.

The fertilization treatments were: compost application of (i) 80 kg ha−1 N1 (C1) in split application, The fertilization treatments were: compost application of (i) 80 kg ha− N (C1) in split application, (ii) 160 kg ha−1 N1 in split application (C2), (iii) 320 kg ha−1 N (C3) in split application, (iv) 160 kg ha1−1 (ii) 160 kg ha− N in split application (C2), (iii) 320 kg ha− N (C3) in split application, (iv) 160 kg ha− N N in single application (C4), (v) an untreated control (CONTR) and (vi) 160 kg ha−1 nitrogen1 chemical in single application (C4), (v) an untreated control (CONTR) and (vi) 160 kg ha− nitrogen chemical fertilizerfertilizer (standard (standard fertilization fertilization practice) practice) (CONVEN). (CONVEN). The The C2 C2 treatment treatment had had nitrogen nitrogen units units equivalent equivalent with that of the CONVEN, whereas the C4 treatment was included in the study to evaluate the efficiency of the compost as a slow release fertilizer. Beside C4, the fertilization scheme followed the local and international standard practices for rice cultivation, where the amount is divided in three Agronomy 2019, 9, 553 5 of 18 with that of the CONVEN, whereas the C4 treatment was included in the study to evaluate the efficiency of the compost as a slow release fertilizer. Beside C4, the fertilization scheme followed the local and international standard practices for rice cultivation, where the amount is divided in three increments: 40% of N units are incorporated as basal before flooding, 40% is applied at the tillering stage and similarly the rest 20% at the panicle initiation stage. Before flooding and sowing, the basic fertilization was achieved with the incorporation of compost treatments in each plot into the upper 5–10 cm of the soil, using a plot rotary tiller machine. At tillering and at panicle initiation stages, the compost treatments were achieved as surface fertilization. The different types of soil treatments and their abbreviations are presented in Table1. According to (i) the nitrogen concentration of mature compost presented in Table2 and (ii) the amount of nitrogen units presented in Table3, the relative amount of compost at C1, C2, C3, and C4 treatment is 3.0, 6.0, 1 12.0, and 6.0 Mg ha− , respectively.

Table 3. Different fertilization treatments, their abbreviations, and the amount of nitrogen units 1 (kg ha− ) were used at different stages during the rice-growing season (before sowing, at tillering, and at panicle initiation).

Second Surface Fertilization Basic Fertilization First Surface Fertilization Treatment 1 1 (at Panicle Initiation), (Before Sowing), kg ha− (at Tillering), kg ha− 1 kg ha− C1 32 32 16 C2 64 64 32 C3 128 128 64 C4 160 0 0 CONTR 0 0 0 CONVEN 64 64 32

Seeds (0.220 kg) of the Greek commercial variety DION (japonica type), which belongs to the European Core Collection, were directly seeded into each of the flooded plots on 9 June 2017 and on 6 June 2018, respectively. Besides fertilization, plots treated with compost were kept free from weeds by hand weeding, whereas standard cultural practices for rice cultivation were conducted including harrowing, tillage, and lazier leveling. The experiments were harvested when the plants reached the physiological maturity stage on 10 October 2017 and 9 October 2018, respectively.

2.4. Growth Parameters During the experimentation period, the following traits were assessed at various stages: (1) Plant height (PH; cm) at 42, 60, and 80 days after the sowing (DAS), by measuring the main shoot from the ground level up to the tip of the largest leaf stretched of 30 random rice plants per plot; (2) total dry 1 aboveground biomass (BT; Mg ha− ) at 85 DAS and at maturity stage, by cutting three random samples from each plot at ground level, covering an area of 0.25 m2, and weighting it after drying for 48–72 h in 1 2 an air oven at 70 ◦C until constant weight; (3) grain yield (Mg ha− ) by cutting two samples of 1 m each per plot, the plants were cut at the ground level and they were harvested by using an electric panicle harvester.

2.5. Physiological Parameters The chlorophyll content of the leaves was measured at 32, 42, 62, 90, and 105 DAS using a portable chlorophyll content meter (CCM-200, Opti-Sciences, Tyngsboro, MA, USA). For this purpose, ten measurements were acquired from different plants in each plot, from the second youngest leaf (counting from the plant apex) of the main shoot with the same orientation toward the sun. At 32, 62, 90, and 105 DAS, the quantum yield (QY) of photochemical energy conversion at PSII was measured at midday, using a FluorPen FP100 (Photon Systems Instruments, Brno, Czech Republic) on light-adapted leaves. For this purpose, ten measurements were taken in each plot, from the upper Agronomy 2019, 9, 553 6 of 18 third of the second youngest leaf (counting from the plant apex) of the main shoot, with the same orientation toward the sun [20]. Based on the phenological growth/BBCH stages, the 32, 62, 90, and 105 DAS, in which CCI and QY were measured, corresponded to the tillering stage, booting stage, filling stage, and maturity stage, respectively. The harvest index (HI) was also calculated as the ratio of grain yield to total dry aboveground biomass. HI is considered as a measure of biological success in partitioning assimilated photosynthate to the harvestable product [21].

2.6. Phenotypic and Quality Analysis Brown rice was obtained using a dehusker machine (Taka Yama, TW Grandeur Machinery Co., Taichung, Taiwan), whereas white rice was obtained subsequently using a whitening machine (SATAKE type TM 05C, OLMIA). Total milling yield (TMY) was determined as the percentage ratio of dehulled (brown) rice grains’ weight to the paddy rice weight, whereas the 100 grains weight (100GW) was determined using a precision electronic scale model KERN 573 (Kern & Sohn Gmbh, D-72336, Balingen, Germany). Whole milling yield (WMY), percentage of chalkiness (CH), as well as the grains’ dimensions paddy rice length (PL), width (PW), and length/width ratio (PR), the brown rice length (BL), width (BW), and length/width ratio (BR), the white rice length (WL), width (WW), and length/width ratio (WR) were determined by measuring the two samples of 100 grains for each plot, using the SeedCount SC4 digital imaging seed analyzer (SeedCount Australasia, Condell Park, Australia). Finally, amylose content (%, AMY) was determined in all the samples as per the procedure of ISO 6647 [22].

2.7. Statistical Analysis The statistical analysis (ANOVA) was carried out using the computer software MSTAT-C version 1.41 (Michigan State University, East Lansing, MI). All measures and derived data were objected to a combined over-year analysis of variance (Experiment Model Number 15, One Factor Randomized Complete Block Design Combined over Years), with compost treatment as the main factor. In cases where the factor year was significant, the data were objected to analysis of variance separately for each year (Experiment Model 7 Number, One Factor Randomized Complete Block Design). Fisher’s Protected LSD procedures were used to detect and separate mean treatments differences at p < 0.05. The combined analysis of data was justified following the Bartlett’s test for homogeneity of variances, which indicated that data were not heterogeneous.

