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Individuation of the best agronomic practices for organic durum wheat cultivation in the Mediterranean environment: a multivariate approach

Individuation of the best agronomic practices for organic durum wheat cultivation in the... Background The main challenge of organic cereal systems is ensuring high yields and grain quality while maintain- ing pedo-environmental sustainability. Despite the potential benefits of organic farming systems, a debated limitation is their actual contribution to food security. Durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.], one of the most important staple food crops, is mainly grown in the Mediterranean environments, where farmers have to face profound inter-annual fluctuations in productions, expecially under organic system, due to prolonged drought and heat spells. With the overarching objective of deriving practical indications to support organic wheat production in the Mediterranean region, we tested the effect of nitrogen and sulphur-based organic foliar fertilizers on two ancient and two modern durum wheat varieties grown in two seasons (2018–2019) characterized by different weather condi- tions. Moreover, we evaluated the effect of a foliar application of Selenium at booting on grain yield and quality. Results Results from the Principal Component analysis revealed that seasonal weather and the varietal choice determined most of the variability of yield and quality traits, while Selenium application markedly affected the performance of organic durum wheat, especially in the milder season. The Cluster Analysis computed on the Princi- pal Components revealed three groups, representative of (i) the modern variety, Marco Aurelio, grown in the dryest season (average yield, low protein content), (ii) all varieties grown in 2018, with the addition of sodium selenate (high yield, high protein content), and (iii) the ancient variety, Cappelli, grown in both seasons (low yield, average protein content). Conclusions This study evidenced that tailored agronomic practices are needed to sustain the organic durum wheat systems in the Mediterranean area. The promising beneficial effect of Selenium would deserve a dedicated research program, where additional experiments should further investigate its impact on organic durum wheat yield and quality. The multivariate approach permitted us to identify the most effective agronomic practices in relation to dif- ferent environmental conditions; the outputs from this study are ready to be transferred to organic farmers aiming at improving the performance of durum wheat systems and at providing an effective contribution to food security. Keywords Foliar fertilization, Organic farming, Nitrogen, Selenium, Sulfur, PCA, Cluster analysis *Correspondence: Marcella Michela Giuliani marcella.giuliani@unifg.it Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Carucci et al. Agriculture & Food Security (2023) 12:12 Page 2 of 11 and adapting to climate change [9]. Relative to organic Introduction nitrogen management, even if it is well-known that split- According to the International Federation of Organic ting mineral N application in conventional agriculture Agriculture Movements (IFOAM), organic agriculture is increases fertilization efficiency [21–23], topdressing or a production system that sustains the health of soils, eco- foliar fertilizations are not commonly used in organic systems, and people, producing high-quality food with- farming. The synergistic effect of sulfur (S) and organic N out using mineral fertilizers, synthetic pesticides, animal soil fertilization could also lead to higher yields and bet- drugs, and food additives that may have adverse health ter quality in durum wheat [24]. Still, their contemporary effects [1]. use as organic foliar fertilizers in organic durum wheat Some studies reported that, with certain crops and is almost unexplored. Besides macronutrients, the Euro- under certain growing conditions, organic systems pean Commission Regulation (EC) No. 889/2008 allows come closer to matching conventional systems in terms using trace elements in fertilizer formulations for organic of yields [2, 3]. On the contrary, in several studies, crop production. Selenium (Se) is not listed among eligible yield averages are reported to be from 8% to 25% lower in trace elements, although its beneficial effects on stress organic systems than in conventional ones [4–7]. Organic tolerance [25, 26] and its positive action on plant pro- cereal have about 26% of yield reduction in organic farm- ductivity and nutritional quality have been widely docu- ing [8] and this aspect is crucial since cereal is knowing to mented [27–30], also on wheat [31, 32]. However, its use be one of the main food source for world population [9]. as ingredient in foliar fertilizer formulations has not been Furthermore, climate change has, and will increasingly proposed yet in organic systems [33]. have, severe impacts for agricultural production and food We conducted a 2-year field experiment, where four security [10], with uneven effects depending on the geo - durum wheat varieties were grown under alternative graphical area. For example, the Mediterranean basin has organic farming practices in the Mediterranean area to been identified as one of the most vulnerable regions to identify the most promising on yield and quality traits. climate changes globally [11], being highly affected by We evaluated the effect of N and S foliar applications increasing water scarcity and drought. from organic sources in combination with Se on yield, Durum wheat [Triticum turgidum subsp. durum grain protein concentration, plant N content, dry plant (Desf.) Husnot] is an important cereal crop feeding biomass, and harvest index using multivariate analyses. humanity [12]. It is mainly grown in the Mediterranean Our study provides the first scientific report on the effec - environments [13], where farmers must face profound tiveness of Se as foliar fertilizer on organic durum wheat, inter-annual fluctuations in yield and quality due to pro - giving quantitative figures to evaluate its potential inclu - longed drought and heat events [14]. Furthermore, in the sion among the eligible trace elements in the European organic farming, these environmental stresses, combined Organic Production Regulation. with the limited soil N availability of organic systems [15, 16], are detrimental to yield formation, as leaf water rela- Materials and methods tions and photosynthetic activity are impaired, leading to Experimental setup reduced growth rates, shortened grain filling period, and Experimental field trials were conducted in 2017–2018 lower grain weights [17]. and 2018–2019 (2018 and 2019 hereafter) at the Research Since the EU political framework