3. Results and Discussion The laboratory analysis results of the main raw material of compost (Table2), i.e., the RB, agrees with those of Hossain et al. [4], who report that RB has about 2.51% nitrogen, 1.99% phosphorus, 1.78% potassium, and C/N ratio 19. The key element of the composting process is the production of a stable and mature end-product, suitable to be applied as fertilizer or soil amendment [23]. In our study, the C/N ratio was stabilized very soon (approximately in 40 days) at values below 12, revealing that the maturing of compost was achieved. This significant reduction of C/N ratio indicates a rather fast decomposition of the organic material added and subsequent nutrient release, which is arguably attributed to the enhancement of raw materials with the compost accelerator, as well as to their colonization with insect populations. Additionally, the nitrogen content of the mature compost was 2.65% and very close to that of the initial mixture (2.26%) (Table2). This reveals that during the composting process no nitrogen losses—which could have been caused by the nitrification of nitrate to nitrite and the evaporation of ammonia nitrogen—took place. According to Hao and Benke [24] the main form of N lost during composting is ammonia emission ranging from by 13% to 70%. The same authors reported that this wide variations appeared because of the differences in the properties of the raw material used, environmental conditions, and compost management practices. Zhu [25] composted swine manure and rice straw. They concluded that a lower initial C/N ratio of 20 by raw material Agronomy 2019, 9, 553 7 of 18 caused a higher N loss by 8% than that C/N ratio 25 caused. Additionally, Wong et al. [26] found that the use of zeolite in composting process appears promising since zeolite leads to the adsorption and precipitation of ammonia. Findings of Wong et al. [26] might partially explain the lack of nitrogen losses observed in our study. Generally, in our study, factors like the initial C/N ratio 19.5, the preservation of temperature above 60–65 ◦C, and the use of zeolite among raw material might be contributed to the lack of nitrogen losses during composting. Temperature and relative humidity in 2017 were slightly lower than 2018 (Table1). However, these differences are rather marginal and cannot possibly induce any significant changes in the morphophysiological and quality traits of the rice plants between the two years. Generally, the statistical analysis of the growth and physiological traits showed significant effects because of the years (Y), the compost treatment (T), and in some cases, their interactions (Tables4 and5 ). Nevertheless, statistical analysis of the quality traits of rice indicated that, in most cases, the effect of the year, the compost treatment, and their interaction were non-significant (Table5). Agronomy 2019, 9, 553 8 of 18

Table 4. Analysis of variance (one factor randomized complete block design combined over years) of the agronomic and physiological traits as influenced by the compost treatments.

Significance of F Ratio Source df PH42 PH60 PH80 BT85 BTM CCI32 CCI42 CCI62 CCI90 CCI105 QY32 QY62 QY90 QY105 Yield Year (Y) 1 ** * ** ** NS ** ** NS NS ** * NS * NS NS Error 8 NS Treatment 5 ** ** ** ** ** ** ** ** ** ** * NS * ** ** (T) Y x T 5 ** ** ** ** NS ** ** NS ** * NS NS * NS * Error 40 CV 4.35 5.91 4.07 11.53 11.06 14.58 9.41 9.57 9.85 11.87 5.67 4.18 5.11 5.76 11.27 CV, coefficient of variation; df, degree of freedom; NS, nonsignificant; * p < 0.05 level of significance; ** p < 0.01 level of significance; PH42, PH60, PH80: plant height at 42, 60, 80 DAS (days after sowing); BT85, BTM: biomass total at 85 DAS and at maturity; CCI32, CCI42, CCI62, CCI90, CCI105: chlorophyll content index at 32, 42, 62, 90, and 105 DAS; QY32, QY62, QY90, QY105: quantum yield at 32, 62, 90, and 105 DAS; yield: grains yield at maturity; p for Year (Y) p = 0.0557.

Table 5. Analysis of variance (one factor randomized complete block design combined over years) of the agronomic, qualitative, and physico-chemical traits as influenced by the compost treatments.

Significance of F Ratio Source df HI NGM TMY WMY PL PW PR BL BW BR WL WW WR 100GW CH AMY Year (Y) 1 NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS NS Error 8 Treatment (T) 5 ** ** NS NS NS * NS NS ** ** NS ** ** NS ** NS Y x T 5 NS * NS NS NS NS NS NS NS NS NS * NS NS NS NS Error 40 CV 10.39 5.65 0.86 4.31 1.37 1.44 1.58 0.56 2.43 3.02 1.38 0.97 1.32 10.64 19.70 5.96 CV, coefficient of variation; df, degree of freedom; NS, nonsignificant; * p < 0.05 level of significance; ** p < 0.01 level of significance; HI: harvest index; NGM: % nitrogen at grains at maturity; TMY: total milling yield, WMY: whole milling yield; PL, PW, PR: paddy rice length, width, and length/width ratio; BL, BW, BR: brown rice length, width and length/width ratio; WL, WW, WR: white rice length, width, and length/width ratio; 100GW: weight of 100 grains; CH: % chalkiness; AMY: % amylose. Agronomy 2019, 9, 553 9 of 18

Concerning the plant height, the ANOVA indicated that rice height at 42, 60 and 80 DAS was affected by the year (Y), the compost treatment (T), and their Y T interactions (Table4). Thus, × mean values are presented separately for each year in Figure3a and 3b, respectively. For the same reason (ANOVA in Table4), the total dry aboveground biomass at 85 DAS is presented separately for each year Figure4a,b. In the 2017 experiment and at 42, 60, and 80 DAS, the compost application in paddies resulted in significantly higher (8%–46% average increase in height) and heavier (32%–70% average increase in dry aboveground biomass) plants compared to those of the control treatment Figures3a and4a . Similar but more pronounced results were obtained in the 2018 experiment, since at 42, 60, and 80 DAS the compost application resulted in significant higher (8%–64%) and heavier Agronomy(77%–113%) 2019, 9 plants, x FOR comparedPEER REVIEW to those of the control treatment Figures3b and4b. 10 of 18

2017 LSD = 2.84 2018 LSD42 DAS = 2.84 LSD60 DAS = 4.31 42 DAS 60 DAS 80 DAS 60 DAS 42 DAS 60 DAS 80 DAS LSD80 DAS = 3.30 80 DAS a a a 100 a b 100 b c b b c d a d d c a 80 a e a 80 cd c 80 a e a 80 d b b b b e b a c cd e 60 b a 60 d cd c b cd c d c cd e d a a 40 e 40 c bc a ab a 40 40 c bc d Plant height (cm) height Plant (cm) height Plant Plant height (cm) height Plant 20 (cm) height Plant 20

0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Treatment Treatment

(a) (b)

FigureFigure 3. 3. HeightHeight of of rice rice plants plants (means (means ± se)se) grown grown in in differently differently fertilized fertilized soil soil at at 42, 42, 60, 60, and and 80 80 days days ± afterafter the the sowing sowing (DAS) (DAS) of of the the experiment experiment during during 2017 2017 (a (a) )and and 2018 2018 ( (bb).). Treatments Treatments contain contain compost compost −1 1 −1 1 applicationapplication of of (i) (i) 80 80 kg kg ha ha−1 −N inN split in split application application (C1), (C1), (ii) (ii)160 160kg ha kg−1ha N− in Nsplit in splitapplication application (C2), (C2),(iii) −1 1 −1 1 320(iii) kg 320 ha kg−1 N ha in− splitN in splitapplication application (C3), (C3), (iv) (iv)160 160kg kgha− ha1 N− inN single in single application application (C4), (C4), (v) (v) an an untreated untreated −1 1 controlcontrol (CONTR), (CONTR), and and (vi) (vi) 160 160 kg kg ha ha−1− nitrogennitrogen chemical chemical fertilizer fertilizer (CONVEN). (CONVEN). Means Means were were compared compared byby the the Bonferroni Bonferroni adjusted adjusted LSD LSD value value at at pp << 0.05.0.05. Different Different letters letters charac characterizeterize significant significant differences differences betweenbetween treatments treatments for for each each DAS. DAS. Full Full description description of of the the treatments treatments examined examined is is given given in in Table Table 33..

2017 2018 2017 LSD = 0.912 2018 LSD85 DAS = 1.57 LSD85 DAS = 0.912 LSD85 DAS = 1.57 85 DAS 85 DAS 16 10 16 a a a ab 14 bc 8 c 12 c 12 b bc 10 c c 6 d 8 d 4 6 d 4 2 2 2 0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Total Dry Aboveground Aboveground Dry Biomass Total(tn/ha)

Tota Dry Aboveground DryAboveground Tota Biomass(tn/ha) Treatment Total Dry Aboveground Aboveground Dry Biomass Total(tn/ha)

Tota Dry Aboveground DryAboveground Tota Biomass(tn/ha) Treatment Treatment (b) (a) (b)

FigureFigure 4. 4. TotalTotal dry dry aboveground biomassbiomass ofof rice rice plants plants (means (means ±se) se) grown grown in in di ffdifferentlyerently fertilized fertilized soil ± soilat85 at days85 days after after the sowingthe sowing (DAS) (D ofAS) the of experiment the experiment during during 2017 (a2017) and (a 2018) and ( b2018). Treatments (b). Treatments contain 1 −1 1 −1 containcompost compost application application of (i) 80 of kg (i) ha −80 Nkg in ha split−1 N application in split application (C1), (ii)160 (C1), kg (ii) ha −160N kg in splitha−1 applicationN in split 1 −1 1 −1 application(C2), (iii) 320 (C2), kg ha(iii)− 320N inkg split ha−1 applicationN in split application (C3), (iv) 160 (C3), kg ha(iv)− 160N inkg single ha−1 N application in single application (C4), (v) an 1 (C4),untreated (v) ancontrol untreated (CONTR), control and(CONTR), (vi) 160 and kg ha(vi)− 160nitrogen kg ha chemical−1 nitrogen fertilizer chemical (CONVEN). fertilizer (CONVEN). Means were Meanscompared were by compared the Bonferroni by the adjustedBonferroni LSD adjusted value atLSDp < value0.05. at Di pff

20 a a 16 b b 12 c d 8

4

0 C1 C2 C3 C4 CONTR CONVEN Total Dry Aboveground Biomass (tn/ha) (tn/ha) Biomass Aboveground Dry Total Total Dry Aboveground Biomass (tn/ha) (tn/ha) Biomass Aboveground Dry Total Treatment

Agronomy 2019, 9, x FOR PEER REVIEW 10 of 18

2017 2018 LSD42 DAS = 2.84 LSD = 4.31 42 DAS 60 DAS 80 DAS 60 DAS 42 DAS 60 DAS 80 DAS LSD80 DAS = 3.30 a a 100 b 100 b c d a d cd c 80 a e a 80 d b b b b e a c cd 60 b c 60 d d c cd e e a ab a 40 40 c bc d

Plant height (cm) height Plant 20 (cm) height Plant 20

0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Treatment Treatment

(a) (b)

Figure 3. Height of rice plants (means ± se) grown in differently fertilized soil at 42, 60, and 80 days after the sowing (DAS) of the experiment during 2017 (a) and 2018 (b). Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments for each DAS. Full description of the treatments examined is given in Table 3.

2017 2018 LSD85 DAS = 0.912 LSD85 DAS = 1.57 85 DAS 85 DAS

10 16 a a ab 14 8 bc c c 12 b bc 10 c c 6 d 8 4 6 d 4 2 2 0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Total Dry Aboveground Aboveground Dry Biomass Total(tn/ha)

Tota Dry Aboveground DryAboveground Tota Biomass(tn/ha) Treatment Treatment

(a) (b)

Figure 4. Total dry aboveground biomass of rice plants (means ± se) grown in differently fertilized soil at 85 days after the sowing (DAS) of the experiment during 2017 (a) and 2018 (b). Treatments Agronomy 2019contain, 9, 553 compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split 10 of 18 application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). 61%–73%Means of the were CONVEN compared biomass. by the Bonferroni In both adjusted years, LSD plant value biomass at p < 0.05. at maturityDifferent letters in C3 characterize was similar to that in the CONVENsignificant treatment differences (Figure between5 ).trea Summarizingtments. Full description biomass of results, the treatments the C3 examined treatment is exhibitedgiven in similar biomass toTable CONVEN 3. throughout the season (except of 85 DAS in 2018).

2017 and 2018 LSD = 1.27 Maturity

20 a a 16 b b 12 c d 8

4

0 C1 C2 C3 C4 CONTR CONVEN

Total Dry Aboveground Biomass (tn/ha) (tn/ha) Biomass Aboveground Dry Total Treatment

Figure 5. Total dry aboveground biomass of rice plants (means se) grown in differently fertilized soil ± at maturity stage of the experiments during 2017 and 2018. Treatments contain compost application of 1 1 1 (i) 80 kg ha− N in split application (C1), (ii) 160 kg ha− N in split application (C2), (iii) 320 kg ha− N 1 in split application (C3), (iv) 160 kg ha− N in single application (C4), (v) an untreated control (CONTR), 1 and (vi) 160 kg ha− nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. Full description of the treatments examined is given in Table3.

The application of the C3 compost treatment had the most pronounced effect on plant biomass at maturity over the application of recommended inorganic fertilizer (CONVEN). In most cases, maximum plant height was observed in the C3 and CONVEN treatments. The increase in plant height and biomass is arguably attributed to the enhanced nutrient level induced in the soil by the compost, which leads to the continuous assimilation of nutrients in available forms by the plants (or to a slow release fertilization). This hypothesis for the positive effect of compost in plant height and biomass has also been made by other researchers [27,28]. Concerning the physiological traits, the results showed significant Y T interaction for CCI, × with the exception of 62 DAS showing significant difference only for T factor (Table4). Thus, the mean values for each compost treatment are presented separately in Figure6. The CCI values ranged between 5.3 and 6.9 at 32 DAS, 12.9 and 16.5 at 62 DAS, 17.9 and 26.7 at 90 DAS, and 11.6 and 17.1 at 105 DAS. The CCI showed an increase during the season up to 90 DAS—as the plants were growing—and an expected decline at 105 DAS, since the plants entered the maturity phase. Generally, the CCI in C3 was similar or higher (18% at 32 DAS) compared to the CONVEN treatment (Figure6). Similarly, the CCI in C1, C2, and C4 was similar to the CONVEN one at 32 DAS, but lower by 12% to 23% at 62, 92, and 105 DAS. Based on the phenological growth/BBCH stages, the mean CCI values in the current study for the tillering stage, booting stage, filling stage, and maturity stage were 6.0, 16.9, 23.0, and 14.2, respectively. In accordance, Liu et al. [29] concluded that at the same growth stages the median CCI values were 21.1, 43.1, 41.1, and 18.9, respectively. In both studies, the CCI values followed the same trend: a growth path until the filling stage and then a decrease until the maturity stage. Nevertheless, for the same growth stages, the CCI values were quite lower in our study. According to Peng et al. [30], CCI is a good indicator for the evaluation of compost effects on rice cultivation, whereas chlorophyll meters can be used for monitoring leaf nitrogen status in rice, since rice plants with higher nitrogen content have higher chlorophyll content and consequently higher CCI values [31]. Chlorophyll provides an indication of the nutritional status as a result of nitrogen absorption and utilization, which serves as a reliable means to estimate the function of the nitrogen fertilizer [29] and this is confirmed from our results. Agronomy 2019, 9, x FOR PEER REVIEW 11 of 18

Figure 5. Total dry aboveground biomass of rice plants (means ± se) grown in differently fertilized soil at maturity stage of the experiments during 2017 and 2018. Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. Full description of the treatments examined is given in Table 3.

Concerning the physiological traits, the results showed significant Y × T interaction for CCI, with the exception of 62 DAS showing significant difference only for T factor (Table 4). Thus, the mean values for each compost treatment are presented separately in Figure 6. The CCI values ranged between 5.3 and 6.9 at 32 DAS, 12.9 and 16.5 at 62 DAS, 17.9 and 26.7 at 90 DAS, and 11.6 and 17.1 at 105 DAS. The CCI showed an increase during the season up to 90 DAS—as the plants were growing— and an expected decline at 105 DAS, since the plants entered the maturity phase. Generally, the CCI in C3 was similar or higher (18% at 32 DAS) compared to the CONVEN treatment (Figure 6). Similarly, the CCI in C1, C2, and C4 was similar to the CONVEN one at 32 DAS, but lower by 12% to 23% at 62, 92, and 105 DAS. Based on the phenological growth/BBCH stages, the mean CCI values in the current study for the tillering stage, booting stage, filling stage, and maturity stage were 6.0, 16.9, 23.0, and 14.2, respectively. In accordance, Liu et al. [29] concluded that at the same growth stages the median CCI values were 21.1, 43.1, 41.1, and 18.9, respectively. In both studies, the CCI values followed the same trend: a growth path until the filling stage and then a decrease until the maturity stage. Nevertheless, for the same growth stages, the CCI values were quite lower in our study. According to Peng et al. [30], CCI is a good indicator for the evaluation of compost effects on rice cultivation, whereas chlorophyll meters can be used for monitoring leaf nitrogen status in rice, since rice plants with higher nitrogen content have higher chlorophyll content and consequently higher CCI values [31]. Chlorophyll provides an indication of the nutritional status as a result of nitrogen Agronomyabsorption2019, 9, 553 and utilization, which serves as a reliable means to estimate the function of the nitrogen11 of 18 fertilizer [29] and this is confirmed from our results.