is pushing towards a Centre for Cereal and Industrial Crops (CREA-CI) in wider adoption of organic farming in the coming years Foggia, Southern Italy (41°46′N, 16°54′E), as reported [18], researchers need to provide farmers with innovative by Carucci et  al. [33]. Two old (Old Saragolla and Cap- and sustainable agronomic strategies to stabilize organic pelli) and two modern (Marco Aurelio and Nadif ) durum durum wheat yield and quality to contribute to food wheat varieties were grown on clay soil (United States security. Within the organic sector, there is a high inter- Department of Agriculture Classification, Washington, est in heritage varieties of wheat, and old wheat varieties DC, USA) (Table  1) according to standard organic farm- are claimed to possess better characteristics than modern ing practices. cultivars in several respects [19]. Moreover, in literature The field experiment was arranged in a split–split plot is often reported that the modern varieties are usually design with three factors (variety, organic fertilization, unsuitable for organic systems [20] which needed dedi- Se application) and three replicates. The durum wheat cated breeding program. Other authors find it difficult to variety was the main plot, the organic fertilization was develop separate breeding programs for organic crops, the plot, and the selenium application was the sub-plot considering also that many breeding goals are the same (10.2 m ). The fields chosen for experimental trials were for organic and conventional grains [19]. Indeed, modern homogeneous and without preceding crop (set-aside). breeding approaches aim at obtaining cultivars capable The sowing dates were 1st December (2018) and 24th of high yield under sustainable agricultural conditions C arucci et al. Agriculture & Food Security (2023) 12:12 Page 3 of 11 Table 1 Main soil physical and chemical properties of the 13.5 °C and 11.7 °C, respectively. Figure 1 reports precipi- experimental fields in 2018 and 2019 tation and temperature trends in the 2  years compared with the long-term average (2000–2017) (source: NASA Soil properties Unit 2018 2019 POWER database [35]). Sand % 11.4 15.4 Silt % 39.6 34.9 Determination of yield, grain protein concentration, plant Clay % 49 49.7 N content, plant dry weight, and harvest index Total N (Kjeldhal method) ‰ 1.3 1.1 At physiological maturity (BBCH stage 87), on 0.5 linear a –1 Mineral Nmg kg 15.9 19.2 meters, plants were taken in two adjacent rows, cutting –1 Available P (Olsen method)mg kg 62 68 off the shoots at the crown level and separating them into –1 Exchangeable K (Ammonium acetate method)mg kg 422 450 straw and grain. Organic matter ( Walkley–Black method) % 2.5 2.6 Plant dry weight was determined by oven drying the Mineral N was determined at 0.3 m soil depth in pre-sowing as the sum of samples at 65 °C until constant weight. All samples were nitrate and ammonium content [56] grounded using a Cyclotec Sample Mill 1093 (Foss Teca- tor, Hillerød, Denmark). N concentration in straw and grains was determined triplicate using Leco CHNS 628 November (2019). Sowing was performed at a seeding −2 Analyzer (Leco corporation, St. Joseph, Michigan); N rate of 350 germinable seeds m . Four fertilization strat- −1 content was computed as the product of dry weight and egies were evaluated: (1) control (CTR), where 50 kg  ha N concentration. Total plant N content was derived as of dry blood meal was applied at sowing; (2) CTR, plus −1 the sum of N content of the straw and grain. Finally, Har- 45 kg  ha of foliar S applied at flag leaf stage (BBCH 47, −1 vest Index (HI) was computed as the ratio of grain weight CTR + S); (3) CTR, plus 45  kg  ha of foliar N applied to aboveground dry matter [36]. At full maturity (11% at heading (BBCH 51, CTR + N); (4) CTR, plus N and S humidity, on 29 and 18 June in 2018 and 2019), the crop foliar application at flag leaf and heading stages, respec - was machine-harvested, and the yield was evaluated. tively (CTR + NS). The effect of Se application was evalu - Grain protein concentration (GPC, %) was determined ated by comparing Se0, without selenium application, on grain samples by near-infrared reflectance spectros - and Se60, where one foliar application of sodium selenate −1 copy (Infratec 1229, Foss Tecator, Hillerød, Denmark). (Na SeO ), at the rate of 60  g  ha [34] was applied at 2 4 booting stage (BBCH stage 41). Foliar fertilizers were applied with a hand-held knapsack sprayer. All agricul- Statistical analyses tural practices were performed according to the organic Multivariate analyses were performed on the five durum practices commonly adopted by local farmers, following wheat traits (i.e., yield, grain protein concentration, plant the European Council Regulation (EC) No. 834/2007. A N content, plant dry weight, and harvest index), consid- weather station close to the experimental field recorded ering the four genotypes, the four organic fertilization, daily precipitation and temperature. In the 2018 and and the two Selenium applications over the 2  years as 2019 growing seasons, accumulated precipitations were additional descriptors [37]. A correlation analysis fol- 401  mm and 299  mm, and average temperatures were lowed by a Principal Component Analysis (PCA) was Fig. 1 Daily accumulated precipitation (mm) (a) and air temperature (°C) (b) in 2018 and 2019 (1st January–20th June). The black line (a)—average accumulated daily precipitations from 2000 to 2017. Shaded areas (b)—daily average mean ± standard deviation for Tmax (orange) and Tmin (cyan) in 2000–2017 Carucci et al. Agriculture & Food Security (2023) 12:12 Page 4 of 11 performed using all experimental traits (yield, grain deviation. A v test was computed to characterize the protein concentration, plant dry weight, plant N con- clusters considering both active and supplementary tent, and harvest index) as active quantitative variables. variables under the null hypothesis (H0) that the cluster The variables were centered and scaled before the PCA average did not differ from the overall average. The sign through diagonalization of the correlation matrix and of the v test statistic indicates an under- (−) or over- (+) extraction of the associated eigenvectors and eigenval- representation within the cluster. All statistical analyses ues. All tested factors (growing season, variety, organic were performed under the R 4.0.3 environment [38], Fac- fertilizer, and Se application) were used as qualitative toMineR package [39] for PCA and cluster analysis, and supplementary variables in the PCA, i.e., they did not ggplot2 [40] package for boxplot analysis and graphical contribute to the computation of Principal Components representations. (PC). Their coordinates were calculated as the barycen - tre of the corresponding individuals in the PC space. We Results then applied a non-supervised Hierarchical Clustering on Principal component analysis Principal Components (HCPC) using Euclidean distance All Pearson correlations among durum wheat traits were and Ward’s criterion to identify groups of data showing significant at p ≤ 0.05, except for the correlation between similar behavior. The cluster’s mean of any experimental yield and plant dry weight (Fig.  2a). Strongest posi- factor Xq was tested under the null hypothesis that the tive correlations emerged between plant N content and distribution of X did not vary across clusters (Eq. 1): plant dry weight (0.7), and between yield and HI (0.68), whereas plant dry weight was negatively correlated with Xq − X HI (− 0.6). GPC was positively correlated with plant N u = 2 (1) N−n q content (0.42), plant dry weight (0.36), and yield (0.19) n N−1 and negatively with HI (− 0.19). The first two components, explaining 79.8% of the where n is the number of experimental data in cluster q, total variance, were retained in the analysis (Fig.  2b). N is the total number of data, and S is the global standard Next, the characterization of PCs was performed by Fig. 2 Correlation matrix with Pearson’s r values (A), scree plot (B) of the principal component analysis, and biplot of variables (C) of durum wheat grain yield, grain protein concentration (GPC), plant N content (PlantNContent), plant dry weight (PlantDryWeight), and harvest index (HI) C arucci et al. Agriculture & Food Security (2023) 12:12 Page 5 of 11 Table 2 Correlation coefficients between active quantitative Table 3 Barycenter’s coordinates of the supplementary variables, supplementary qualitative variables, and the first two qualitative variable levels in the first two Principal Components Principal Components (PC), with indication of the explained (PC1, PC2) variance Factor Level Coordinate Variable PC1 PC2 PC1 PC2 Quantitative active variables Growing season 2018 0.60 0.75 Yield − 0.05ns 0.96*** 2019 − 0.60 − 0.75 GPC 0.59*** 0.34*** Variety Cappelli 1.23 − 0.73 Plant N content 0.81*** 0.37*** Old Saragolla − 0.19 − 0.49 Plant dry weight 0.91*** 0.03ns Marco Aurelio − 0.75 1.28 HI − 0.70*** 0.70*** Nadif − 0.29 − 0.07 Qualitative supplementary variables Organic fertilizer CTR 0.10 0.09 Growing season 0.40*** 0.58*** CTR + N 0.23 − 0.17 Variety 0.49*** 0.60*** CTR + S − 0.12 − 0.13 Organic fertilizer 0.11ns 0.11ns CTR + NS − 0.21 0.20 Selenium application 0.03ns 0.18*** Selenium application Se0 0.05 − 0.24 Explained variance 46.4% 33.5% Se60 − 0.05 0.24 ns, not significant Significant values are reported in bold Significance codes: ***p < 0.001 CTR, control; CTR + N, control plus N foliar application; CTR + S, control plus S foliar application; CTR + NS, control plus N and S foliar application; Se0, no selenium application; Se60, one foliar application of sodium selenate calculating correlation coefficients with active and Cluster analysis supplementary variables and the associated signifi- Three clusters emerged from the hierarchical clustering cance level (Table 2). performed on the extracted PCs (Fig.  3a). The clusters The first PC (PC1) explained 46.4% of the total vari- composition was characterized considering the repre- ance; it was positively correlated with GPC, plant N sentativeness of the qualitative and quantitative variables content, and plant dry weight and negatively with HI, used in the PCA, using an alpha level α = 0.05 for all sta- whereas its correlation with grain yield was not sig- tistical tests. All quantitative variables significantly con - nificant (Table  2). Thus, PC1 could be considered as tributed to explaining the inter-cluster variance, with a “qualitative factor”. The second PC (PC2) explained 2 2 GPC (ƞ = 0.72) and yield (ƞ = 0.62) as the most rel- 33.4% of the total variance and was highly correlated evant variables. Category frequency distributions within with grain yield and HI, whereas GPC and plant N clusters for the qualitative variables highlighted that content showed weaker correlations with PC2, even if the growing season and the variety at p ≤ 0.001, and Se significant (Table  2). Thus, PC2 could be considered application at p ≤ 0.05, were significantly different from as a “quantitative factor”. Among the supplementary the overall frequency distribution according to χ test, qualitative variables, growing season and variety were whereas organic fertilizer was not significant (p = 0.42). significantly and positively correlated with PC1 and Cluster 1 (C1) was entirely composed of experimental PC2, while Se application was significantly and posi- data collected in 2019, and 55.8% of the data belonged to tively correlated with PC2 (Table 2). Marco Aurelio. Cappelli was absent from C1 (Table  4). Relative to PC1 (“qualitative factor”), positive bar- This cluster was characterized by high HI, average grain ycenter’s coordinates were observed for 2018 and for yield, and low GPC (Table  5), and it was positioned on the old variety Cappelli, which showed the highest the negative side of the "qualitative factor" PC1 (Fig. 3a). positive coordinate, while 2019 data and the modern Cluster 2 (C2) grouped data from the 2018 growing variety Marco Aurelio obtained significative negative season exclusively (Table  4). All varieties were equally coordinates (Table  3). On the “quantitative factor” represented in C2, with percentages ranging from 19.2% PC2, significant positive values resulted for 2018 data (Cappelli) to 28.9% (Marco Aurelio) (Table  4). A signifi - and for the modern variety Marco Aurelio, which cant presence of the Se60 application was evident in C2, obtained the highest positive coordinate, and for Se60 whereas Se0 data were significantly under-represented. plots (Table  3). Finally, the barycenter of Cappelli and The values of all quantitative variables belong - Old Saragolla was placed on the negative side of PC2, ing to C2 were significantly higher than their average, along with 2019 and Se0 (Table 3). Carucci et al. Agriculture & Food Security (2023) 12:12 Page 6 of 11 Fig. 3 PCA biplot (a) with clusters delimitation (solid black lines and italics numbers); the barycenter of the supplementary variables most contributing to cluster variances are highlighted with colors (2018, orange; 2019, green; Se0, red; Se60, blu) and symbols (Cappelli, circle; Marco Aurelio, triangle). The other supplementary variables are reported in grey. Boxplots of distributions of yield (b) and grain protein concentration (c) resulting from the cluster analysis. Symbols and colors of boxplot charts reflect the visuals used in the PCA biplot especially GPC and yield (Table  5). Data from C2 were Finally, focusing on Se application, a boxplot analysis mainly positioned on the positive side of both “qualita- was conducted using the distributions