2017 and 2018

32 DAS 42 DAS 62 DAS 90 DAS 105 DAS

30 a a b 25 b c a a 20 a d b b b a b b bc c 15 c a c b 10 d a ab c e bc c e bc 5 ChlorophyllIndex, CCI Content 0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 6. Chlorophyll content index (CCI) of rice plants (means se) grown in differently fertilized ± soil atFigure 32, 42, 6. 62, Chlorophyll 90, and 105 content days index after the(CCI) sowing of rice (DAS) plants of(means the experiments ± se) grown duringin differently 2017 and fertilized 2018. soil at 32, 42, 62, 90, and 105 days after the sowing (DAS)1 of the experiments during 2017 and 2018.1 Treatments contain compost application of (i) 80 kg ha− N in split application (C1), (ii) 160 kg ha− N Treatments contain compost application1 of (i) 80 kg ha−1 N in split application (C1), (ii)1 160 kg ha−1 N in split application (C2), (iii) 320 kg ha− N in split application (C3), (iv) 160 kg ha− N in single in split application (C2), (iii) 320 kg ha−1 N in split application (C3),1 (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha− nitrogen chemical fertilizer application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters Agronomycharacterize 2019, 9, significantx FOR PEER di REVIEWfferences between treatments for each DAS. Full description of the treatments12 of 18 characterize significant differences between treatments for each DAS. Full description of the examined is given in Table3. treatments examined is given in Table 3. Quantum yield (QY) from 32 to 105 DAS was mainly affected by the compost treatment (T) (TableQuantum 4). Thus, yield the (QY)mean from values 32 for to each 105 DAScompos wast treatment mainly a areffected presented by the separately compost treatmentat different(T)

(TableDAS4 ).in Thus, Figure the 7. Plants mean valuesexhibited for similar each compost QY across treatment the different are presented treatments, separately except in atthe di casesfferent of 90 DAS inand Figure 1057 .DAS. Plants More exhibited specifically, similar at 90 QY DAS across plants the tr dieatedfferent with treatments, compost had except up to in 7% the higher cases QY of than 90 and 105the DAS. CONVEN, More specifically, whereas at at105 90 DAS DAS only plants plants treated at C3 with had compost 7% higher had quantum up to 7% yield higher compared QY than to the CONVEN,CONVEN. whereas at 105 DAS only plants at C3 had 7% higher quantum yield compared to CONVEN.

2017 and 2018 LSD 32DAS = 0.03 LSD 62DAS = 0.03 32 DAS 62 DAS 90 DAS 105 DAS LSD 90DAS = 0.03 LSD 105DAS = 0.03 0.8

a ab a a 0.7 bc a a c a a a a a ab a abc b b abc b b bc c 0.6

Quantum Yield Quantum c

0.5 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 7. Quantum yield of rice plants (means se) grown in differently fertilized soil at 32, 62, 90, ± andFigure 105 days 7. Quantum after the yield sowing of rice (DAS) plants of (means the experiments ± se) grown during in differently 2017 and fertilized 2018. Treatments soil at 32, 62, contain 90, 1 1 compostand 105 application days after ofthe (i) sowing 80 kg ha(DAS)− N of in the split expe applicationriments during (C1), (ii)2017 160 and kg 2018. ha− NTreatments in split application contain 1 1 (C2),compost (iii) 320 application kg ha− N ofin (i) split 80 kg application ha−1 N in split (C3), application (iv) 160 kg (C1), ha− (ii)N 160 in kg single ha−1 applicationN in split application (C4), (v) an 1 untreated(C2), (iii) control 320 kg (CONTR), ha−1 N in split and (vi)application 160 kg ha(C3),− nitrogen(iv) 160 kg chemical ha−1 N in fertilizer single application (CONVEN). (C4), Means (v) an were compareduntreated by control the Bonferroni (CONTR), adjustedand (vi) 160 LSD kg value ha−1 nitrogen at p < 0.05. chemical Different fertilizer letters (CONVEN). characterize Means significant were diffcomparederences between by the Bonferroni treatments adjusted for each LSD DAS. value Full at description p < 0.05. Different of the treatments letters characterize examined significant is given in Tabledifferences3. between treatments for each DAS. Full description of the treatments examined is given in Table 3.

Regarding the yield, the effect of compost treatment and the Y × T were significant (Table 4). For this reason, the means presented in Figure 8a,b are not averaged across years, in order to investigate the effect of year on the yield of different treatments. C2 and CONVEN in 2017, which received similar N units, resulted in very similar yields, 7.5 Mg ha−1 and 7.3 Mg ha−1, respectively. Additionally, yield obtained by C1 (half N dose) was significantly lower (−12%) than that of CONVEN and C3 (double N dose) exhibited significantly higher (19%) yield compared to the CONVEN treatment Figure 8a. Similar results were observed in 2018, where the yield of C2, C3, and C4 did not differ significantly compared to the CONVEN one (6.3–6.9 Mg ha−1) Figure 8b. In conclusion, C2 and C3 showed a more consistent behavior across the two years of experimentation compared to the other treatments. Siavoshi and Laware [32] reported that 4 Mg ha−1 of an organic fertilizer comprising 25% of rice straw and husks and 75% by cow and poultry manure increased the yield by 19% (4.7 Mg ha−1). In the present study, the application of 3.0 Mg ha−1 of compost (C1 treatment) increased the yield to 28.5% compared to the CONTR (untreated). However, we decided to focus the discussion on the comparison with the conventional fertilization treatment, in order to give a more complete view of the use of the natural fertilizer instead of the synthetic ones. From this point of view, the addition of 6.0 Mg ha−1 of compost (C2 treatment) in the soil produced similar yield with that of the CONVEN treatment. The application of 6.0 Mg ha−1 of compost to the soil led to an impressive yield increase in both years, 38% in 2017 and 66% in 2018 compared to the CONTR. We hypothesized that these increases appeared because of the improvement in soil fertility because of compost incorporation and most likely because of its main components RH and RB, specifically. Moreover, the used compost had a low C/N ratio (9.5), potentially able to drive a fast release of mineral nitrogen into the soil. The