of yield and grain tive” and “quantitative” factors PC1 and PC2 (Fig.  3a). protein concentration, i.e., the key indicators of the value Cluster 3 (C3) was the only cluster, where the two grow- of durum wheat productions from a farmer’s perspective. ing seasons were concurrently present, despite 80.3% of In C1, Se application did not significantly affect yield ( x −1 −1 the data being collected in 2019. Nearly half of the data Se0 = 2.88 t ha with SD = 0.49 t ha ; xSe60 = 2.68 t −1 −1 in C3 belonged to Cappelli, while Marco Aurelio was ha with SD = 0.44 t ha ) and GPC ( xSe0 = 10.2% with absent. Se0 treatment was over-represented (Table  4). SD = 0.49%; xSe60 = 10.1% with SD = 0.41%) (Fig.  3b, This cluster was characterized by high plant dry weight, c). Conversely, in C2 Se application was determinant in average GPC, and low HI and yield (Table 5), and it was increasing durum wheat yield, as Se60 treatment led to −1 −1 positioned on the negative side of the “quantitative fac- 3.32 t ha (SD = 0.51 t ha ), which was 19.4% higher −1 tor” PC1 (Fig. 3a). than the mean yield in Se0 ( xSe0 = 2.78 t ha with C arucci et al. Agriculture & Food Security (2023) 12:12 Page 7 of 11 Table 4 Within-cluster distributions (Mod.Cla), v test, and p value of supplementary qualitative variables Cluster 1 Cluster 2 Cluster 3 Mod.Cla (%) v test p value Mod.Cla (%) v test p value Mod.Cla (%) v test p value Growing season 2018 0.0 − 8.2 < 0.001 100.0 13.4 < 0.001 19.7 − 6.2 < 0.001 2019 100.0 8.2 < 0.001 0.0 − 13.4 < 0.001 80.3 6.2 < 0.001 Variety Cappelli 0.0 − 5.0 < 0.001 19.3 − 1.6 0.1 48.5 5.3 < 0.001 Old Saragolla 16.3 − 1.5 0.1 25.3 0.1 0.9 30.3 1.2 0.2 Marco Aurelio 55.8 5.0 < 0.001 28.9 1.1 0.3 0.0 − 6.6 < 0.001 Nadif 27.9 0.5 0.6 26.5 0.4 0.7 21.2 − 0.9 0.4 Organic fertilizer CTR 20.9 − 0.7 0.5 24.1 − 0.3 0.8 28.8 0.9 0.4 CTR + N 16.3 − 1.5 0.1 25.3 0.1 0.9 30.3 1.2 0.2 CTR + S 27.9 0.5 0.6 25.3 0.1 0.9 22.7 − 0.5 0.6 CTR + NS 34.9 1.6 0.1 25.3 0.1 0.9 18.2 − 1.6 0.1 Se application Se0 44.2 − 0.9 0.4 42.2 − 1.9 0.04 63.6 2.7 0.01 Se60 55.8 0.9 0.4 57.8 1.9 0.04 36.4 − 2.7 0.01 CTR, control; CTR + N, control plus N foliar application; CTR + S, control plus S foliar application; CTR + NS, control plus N and S foliar application; Se0, no selenium application; Se60, one foliar application of sodium selenite Table 5 v test, mean in the cluster, overall mean, standard deviation (SD) in the cluster, overall standard deviation, and p value of the active quantitative variables v test Mean Overall mean SD Overall SD p value Cluster 1 −1 Yield, t ha 1.7 2.8 2.7 0.5 0.7 0.1 GPC, % − 9.8 10.2 11.8 0.4 1.3 < 0.001 −1 Plant dry weight, t ha − 6.8 6.7 8.5 1.1 2.0 < 0.001 −1 Plant N content, kg ha − 5.4 75.2 93.1 16.7 24.7 < 0.001 HI 7.6 0.4 0.3 0.1 0.1 < 0.001 Cluster 2 −1 Yield, t ha 7.8 3.1 2.7 0.5 0.7 < 0.001 GPC, % 10.4 12.9 11.8 0.5 1.3 < 0.001 −1 Plant dry weight, t ha 1.7 8.8 8.5 1.3 2.0 0.1 −1 Plant N content, kg ha 3.9 101.2 93.1 21.1 24.7 < 0.001 HI 3.3 0.4 0.3 0.1 0.1 0.0 Cluster 3 −1 Yield, t ha − 9.7 2.0 2.7 0.3 0.7 < 0.001 GPC, % − 2.3 11.5 11.8 0.9 1.3 0.02 −1 Plant dry weight, t ha 4.2 9.4 8.5 2.4 2.0 < 0.001 −1 Plant N content, kg ha 0.6 94.7 93.1 27.1 24.7 0.5 HI − 10.1 0.2 0.3 0.1 0.1 < 0.001 GPC, grain protein concentration; HI, harvest index −1 −1 −1 SD = 0.38 t ha ) (Fig. 3b). The effect of Se application on SD = 0.31 t ha ; xSe60 = 1.88 t ha with SD = 0.31 t −1 GPC was negligible (Fig. 3c). ha ) (Fig.  3b) and a slight reduction in average GPC Finally, the effect of Se application in cluster 3 led ( xSe0 = 11.7% with SD = 1.08%; xSe60 = 11.3% with −1 to 13% decrease in mean yield ( xSe0 = 2.13 t ha with SD = 0.57%) (Fig. 3c). Carucci et al. Agriculture & Food Security (2023) 12:12 Page 8 of 11 Discussion lines from Italian, Syrian–Palestinian, and North Afri- In this study we combine Principal Component Analysis can landraces [44], characterized by high stability levels (PCA) and Cluster Analysis to give an analytic workflow of protein, dietary fiber, and antioxidants [45] also under capable to synthesize experimental evidence and cur- water stress condition. Our results suggest that the vari- rent knowledge on organic wheat systems in semi-arid etal choice in organic durum wheat systems can be con- environments, entailing traditional and modern varie- sidered the most crucial agronomical factor, especially ties, alternative foliar fertilization strategies and the addi- under water scarcity conditions like those foreseen in the tion of Selenium as bio-stimulant to plant metabolism to coming years. Moreover, the varietal choice in organic improve yield and quality response. durum wheat systems could reflect a different farmer’s The occurrence of drought stress will likely be even attitude. The modern variety Marco Aurelio is the right more impacting in the coming years in the Mediterra- choice when high yield is sought. On the contrary, the nean area [41], leading to a reduction of crop yield on old variety Cappelli seems to be the most feasible alterna- major crops, with a negative impact on food security [10]. tive when seeking stability in grain protein concentration, Wheat is one of the most important crops affecting global even accepting lower yields. food security and is known as the source of food for more Cluster 2 showed the best quantitative and qualitative than 50% of the world’s population. Since it often is a performance, since it included all data from the 2018, the rainfed crop, prolonged period of water scarcity condi- milder growing season. Selenium application was selected tions severely compromises its grain yield [9]. In our as a determinant contributor to Cluster 2, where it was field experiment, particularly harsh conditions occurred associated with about 20% yield increase, consistently on in 2019, which was characterized by very low precipita- all varieties. To date, Selenium is not listed among eligi- tions, 299 mm, compared with 401 mm in 2018. The field ble microelements in organic agriculture by the Euro- data from 2019 obtained negative coordinates on both pean Commission Regulation (EC) No. 889/2008. The ‘qualitative’ and ‘quantitative’ PCA factors (PC1 and PC2, rationale for including foliar Selenium application in our respectively) and grouped together in Cluster 1. How- experimental trial relies on scientific evidence of its bene - ever, Cluster 1 was mainly positioned on the positive side ficial effects on plant stress tolerance [25, 46]. Our results of the ‘quantitative’ PC2 factor, showing a slightly higher agree with several authors who reported increases in yield level than the overall mean due to the higher yield grain yield grown under conventional agronomic systems potential of Marco Aurelio. This result highlights that the after selenate foliar applications [27, 28, 30, 32], even if choice of the variety Marco Aurelio has buffered the neg - other authors did not report any significant effect [47– ative impact of water scarcity on quantitative parameters, 49]. On the contrary, the absence of beneficial effects of such as yield and HI. Marco Aurelio is a modern variety Selenium in the drier growing season disagree with stud- released in 2010, recently approved for use in organic ies conducted under conventional agronomic systems, farming [42], and is among the highest yielding varieties. in which late foliar applications of microelements dem- u Th s, this result does not comply with the hypothesis onstrated to enhance wheat growth parameters under that varieties that perform well under conventional farm- drought stress only [50]. To date, the effect of foliar appli - ing may not perform well under organic management cations of micronutrients is still controversial [51] and [20] and confirmed the assumption that modern varieties requires further experimental insights and a careful case- derive from breeding programs that aim to both satisfy by-case evaluation. Any deviation from the correct ratio food demand and support sustainable agricultural pro- of elements may lead to antagonism phenomena deter- ductivity for adaptation to climate change [9]. Besides, mining impairment of absorption and transport [52]. The Marco Aurelio is also characterized by high variability decisive yield increase obtained in response to Selenium in GPC. This latter aspect was confirmed by the negative applications in our experiment claims for a more articu- coordinates obtained by Cluster 1 on the ‘qualitative’ PC1 lated research program. Alternative solutions, doses, and factor, highlighting the detrimental impact of drought timing of applications have to be tested to evaluate the stress on GPC on this modern variety [43]. On the con- inclusion of Selenium in commercial formulations for trary, despite Cluster 3 grouped 80.3% of the data from organic agriculture. the drier growing season, this Cluster was mainly posi- Finally, we tested the effect of organic N- and S-based tioned on the positive side of the ‘qualitative’ PC1 factor, foliar fertilization on durum wheat for the first time, even showing a significative higher GPC value than the over - if at a low N concentration in the solutions (4% of total all mean. This behavior can be attributed to the positive N). Our choice was driven by the evidence that foliar effect of Cappelli, the most represented variety in Clus - N applications at heading demonstrated to be effec - ter 3, on the qualitative traits. Indeed, Cappelli is an old tive in improving wheat nutrition [21, 23], being leaves variety (year of release 1915), selected from individual more efficient than roots at absorbing nutrients at late C arucci et al. Agriculture & Food Security (2023) 12:12 Page 9 of 11 −1 CTR + S Organic fertilization with 50 kg ha of dry blood meal applied at development stages [53, 54]. However, the foliar organic −1 sowing and 45 kg ha of foliar S applied at flag leaf stage fertilization did not significantly contribute to explain - −1 CTR + N Organic fertilization with 50 kg ha of dry blood meal applied at −1 ing the clusters’ difference considering frequency dis - sowing and 45 kg ha of foliar N applied at heading −1 CTR + NS Organic fertilization with 50 kg ha of dry blood meal applied tribution. These results suggest the need for further −1 at sowing, plus 45 kg ha of foliar N applied at heading and investigations to develop more effective organic foliar −1 45 kg ha of foliar S applied at flag leaf stage fertilizer formulations, particularly with increased N con- Se0 No selenium f oliar application Se60 F oliar application of sodium selenate (Na SeO ) at the rate of centration. Moreover, recent trends in fertilizer costs, 2 4 −1 60 g ha along with their scarcity on the international market, BBCH Biologische Bundesanstalt, Bundessortenamt and Chemical are shrinking crop yields and food security [55]. This industry HI Harvest index situation and the need to foster the sustainability of the GPC Grain protein concentration agricultural farming practices sector must push organic PCA Principal component analysis fertilizers as an alternative to massive mineral fertilizers. PC Principal component HCPC Hierarchical clustering on principal components Conclusion and future studies Acknowledgements The debate regarding the role of organic agriculture This research was part of project SOFT (Smart Organic Farming Tecniques) financed under the PSR Puglia 2014–2020 funds, Measure 16—Cooperation, remains open, particularly when related to food security Submeasure 16.2—Support for pilot projects and the development of new and climate change [8]. We do agree with the idea that products, practices, processes, and technologies (CUP B79J20000080009). the conventional and organic systems do not have to Author contributions necessarily be considered competing entities with each Conceptualization, MMG. Methodology, MMG, GG and FC. Validation, MMG, other nor necessarily be compared in terms of produc- GG, and SB. Formal analysis, FC, GG, MMG, and SB. Investigation, FC and AG. tivity [8]. However, considering the objective set by the Writing—original draft preparation, FC. Writing—review and editing, MMG, GG, and SB. Visualization, AG and FC, and SB. Supervision, MMG, and GG. Pro- European Commission to reach at least 25% of agricul- ject administration, MMG. All authors have read and agreed to the published tural land in organic farming by 2030, it is crucial to version of the manuscript. investigate agronomic strategies capable of improving the Funding productive response of organic systems and, therefore, This research did not receive any specific grant from funding agencies in the their contribution to food security. This study provides public, commercial, or not-for-profit sectors. practical agronomic information based on experimental Availability of data and materials evidence to support organic farmers in advancing their The data sets used and/or analyzed during the current study will be available practices to sustain durum wheat yield and quality in the from the authors on reasonable request. Mediterranean. We tested the effects of the main alter - natives in the hands of farmers, from the varietal choice Declarations (two ancient and two modern wheat varieties) up to the Ethics approval and consent to participate possible foliar applications of nutrients. We then added Not applicable. Selenium to evaluate its possible bio-stimulant effect. This micro-nutrient, still not listed as an eligible nutri - Consent for publication Not applicable. ent in organic legislation, demonstrated its efficacy in the milder season. The analytic workflow based on multivari - Competing interests ate statistical techniques proposed here permitted us to The authors declare no competing interests. identify the most promising combination of agronomic Author details practices according to different environmental condi - Department of Agricultural and Forestry Sciences (DAFNE), University of Tus- tions. Further experiments are needed to shed more light cia, 01100 Viterbo, Italy. Department of Agricultural Sciences, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, on these complex cropping systems, also considering the FG, Italy. Council for Agricultural Research and Economics, Research Centre consequences of the adoption of agronomic management for Agriculture and Environment (CREA-AA), 40128 Bologna, BO, Italy. practices on the socio-economic and environmental Received: 5 August 2022 Accepted: 7 March 2023 sustainability. Abbreviations ANOVA Analysis of variance References N Nitrogen 1. IFOAM; 2008. https:// www. ifoam. bio/ why- organ ic/ organ ic- landm arks/ S Sulfur defin ition- organ ic#: ~: text= in% 20Vig nola% 2C% 20Ita ly.