Agronomy 2019, 9, 553 12 of 18

Regarding the yield, the effect of compost treatment and the Y T were significant (Table4). × For this reason, the means presented in Figure8a,b are not averaged across years, in order to investigate the effect of year on the yield of different treatments. C2 and CONVEN in 2017, which received similar 1 1 N units, resulted in very similar yields, 7.5 Mg ha− and 7.3 Mg ha− , respectively. Additionally, yield obtained by C1 (half N dose) was significantly lower ( 12%) than that of CONVEN and C3 (double N − dose) exhibited significantly higher (19%) yield compared to the CONVEN treatment Figure8a. Similar results were observed in 2018, where the yield of C2, C3, and C4 did not differ significantly compared 1 to the CONVEN one (6.3–6.9 Mg ha− ) Figure8b. In conclusion, C2 and C3 showed a more consistent behavior across the two years of experimentation compared to the other treatments. Siavoshi and 1 Laware [32] reported that 4 Mg ha− of an organic fertilizer comprising 25% of rice straw and husks 1 and 75% by cow and poultry manure increased the yield by 19% (4.7 Mg ha− ). In the present study, 1 the application of 3.0 Mg ha− of compost (C1 treatment) increased the yield to 28.5% compared to the CONTR (untreated). However, we decided to focus the discussion on the comparison with the conventional fertilization treatment, in order to give a more complete view of the use of the natural 1 fertilizer instead of the synthetic ones. From this point of view, the addition of 6.0 Mg ha− of compost (C2 treatment) in the soil produced similar yield with that of the CONVEN treatment. The application 1 of 6.0 Mg ha− of compost to the soil led to an impressive yield increase in both years, 38% in 2017 and 66% in 2018 compared to the CONTR. We hypothesized that these increases appeared because of the Agronomyimprovement 2019, 9, x in FOR soil PEER fertility REVIEW because of compost incorporation and most likely because of its13 mainof 18 components RH and RB, specifically. Moreover, the used compost had a low C/N ratio (9.5), potentially effectivenessable to drive of a fastRH releasein compost of mineral and in nitrogenbiofertilize intor production the soil. The is ewellffectiveness docume ofnted. RH Pode in compost [33] refers and thatin biofertilizer the fertilization production of paddy is well fields documented. with RH ash Pode waste [33 increases] refers that the theconcentration fertilization of of silicic paddy acid fields in thewith soil, RH yielding ash waste a rich increases harvest the of concentrationrice. Similarly, of Mohamed silicic acid et in al. the [34] soil, found yielding that RH a rich are harvest a renewable of rice. sourceSimilarly, for the Mohamed production et al. of [ 34zeolite,] found which that is RH used are as a renewablea soil amendment. source for the production of zeolite, which is used as a soil amendment.

2017 LSD = 0.74 2018 LSD = 1.06 10 10 a

8 b bc 8 a a d cd ab a 6 6 bc e c 4 4 Rice Yield (tn/ha) Yield Rice

2 (tn/ha) Yield Rice 2

0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Treatment Treatment

(a) (b)

FigureFigure 8. 8. YieldYield of rice of rice plants plants (means (means ± se) grownse) grown in differe in dintlyfferently fertilized fertilized soil of the soil experiment of the experiment during ± −1 1 2017during (a) and 2017 2018 (a) and (b). 2018Treatments (b). Treatments contain compost contain application compost application of (i) 80 kg ofha (i) N 80 in kg split ha− applicationN in split −1 1 −1 1 (C1),application (ii) 160 (C1),kg ha (ii) N 160 in kgsplit ha application− N in split (C2), application (iii) 320 (C2), kg ha (iii) N 320 in kgsplit ha application− N in split (C3), application (iv) 160 (C3), kg −1 1 −1 1 ha(iv) N 160 in kg single ha− applicationN in single application(C4), (v) an (C4), untreated (v) an control untreated (CONTR), control (CONTR),and (vi) 160 and kg (vi) ha 160 nitrogen kg ha− chemicalnitrogen fertilizer chemical (CONVEN). fertilizer (CONVEN). Means were Means compar wereed compared by the Bonferroni by the Bonferroni adjusted adjusted LSD value LSD at value p < 0.05.at p

TheThe HI HI was was affected affected by by the the compost compost treatment treatment (Tab (Tablele 5).5). The The HI HI of of C1, C1, C2, C2, and and C4 C4 was was similar, similar, whereaswhereas the the HI HI of CONVEN was significantlysignificantly lowerlower (Figure(Figure9 ),9), because because of of their their higher higher biomass biomass rate rate at atmaturity. maturity. The The HI HI of of C3 C3 did did not not diff differer from from the th respectivee respective of C2 of andC2 and CONVEN. CONVEN. This This means means that thesethat thesetreatments treatments resulted resulted in biomass in biomass increases, increase buts, without but without a significant a significant yield yield increase. increase.

2017 and 2018 LSD = 0.05 0.8

a 0.6 a ab a bc c 0.4 Harvest Index 0.2

0.0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 9. Harvest index (HI) (means ± se) of rice plants grown in differently fertilized soil of the experiments during 2017 and 2018. Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. Full description of the treatments examined is given in Table 3.

Agronomy 2019, 9, x FOR PEER REVIEW 13 of 18 effectiveness of RH in compost and in biofertilizer production is well documented. Pode [33] refers that the fertilization of paddy fields with RH ash waste increases the concentration of silicic acid in the soil, yielding a rich harvest of rice. Similarly, Mohamed et al. [34] found that RH are a renewable source for the production of zeolite, which is used as a soil amendment.

2017 LSD = 0.74 2018 LSD = 1.06 10 10 a

8 b bc 8 a a d cd ab a 6 6 bc e c 4 4 Rice Yield (tn/ha) Yield Rice

2 (tn/ha) Yield Rice 2

0 0 C1 C2 C3 C4 CONTR CONVEN C1 C2 C3 C4 CONTR CONVEN Treatment Treatment

(a) (b)

Figure 8. Yield of rice plants (means ± se) grown in differently fertilized soil of the experiment during 2017 (a) and 2018 (b). Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. Full description of the treatments examined is given in Table 3.

The HI was affected by the compost treatment (Table 5). The HI of C1, C2, and C4 was similar, whereas the HI of CONVEN was significantly lower (Figure 9), because of their higher biomass rate atAgronomy maturity.2019 ,The9, 553 HI of C3 did not differ from the respective of C2 and CONVEN. This means13 that of 18 these treatments resulted in biomass increases, but without a significant yield increase.

2017 and 2018 LSD = 0.05 0.8

a 0.6 a ab a bc c 0.4 Harvest Index 0.2

0.0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 9. Harvest index (HI) (means se) of rice plants grown in differently fertilized soil of the ± 1 Figureexperiments 9. Harvest during index 2017 and(HI) 2018.(means Treatments ± se) of containrice plants compost grown application in differently of (i) fertilized 80 kg ha− soilN inof splitthe 1 1 experimentsapplication (C1), during (ii) 2017 160 kg and ha 2018.− N inTreatments split application contain (C2), compost (iii) 320 application kg ha− N of in (i) split 80 kg application ha−1 N in split (C3), 1 1 application(iv) 160 kg ha(C1),− N (ii) in 160 single kg ha application−1 N in split (C4), application (v) an untreated (C2), (iii) control320 kg ha (CONTR),−1 N in split and application (vi) 160 kg (C3), ha− (iv)nitrogen 160 kg chemical ha−1 N in fertilizer single (CONVEN).application (C4), Means (v) were an un comparedtreated control by the (CONTR), Bonferroni and adjusted (vi) 160 LSD kg value ha−1 nitrogenat p < 0.05. chemical Different fertilizer letters (CONVEN). characterize significantMeans were di comparedfferences between by the Bonferroni treatments. adjusted Full description LSD value of Agronomy 2019, 9, x FOR PEER REVIEW 14 of 18 atthe p treatments< 0.05. Different examined letters is givencharacterize in Table significan3. t differences between treatments. Full description of the treatments examined is given in Table 3. The N concentration inin ricerice grainsgrains waswas aaffectedffected by by the the treatment treatment and and by by Y Y ×T T interactions interactions (Table (Table5, × 5,Figure Figure 10 ).10). The The C2, C2, C3, C3, and and CONVEN CONVEN treatments treatments resulted resulted in similar in similar nitrogen nitrogen concentration concentration in grains, in grains,whereas whereas N in C1 N and in C1 C4 and were C4 12% were and 12% 16% and lower, 16% respectively, lower, respectively, compared compared to CONVEN. to CONVEN.