- ,Organ ic% 20Agr Se Selenium icult ure% 20is% 20a% 20pro ducti on% 20sys tem% 20that% 20sus tains% −1 CTR Organic fertilization with 50 kg ha of dry blood meal applied at 20the% 20hea lth,of% 20inp uts% 20with% 20adv erse% 20eff ects. Accessed sowing on 23 Dec 2021. Carucci et al. 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Individuation of the best agronomic practices for organic durum wheat cultivation in the Mediterranean environment: a multivariate approach

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Abstract

Background The main challenge of organic cereal systems is ensuring high yields and grain quality while maintain- ing pedo-environmental sustainability. Despite the potential benefits of organic farming systems, a debated limitation is their actual contribution to food security. Durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.], one of the most important staple food crops, is mainly grown in the Mediterranean environments, where farmers have to face profound inter-annual fluctuations in productions, expecially under organic system, due to prolonged drought and heat spells. With the overarching objective of deriving practical indications to support organic wheat production in the Mediterranean region, we tested the effect of nitrogen and sulphur-based organic foliar fertilizers on two ancient and two modern durum wheat varieties grown in two seasons (2018–2019) characterized by different weather condi- tions. Moreover, we evaluated the effect of a foliar application of Selenium at booting on grain yield and quality. Results Results from the Principal Component analysis revealed that seasonal weather and the varietal choice determined most of the variability of yield and quality traits, while Selenium application markedly affected the performance of organic durum wheat, especially in the milder season. The Cluster Analysis computed on the Princi- pal Components revealed three groups, representative of (i) the modern variety, Marco Aurelio, grown in the dryest season (average yield, low protein content), (ii) all varieties grown in 2018, with the addition of sodium selenate (high yield, high protein content), and (iii) the ancient variety, Cappelli, grown in both seasons (low yield, average protein content). Conclusions This study evidenced that tailored agronomic practices are needed to sustain the organic durum wheat systems in the Mediterranean area. The promising beneficial effect of Selenium would deserve a dedicated research program, where additional experiments should further investigate its impact on organic durum wheat yield and quality. The multivariate approach permitted us to identify the most effective agronomic practices in relation to dif- ferent environmental conditions; the outputs from this study are ready to be transferred to organic farmers aiming at improving the performance of durum wheat systems and at providing an effective contribution to food security. Keywords Foliar fertilization, Organic farming, Nitrogen, Selenium, Sulfur, PCA, Cluster analysis *Correspondence: Marcella Michela Giuliani marcella.giuliani@unifg.it Full list of author information is available at the end of the article © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Carucci et al. Agriculture & Food Security (2023) 12:12 Page 2 of 11 and adapting to climate change [9]. Relative to organic Introduction nitrogen management, even if it is well-known that split- According to the International Federation of Organic ting mineral N application in conventional agriculture Agriculture Movements (IFOAM), organic agriculture is increases fertilization efficiency [21–23], topdressing or a production system that sustains the health of soils, eco- foliar fertilizations are not commonly used in organic systems, and people, producing high-quality food with- farming. The synergistic effect of sulfur (S) and organic N out using mineral fertilizers, synthetic pesticides, animal soil fertilization could also lead to higher yields and bet- drugs, and food additives that may have adverse health ter quality in durum wheat [24]. Still, their contemporary effects [1]. use as organic foliar fertilizers in organic durum wheat Some studies reported that, with certain crops and is almost unexplored. Besides macronutrients, the Euro- under certain growing conditions, organic systems pean Commission Regulation (EC) No. 889/2008 allows come closer to matching conventional systems in terms using trace elements in fertilizer formulations for organic of yields [2, 3]. On the contrary, in several studies, crop production. Selenium (Se) is not listed among eligible yield averages are reported to be from 8% to 25% lower in trace elements, although its beneficial effects on stress organic systems than in conventional ones [4–7]. Organic tolerance [25, 26] and its positive action on plant pro- cereal have about 26% of yield reduction in organic farm- ductivity and nutritional quality have been widely docu- ing [8] and this aspect is crucial since cereal is knowing to mented [27–30], also on wheat [31, 32]. However, its use be one of the main food source for world population [9]. as ingredient in foliar fertilizer formulations has not been Furthermore, climate change has, and will increasingly proposed yet in organic systems [33]. have, severe impacts for agricultural production and food We conducted a 2-year field experiment, where four security [10], with uneven effects depending on the geo - durum wheat varieties were grown under alternative graphical area. For example, the Mediterranean basin has organic farming practices in the Mediterranean area to been identified as one of the most vulnerable regions to identify the most promising on yield and quality traits. climate changes globally [11], being highly affected by We evaluated the effect of N and S foliar applications increasing water scarcity and drought. from organic sources in combination with Se on yield, Durum wheat [Triticum turgidum subsp. durum grain protein concentration, plant N content, dry plant (Desf.) Husnot] is an important cereal crop feeding biomass, and harvest index using multivariate analyses. humanity [12]. It is mainly grown in the Mediterranean Our study provides the first scientific report on the effec - environments [13], where farmers must face profound tiveness of Se as foliar fertilizer on organic durum wheat, inter-annual fluctuations in yield and quality due to pro - giving quantitative figures to evaluate its potential inclu - longed drought and heat events [14]. Furthermore, in the sion among the eligible trace elements in the European organic farming, these environmental stresses, combined Organic Production Regulation. with the limited soil N availability of organic systems [15, 16], are detrimental to yield formation, as leaf water rela- Materials and methods tions and photosynthetic activity are impaired, leading to Experimental setup reduced growth rates, shortened grain filling period, and Experimental field trials were conducted in 2017–2018 lower grain weights [17]. and 2018–2019 (2018 and 2019 hereafter) at the Research Since the EU political framework is pushing towards a Centre for Cereal and Industrial Crops (CREA-CI) in wider adoption of organic farming in the coming years Foggia, Southern Italy (41°46′N, 16°54′E), as reported [18], researchers need to provide farmers with innovative by Carucci et  al. [33]. Two old (Old Saragolla and Cap- and sustainable agronomic strategies to stabilize organic pelli) and two modern (Marco Aurelio and Nadif ) durum durum wheat yield and quality to contribute to food wheat varieties were grown on clay soil (United States security. Within the organic sector, there is a high inter- Department of Agriculture Classification, Washington, est in heritage varieties of wheat, and old wheat varieties DC, USA) (Table  1) according to standard organic farm- are claimed to possess better characteristics than modern ing practices. cultivars in several respects [19]. Moreover, in literature The field experiment was arranged in a split–split plot is often reported that the modern varieties are usually design with three factors (variety, organic fertilization, unsuitable for organic systems [20] which needed dedi- Se application) and three replicates. The durum wheat cated breeding program. Other authors find it difficult to variety was the main plot, the organic fertilization was develop separate breeding programs for organic crops, the plot, and the selenium application was the sub-plot considering also that many breeding goals are the same (10.2 m ). The fields chosen for experimental trials were for organic and conventional grains [19]. Indeed, modern homogeneous and without preceding crop (set-aside). breeding approaches aim at obtaining cultivars capable The sowing dates were 1st December (2018) and 24th of high yield under sustainable agricultural conditions C arucci et al. Agriculture & Food Security (2023) 12:12 Page 3 of 11 Table 1 Main soil physical and chemical properties of the 13.5 °C and 11.7 °C, respectively. Figure 1 reports precipi- experimental fields in 2018 and 2019 tation and temperature trends in the 2  years compared with the long-term average (2000–2017) (source: NASA Soil properties Unit 2018 2019 POWER database [35]). Sand % 11.4 15.4 Silt % 39.6 34.9 Determination of yield, grain protein concentration, plant Clay % 49 49.7 N content, plant dry weight, and harvest index Total N (Kjeldhal method) ‰ 1.3 1.1 At physiological maturity (BBCH stage 87), on 0.5 linear a –1 Mineral Nmg kg 15.9 19.2 meters, plants were taken in two adjacent rows, cutting –1 Available P (Olsen method)mg kg 62 68 off the shoots at the crown level and separating them into –1 Exchangeable K (Ammonium acetate method)mg kg 422 450 straw and grain. Organic matter ( Walkley–Black method) % 2.5 2.6 Plant dry weight was determined by oven drying the Mineral N was determined at 0.3 m soil depth in pre-sowing as the sum of samples at 65 °C until constant weight. All samples were nitrate and ammonium content [56] grounded using a Cyclotec Sample Mill 1093 (Foss Teca- tor, Hillerød, Denmark). N concentration in straw and grains was determined triplicate using Leco CHNS 628 November (2019). Sowing was performed at a seeding −2 Analyzer (Leco corporation, St. Joseph, Michigan); N rate of 350 germinable seeds m . Four fertilization strat- −1 content was computed as the product of dry weight and egies were evaluated: (1) control (CTR), where 50 kg  ha N concentration. Total plant N content was derived as of dry blood meal was applied at sowing; (2) CTR, plus −1 the sum of N content of the straw and grain. Finally, Har- 45 kg  ha of foliar S applied at flag leaf stage (BBCH 47, −1 vest Index (HI) was computed as the ratio of grain weight CTR + S); (3) CTR, plus 45  kg  ha of foliar N applied to aboveground dry matter [36]. At full maturity (11% at heading (BBCH 51, CTR + N); (4) CTR, plus N and S humidity, on 29 and 18 June in 2018 and 2019), the crop foliar application at flag leaf and heading stages, respec - was machine-harvested, and the yield was evaluated. tively (CTR + NS). The effect of Se application was evalu - Grain protein concentration (GPC, %) was determined ated by comparing Se0, without selenium application, on grain samples by near-infrared reflectance spectros - and Se60, where one foliar application of sodium selenate −1 copy (Infratec 1229, Foss Tecator, Hillerød, Denmark). (Na SeO ), at the rate of 60  g  ha [34] was applied at 2 4 booting stage (BBCH stage 41). Foliar fertilizers were applied with a hand-held knapsack sprayer. All agricul- Statistical analyses tural practices were performed according to the organic Multivariate analyses were performed on the five durum practices commonly adopted by local farmers, following wheat traits (i.e., yield, grain protein concentration, plant the European Council Regulation (EC) No. 834/2007. A N content, plant dry weight, and harvest index), consid- weather station close to the experimental field recorded ering the four genotypes, the four organic fertilization, daily precipitation and temperature. In the 2018 and and the two Selenium applications over the 2  years as 2019 growing seasons, accumulated precipitations were additional descriptors [37]. A correlation analysis fol- 401  mm and 299  mm, and average temperatures were lowed by a Principal Component Analysis (PCA) was Fig. 1 Daily accumulated precipitation (mm) (a) and air temperature (°C) (b) in 2018 and 2019 (1st January–20th June). The black line (a)—average accumulated daily precipitations from 2000 to 2017. Shaded