2017 and 2018 LSD = 0.057 1.5 a a a b b b 1.0

0.5 Percentage Nitrogen at grains(%) 0.0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 10. Percentage nitrogen at grains (means se) harvested by rice plants grown in differently ± Figurefertilized 10. soilPercentage of the experiments nitrogen at duringgrains 2017(means and ± 2018.se) harvested Treatments by rice contain plants compost grown applicationin differently of 1 1 1 fertilized(i) 80 kg ha soil− ofN thein split experiments application during (C1), 2017 (ii) 160 and kg 2018. ha− TreatmentsN in split application contain compost (C2), (iii) application 320 kg ha of− (i)N 1 80in splitkg ha application−1 N in split (C3), application (iv) 160 kg(C1), ha− (ii)N 160 insingle kg ha application−1 N in split (C4),application (v) an untreated (C2), (iii)control 320 kg (CONTR),ha−1 N in and (vi) 160 kg ha 1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni split application (C3),− (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni Full description of the treatments examined is found in Table3. adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments.In terms of Full the description quality traits, of the the treatments analysis examined of PW, BW, is found BR, WW, in Table and 3. WR indicated that the effect of compost treatment was significant, whereas the Y T interaction was significant only for WW In terms of the quality traits, the analysis of PW, BW,× BR, WW, and WR indicated that the effect of compost treatment was significant, whereas the Y × T interaction was significant only for WW (Table 5). Therefore, the mean values presented in Figure 11(a) to (c) are averaged across years. In most cases, a constant trend was observed and this was rather expected, since these traits are varietal and it is very unlikely to observe big differences by simply altering the fertilization treatment. Nevertheless, at C3 treatment the width of paddy, brown and white rice grains presented the lowest values—albeit not statistically significant in some cases—whereas the length/width ratio of brown and white rice grains exhibited the highest values and they differed significantly from the CONVEN.

2017 and 2018 LSDPW = 0.04 LSDBW = 0.06 PW BW BR WW WR LSDBR = 0.07 LSDWW = 0.03 LSD = 0.08 4 WR a a b b ab b 3 a a a a a a a a a ab b b b a b b b bc ab a bc b c b 2

1

Ricegrains (mm) dimensions 0 C1 C2 C3 C4 CONTR CONVEN Treatment

Agronomy 2019, 9, x FOR PEER REVIEW 14 of 18

The N concentration in rice grains was affected by the treatment and by Y × T interactions (Table 5, Figure 10). The C2, C3, and CONVEN treatments resulted in similar nitrogen concentration in grains, whereas N in C1 and C4 were 12% and 16% lower, respectively, compared to CONVEN.

2017 and 2018 LSD = 0.057 1.5 a a a b b b 1.0

0.5 Percentage Nitrogen at grains(%) 0.0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 10. Percentage nitrogen at grains (means ± se) harvested by rice plants grown in differently fertilized soil of the experiments during 2017 and 2018. Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments. Full description of the treatments examined is found in Table 3. Agronomy 2019, 9, 553 14 of 18 In terms of the quality traits, the analysis of PW, BW, BR, WW, and WR indicated that the effect of compost treatment was significant, whereas the Y × T interaction was significant only for WW (Table 55).). Therefore,Therefore, thethe meanmean valuesvalues presentedpresented inin FigureFigure 11 11(a)a–c areto (c) averaged are averaged across across years. years. In most In mostcases, cases, a constant a constant trend trend was observed was observed and this and was this rather was rather expected, expected, since thesesince traitsthese aretraits varietal are varietal and it andis very it is unlikely very unlikely to observe to bigobserve differences big differences by simply alteringby simply the fertilizationaltering the treatment.fertilization Nevertheless, treatment. Nevertheless,at C3 treatment at theC3 widthtreatment of paddy, the width brown of paddy, and white brown rice and grains white presented rice grains the lowestpresented values—albeit the lowest values—albeitnot statistically not significant statistically in some significant cases—whereas in some cases—whereas the length/width the ratio length/width of brown ratio and whiteof brown rice andgrains white exhibited rice grains the highest exhibited values the highest and they values differed and significantly they differed from significantly the CONVEN. from the CONVEN.

2017 and 2018 LSDPW = 0.04 LSDBW = 0.06 PW BW BR WW WR LSDBR = 0.07 LSDWW = 0.03 LSD = 0.08 4 WR a a b b ab b 3 a a a a a a a a a ab b b b a b b b bc ab a bc b c b 2

1

Ricegrains (mm) dimensions 0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 11. Width of paddy (PW), width (BW) and length/width ratio (BR) of brown, and width (WW) and length/width ratio (WR) of white rice grains (means se), harvested of rice plants grown ± in differently fertilized soil of the experiments during 2017 and 2018. Treatments contain compost 1 1 application of (i) 80 kg ha− N in split application (C1), (ii) 160 kg ha− N in split application (C2), 1 1 (iii) 320 kg ha− N in split application (C3), (iv) 160 kg ha− N in single application (C4), (v) an untreated 1 control (CONTR), and (vi) 160 kg ha− nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments for each parameter. Full description of the treatments examined is given in Table3.

With respect to 100GW, TMY, and WMY no differences were observed across the years, compost treatments, and Y T interaction (Table5). Milling yield, which is a very important parameter × tightly connected with the value of the rice commodity in the industry, did not exhibit any significant differences among the different fertilization treatments. Thus, it is safe to conclude that the use of the compost did not underrate the commodity value. This contradicts with the findings of McClung [35], who concluded that cultural management methods like fertilization can affect the quality parameters such as total and whole milling yield. It is noteworthy that the grain CH was affected by the compost treatment (Table5) and in C3 it was significantly lower (28%) than the respective one in CONVEN, whereas C1 and C2 resulted in 15% to 21% lower—albeit not statistically significant—CH (Figure 12). Finally, AMY did not differ significantly among all treatments (Table5). Agronomy 2019, 9, x FOR PEER REVIEW 15 of 18

Figure 11. Width of paddy (PW), width (BW) and length/width ratio (BR) of brown, and width (WW) and length/width ratio (WR) of white rice grains (means ± se), harvested of rice plants grown in differently fertilized soil of the experiments during 2017 and 2018. Treatments contain compost application of (i) 80 kg ha−1 N in split application (C1), (ii) 160 kg ha−1 N in split application (C2), (iii) 320 kg ha−1 N in split application (C3), (iv) 160 kg ha−1 N in single application (C4), (v) an untreated control (CONTR), and (vi) 160 kg ha−1 nitrogen chemical fertilizer (CONVEN). Means were compared by the Bonferroni adjusted LSD value at p < 0.05. Different letters characterize significant differences between treatments for each parameter. Full description of the treatments examined is given in Table 3.

With respect to 100GW, TMY, and WMY no differences were observed across the years, compost treatments, and Y × T interaction (Table 5). Milling yield, which is a very important parameter tightly connected with the value of the rice commodity in the industry, did not exhibit any significant differences among the different fertilization treatments. Thus, it is safe to conclude that the use of the compost did not underrate the commodity value. This contradicts with the findings of McClung [35], who concluded that cultural management methods like fertilization can affect the quality parameters such as total and whole milling yield. It is noteworthy that the grain CH was affected by the compost treatment (Table 5) and in C3 it was significantly lower (28%) than the respective one in CONVEN, whereasAgronomy C12019 and, 9, C2 553 resulted in 15% to 21% lower—albeit not statistically significant—CH (Figure 1512). of 18 Finally, AMY did not differ significantly among all treatments (Table 5).

2017 and 2018 LSD = 0.95 20 18 a a a 16 ab 14 ab b 12 10 8 6 4 2

Percentage of grainchalkiness (%) 0 C1 C2 C3 C4 CONTR CONVEN Treatment

Figure 12. The percentage of grains with chalkiness (means se) of grains harvested of rice plants ± Figuregrown 12. inThe di ffpercentageerently fertilized of grains soil with of thechalkiness experiments (means during ± se) 2017of grains and harvested 2018. Treatments of rice plants contain 1 1 growncompost in differently application fertilized of (i) 80 kgsoil ha of− theN in ex splitperiments application during (C1), 2017 (ii) 160and kg2018. ha− TreatmentsN in split applicationcontain 1 −1 1 −1 compost(C2), (iii) application 320 kg ha of− (i)N 80in splitkg ha application N in split (C3),application (iv) 160 (C1), kg ha (ii)− 160N in kg single ha N application in split application (C4), (v) an −1 1 −1 (C2),untreated (iii) 320 control kg ha (CONTR), N in splitand application (vi) 160 kg(C3), ha− (iv)nitrogen 160 kg chemicalha N in fertilizer single application (CONVEN). (C4), Means (v) an were untreatedcompared control by the (CONTR), Bonferroni and adjusted (vi) 160 LSDkg ha value−1 nitrogen at p < chemical0.05. Diff fertilizererent letters (CONVEN). characterize Means significant were compareddifferences by the between Bonferroni treatments adjusted for LSD each value parameter. at p < 0.05. Full descriptionDifferent letters of the characterize treatments significant examined is differencesgiven in Tablebetween3. treatments for each parameter. Full description of the treatments examined is given in Table 3. Summarizing, the results of the study indicated that the application of the proposed compost at 1 theSummarizing, rate of 6 Mg ha the− resultscan be consideredof the study su indicatedfficient for th theat the rice application crop nutrient of the requirements proposed evencompost from at the thefirst rate year of 6of Mg application. ha−1 can be In considered contrast,Moe sufficient et al. [for36] the refer rice that crop organic nutrient fertilizers requirements (like compost even from made thefrom first kitchenyear of application. waste and bamboo)In contrast, with Moe total et al. N [36]< 4% refer were that only organic effective fertilizers at improving (like compost rice made growth fromand kitchen yield inwaste the secondand bamboo) year, after withbeing total N continuously < 4% were only applied effective for 2at years. improving In order rice togrowth understand and yieldthe in socio-economic the second year, implications after being of continuously the use of the applied novel compost, for 2 years. a cost In order analysis to forunderstand its production the socio-economicwas performed implications in 2016, during of the theuse preliminary of the novel phase compost, of our a cost study analysis [37]. Thefor its results production revealed was that performedthe proposed in 2016, compost during has the the preliminary potential to phase increase of our the study gross value[37]. The of riceresults production, revealed specifically, that the proposedin organic compost farming has systems. the potential However, to increase compost the production gross value and of application rice production, cannot specifically, always improve in both the economic and social impacts at the same time. Although some of the compost treatments

resulted in similar soil fertility rates, which are eco-friendly, more technological interventions (such as the enrichment of raw material with materials of high potential in N units) are required to make it as effective as the conventional fertilization, so that rice growers can be motivated to adopt such eco-friendly alternatives in the future. This kind of compost reported in the present study can be also developed in small scale rice farming systems, aiming sustainability through circular economy principals, by reducing the cultivation costs and the environmental footprint of the rice cultivation. Taking into consideration that, at least presently, the complete replacement of chemical fertilizers with composts in crops may not be a realistic idea in the conventional cropping systems, the results of this study reveal that the proposed compost has a potential to be used as a supplementary in paddies in smaller farming systems, or in greenhouse or vegetable-based cultivations. In case of paddies, precision agriculture could be the used for compost application according to field variability and site-specific conditions [38]. Concerning the application of the novel compost in the field, nowadays, many companies have started to develop special spreaders of natural fertilizer and composts that can apply those amounts and particle types. Moreover, there are cases where these spreaders are GPS- and computer-driven (variable rate applicators) [39–43]. Thus, it is expected that in the near future more suitable equipment will be available in the market. Agronomy 2019, 9, 553 16 of 18

Finally, further research is needed in the direction of improving the compost, particularly by increasing the N content, in order to improve its effectiveness and consequently permit the application of smaller amounts of compost into the cropping system.

4. Conclusions In the current study an innovative approach is proposed to exploit the rice milling industrial by-products toward a more sustainable rice farming system with care to the environmental footprint reduction. The novel formulation serves the principals of the circular economy and, at the same time, it could be a valuable solution for sustainable organic farming systems. According to our results, 1 the application of 6.0 Mg ha− of compost into paddies can be considered sufficient for the rice crop nutrient requirements, without compromising yield and quality of the rice commodity.

Author Contributions: Data curation, K.K., A.M., D.S., and D.K.; formal analysis, A.K.; funding acquisition, D.K.; methodology, K.K., A.K., and D.K.; project administration, D.K.; supervision, K.K. and D.K.; writing—original draft, K.K. and A.M.; writing—review and editing, K.K.; D.S. and D.K. Funding: This research has received funding from the European Union’s Horizon 2020 research and innovation program AGROCYCLE under grant agreement No 690142. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

References

1. Wu, F.; Yang, N.; Touré, A.; Jin, Z.; Xu, X. Germinated brown rice and its role in human health. Crit. Rev. Food Sci. Nutr. 2013, 53, 451–463. [CrossRef][PubMed] 2. ISO Rice Bran—IRRI Rice Knowledge Bank. Available online: http://www.knowledgebank.irri.org/step-by- step-production/postharvest/rice-by-products/rice-bran (accessed on 21 June 2019). 3. Aguilar-Garcia, C.; Gavino, G.; Baragaño-Mosqueda, M.; Hevia, P.; Gavino, V.C. Correlation of tocopherol, tocotrienol, γ-oryzanol and total polyphenol content in rice bran with different antioxidant capacity assays. Food Chem. 2007, 102, 1228–1232. [CrossRef] 4. Hossain, S.T.; Sugimoto, H.; Asagi, N.; Araki, T.; Ueno, H.; Morokuma, M.; Kato, H. The use of desalinated-dried jellyfish and rice bran for controlling weeds and rice yield. J. Org. Syst. 2013, 1, 28–37. 5. Chiou, T.-Y.; Ogino, A.; Kobayashi, T.; Adachi, S. Characteristics and antioxidative ability of defatted rice bran extracts obtained using several extractants under subcritical conditions. J. Oleo Sci. 2013, 62, 1–8. [CrossRef][PubMed] 6. Friedman, M. Rice Brans, Rice Bran Oils, and Rice Hulls: Composition, Food and Industrial Uses, and Bioactivities in Humans, Animals, and Cells. J. Agric. Food Chem. 2013, 61, 10626–10641. [CrossRef] 7. Foo, K.Y.; Hameed, B.H. Utilization of rice husk ash as novel adsorbent: A judicious recycling of the colloidal agricultural waste. Adv. Colloid Interface Sci. 2009, 152, 39–47. [CrossRef][PubMed] 8. Lim, J.S.; Abdul Manan, Z.; Wan Alwi, S.R.; Hashim, H. A review on utilisation of biomass from rice industry as a source of renewable energy. Renew. Sustain. Energy Rev. 2012, 16, 3084–3094. [CrossRef] 9. Vadivel, V.; Brindha, P. Antioxidant property of solvent extract and acid/alkali hydrolysates from rice hulls. Food Biosci. 2015, 11, 85–91. [CrossRef] 10. Wang, Z.Y.; Yang, H.M.; Lu, J.; Li, W.Z.; Zou, J.M. Influence of whole hulled rice and rice husk feeding on the performance, carcass yield and digestive tract development of geese. Anim. Feed Sci. Technol. 2014, 194, 99–105. [CrossRef] 11. Souza, T.S.; Hencklein, F.A.; Angelis, D.F.; Gonçalves, R.A.; Fontanetti, C.S. The Allium cepa bioassay to evaluate landfarming soil, before and after the addition of rice hulls to accelerate organic pollutants biodegradation. Ecotoxicol. Environ. Saf. 2009, 72, 1363–1368. [CrossRef] 12. Ogbo, F.C.; Odo, M.O. Potential of Rice Husk and Cassava Peel as Carriers for Bio-fertilizer Production. Niger. J. Biotechnol. 2011, 23, 1–4. 13. Evans, M.R.; Gachukia, M. Fresh parboiled rice hulls serve as an alternative to perlite in greenhouse crop substrates. Hortscience 2004, 39, 232–235. [CrossRef] Agronomy 2019, 9, 553 17 of 18

14. Kong, C.-H.; Xu, X.-H.; Zhang, M.; Zhang, S.-Z. Allelochemical tricin in rice hull and its aurone isomer against rice seedling rot disease. Pest. Manag. Sci. 2010, 66, 1018–1024. [CrossRef][PubMed] 15. Chung, I.M.; Ali, M.; Ahmad, A.; Chun, S.C.; Kim, J.T.; Sultana, S.; Kim, J.S.; Min, S.K.; Seo, B.R. Steroidal constituents of rice (Oryza sativa) hulls with Algicidal and Herbicidal activity against blue-green algae and duckweed. Phytochem. Anal. 2007, 18, 133–145. [CrossRef][PubMed] 16. Kim, S.P.; Kang, M.Y.; Park, J.C.; Nam, S.H.; Friedman, M. Rice Hull Smoke Extract Inactivates Salmonella Typhimurium in Laboratory Media and Protects Infected Mice against Mortality. J. Food Sci. 2012, 77, 80–85. [CrossRef][PubMed] 17. Iranzo, M.; Cañizares, J.V.; Roca-Perez, L.; Sainz-Pardo, I.; Mormeneo, S.; Boluda, R. Characteristics of rice straw and sewage sludge as composting materials in Valencia (Spain). Bioresour. Technol. 2004, 95, 107–112. [CrossRef][PubMed] 18. Allison, F.E. Organic carbon. In Methods of Soil Analysis; Part II; American Society of Agronomy: Madison, WI, USA, 1965; pp. 1372–1376. 19. Olsen, S.R.; Cole, C.V.; Watanabe, F.S.; Dean, L.A. Estimation of Available Phosphorus in Soils by Extraction with

NaHCO3; USDA: Washington, DC, USA, 1954; Volume 939. 20. Oxborough, K.; Baker, N.R. Resolving chlorophyll a fluorescence images of photosynthetic efficiency into photochemical and non-photochemical components—Calculation of qP and Fv-/Fm-; Without measuring Fo. Photosynth. Res. 1997, 54, 135–142. [CrossRef] 21. Stavrakoudis, D.; Katsantonis, D.; Kadoglidou, K.; Kalaitzidis, A.; Gitas, I.Z. Estimating Rice Agronomic Traits Using Drone-Collected Multispectral Imagery. Remote Sens. 2019, 11, 545. [CrossRef] 22. International Organization for Standardization (ISO). Rice. Determination of Amylose Content; Reference number ISO/6647. 1st edn; International Organization for Standardization (ISO): Geneva, Switzerland, 1987; p. 3. 23. Kadoglidou, K.; Chalkos, D.; Karamanoli, K.; Eleftherohorinos, I.G.; Constantinidou, H.-I.A.; Vokou, D. Aromatic plants as soil amendments: Effects of spearmint and sage on soil properties, growth and physiology of tomato seedlings. Sci. Hortic. 2014, 179, 25–35. [CrossRef] 24. Hao, X.; Benke, M. Nitrogen Transformation and losses during composting and mitigation strategies. Dyn. Soil Dyn. Plant. 2008, 2, 10–18. 25. Zhu, N. Effect of low initial C/N ration on aerobic composting of swine manure with rice straw. Bioresour. Technol. 2007, 55, 9–13. [CrossRef][PubMed] 26. Wong, J.W.C.; Wang, X.; Selvam, A. Improving Compost Quality by Controlling Nitrogen Loss During Composting. In Current Developments in Biotechnology and Bioengineering; Elsevier: Amsterdam, The Netherlands, 2017; pp. 59–82. 27. Kavitha, R.; Subramanian, P. Effect of Enriched Municipal Solid Waste Compost Application on Growth, Plant Nutrient Uptake and Yield of Rice. J. Agron. 2007, 6, 586–592. 28. Diacono, M.; Montemurro, F. Long-term effects of organic amendments on soil fertility. A Review. Agron. Sustain. Dev. 2010, 30, 401–422. [CrossRef] 29. Liu, C.; Liu, Y.; Lu, Y.; Liao, Y.; Nie, J.; Yuan, X.; Chen, F. Use of a leaf chlorophyll content index to improve the prediction of above-ground biomass and productivity. Peer J. 2019, 6, e6240. [CrossRef][PubMed] 30. Peng, S.; Garcia, F.V.; Laza, R.C.; Sanico, A.L.; Visperas, R.M.; Cassman, K.G. Increased N-use efficiency using a chlorophyll meter on high-yielding irrigated rice. Field Crop. Res. 1996, 47, 243–252. [CrossRef] 31. Lee, Y.J.; Yang, C.M.; Chang, K.W.; Shen, Y. Effects of nitrogen status on leaf anatomy, chlorophyll content and canopy reflectance of paddy rice. Bot. Stud. 2011, 52, 295–303. 32. Siavoshi, M.; Laware, S.L. Organic Fertilizers Role on Antioxidant Enzymes in Rice (Oryza sativa L.). Int. J. Farm. Alli. Sci. 2013, 2, 1337–1342. 33. Pode, R. Potential applications of rice husk ash waste from rice husk biomass power plant. Renew. Sustain. Energy Rev. 2016, 53, 1468–1485. [CrossRef] 34. Mohamed, R.M.; Mkhalid, I.A.; Barakat, M.A. Rice husk ash as a renewable source for the production of zeolite NaY and its characterization. Arab. J. Chem. 2015, 8, 48–53. [CrossRef] 35. Mc Clung, A. Techniques for development of new cultivars. In Rice: Origin, History, Technology, and Production; John Wiley and Sons Inc.: Hoboken, NJ, USA, 2003; p. 190. 36. Moe, K.; Htwe, A.Z.; Thu, T.T.P.; Kajihara, Y.; Yamakawa, T. Effects on NPK status, growth, dry matter and yield of rice (Oryza sativa) by organic fertilizers applied in field condition. Agriculture 2019, 9, 109. [CrossRef] Agronomy 2019, 9, 553 18 of 18

37. Chen, W.; Oldfield, T.L.; Katsantonis, D.; Kadoglidou, K.; Wood, R.; Holden, N.M. The socio-economic impacts of introducing circular economy into Mediterranean rice production. J. Clean. Prod. 2019, 218, 273–283. [CrossRef] 38. Trivelli, L.; Apicella, A.; Chiarello, F.; Rana, R.; Fantoni, G.; Tarabella, A. From precision agriculture to Industry 4.0. Br. Food J. 2019, 121, 1730–1743. [CrossRef] 39. Newton Crouch Spreaders Compatible with Variable Rate Technology. Available online: http://newtoncrouch. com/spreaders/ (accessed on 11 September 2019). 40. Applying Compost on a Variable Rate with Bergmann Universal Spreader Variosix with TSW A 21. Available online: https://www.youtube.com/watch?v=92gqsnOrzQc (accessed on 11 September 2019). 41. Tips on Using Anaerobic Digestate as a Fertiliser. Available online: https://www.fwi.co.uk/arable/crop- management/nutrition-and-fertiliser/qa-using-anaerobic-digestate-fertiliser (accessed on 11 September 2019). 42. Proceeding with Precision. What Are the Benefits of Investing in and Using Precision Application Technology? Available online: https://www.manuremanager.com/proceeding-with-precision-30718/ (accessed on 11 September 2019). 43. Advanced Distribution for Centrifugal Fertilizer Spreaders. Available online: https://www.mondomacchina. it/en/advanced-distribution-for-centrifugal-fertilizer-spreaders-c2051 (accessed on 11 September 2019).

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).