areas (b)—daily average mean ± standard deviation for Tmax (orange) and Tmin (cyan) in 2000–2017 Carucci et al. Agriculture & Food Security (2023) 12:12 Page 4 of 11 performed using all experimental traits (yield, grain deviation. A v test was computed to characterize the protein concentration, plant dry weight, plant N con- clusters considering both active and supplementary tent, and harvest index) as active quantitative variables. variables under the null hypothesis (H0) that the cluster The variables were centered and scaled before the PCA average did not differ from the overall average. The sign through diagonalization of the correlation matrix and of the v test statistic indicates an under- (−) or over- (+) extraction of the associated eigenvectors and eigenval- representation within the cluster. All statistical analyses ues. All tested factors (growing season, variety, organic were performed under the R 4.0.3 environment [38], Fac- fertilizer, and Se application) were used as qualitative toMineR package [39] for PCA and cluster analysis, and supplementary variables in the PCA, i.e., they did not ggplot2 [40] package for boxplot analysis and graphical contribute to the computation of Principal Components representations. (PC). Their coordinates were calculated as the barycen - tre of the corresponding individuals in the PC space. We Results then applied a non-supervised Hierarchical Clustering on Principal component analysis Principal Components (HCPC) using Euclidean distance All Pearson correlations among durum wheat traits were and Ward’s criterion to identify groups of data showing significant at p ≤ 0.05, except for the correlation between similar behavior. The cluster’s mean of any experimental yield and plant dry weight (Fig.  2a). Strongest posi- factor Xq was tested under the null hypothesis that the tive correlations emerged between plant N content and distribution of X did not vary across clusters (Eq. 1): plant dry weight (0.7), and between yield and HI (0.68), whereas plant dry weight was negatively correlated with Xq − X HI (− 0.6). GPC was positively correlated with plant N u = 2 (1) N−n q content (0.42), plant dry weight (0.36), and yield (0.19) n N−1 and negatively with HI (− 0.19). The first two components, explaining 79.8% of the where n is the number of experimental data in cluster q, total variance, were retained in the analysis (Fig.  2b). N is the total number of data, and S is the global standard Next, the characterization of PCs was performed by Fig. 2 Correlation matrix with Pearson’s r values (A), scree plot (B) of the principal component analysis, and biplot of variables (C) of durum wheat grain yield, grain protein concentration (GPC), plant N content (PlantNContent), plant dry weight (PlantDryWeight), and harvest index (HI) C arucci et al. Agriculture & Food Security (2023) 12:12 Page 5 of 11 Table 2 Correlation coefficients between active quantitative Table 3 Barycenter’s coordinates of the supplementary variables, supplementary qualitative variables, and the first two qualitative variable levels in the first two Principal Components Principal Components (PC), with indication of the explained (PC1, PC2) variance Factor Level Coordinate Variable PC1 PC2 PC1 PC2 Quantitative active variables Growing season 2018 0.60 0.75 Yield − 0.05ns 0.96*** 2019 − 0.60 − 0.75 GPC 0.59*** 0.34*** Variety Cappelli 1.23 − 0.73 Plant N content 0.81*** 0.37*** Old Saragolla − 0.19 − 0.49 Plant dry weight 0.91*** 0.03ns Marco Aurelio − 0.75 1.28 HI − 0.70*** 0.70*** Nadif − 0.29 − 0.07 Qualitative supplementary variables Organic fertilizer CTR 0.10 0.09 Growing season 0.40*** 0.58*** CTR + N 0.23 − 0.17 Variety 0.49*** 0.60*** CTR + S − 0.12 − 0.13 Organic fertilizer 0.11ns 0.11ns CTR + NS − 0.21 0.20 Selenium application 0.03ns 0.18*** Selenium application Se0 0.05 − 0.24 Explained variance 46.4% 33.5% Se60 − 0.05 0.24 ns, not significant Significant values are reported in bold Significance codes: ***p < 0.001 CTR, control; CTR + N, control plus N foliar application; CTR + S, control plus S foliar application; CTR + NS, control plus N and S foliar application; Se0, no selenium application; Se60, one foliar application of sodium selenate calculating correlation coefficients with active and Cluster analysis supplementary variables and the associated signifi- Three clusters emerged from the hierarchical clustering cance level (Table 2). performed on the extracted PCs (Fig.  3a). The clusters The first PC (PC1) explained 46.4% of the total vari- composition was characterized considering the repre- ance; it was positively correlated with GPC, plant N sentativeness of the qualitative and quantitative variables content, and plant dry weight and negatively with HI, used in the PCA, using an alpha level α = 0.05 for all sta- whereas its correlation with grain yield was not sig- tistical tests. All quantitative variables significantly con - nificant (Table  2). Thus, PC1 could be considered as tributed to explaining the inter-cluster variance, with a “qualitative factor”. The second PC (PC2) explained 2 2 GPC (ƞ = 0.72) and yield (ƞ = 0.62) as the most rel- 33.4% of the total variance and was highly correlated evant variables. Category frequency distributions within with grain yield and HI, whereas GPC and plant N clusters for the qualitative variables highlighted that content showed weaker correlations with PC2, even if the growing season and the variety at p ≤ 0.001, and Se significant (Table  2). Thus, PC2 could be considered application at p ≤ 0.05, were significantly different from as a “quantitative factor”. Among the supplementary the overall frequency distribution according to χ test, qualitative variables, growing season and variety were whereas organic fertilizer was not significant (p = 0.42). significantly and positively correlated with PC1 and Cluster 1 (C1) was entirely composed of experimental PC2, while Se application was significantly and posi- data collected in 2019, and 55.8% of the data belonged to tively correlated with PC2 (Table 2). Marco Aurelio. Cappelli was absent from C1 (Table  4). Relative to PC1 (“qualitative factor”), positive bar- This cluster was characterized by high HI, average grain ycenter’s coordinates were observed for 2018 and for yield, and low GPC (Table  5), and it was positioned on the old variety Cappelli, which showed the highest the negative side of the "qualitative factor" PC1 (Fig. 3a). positive coordinate, while 2019 data and the modern Cluster 2 (C2) grouped data from the 2018 growing variety Marco Aurelio obtained significative negative season exclusively (Table  4). All varieties were equally coordinates (Table  3). On the “quantitative factor” represented in C2, with percentages ranging from 19.2% PC2, significant positive values resulted for 2018 data (Cappelli) to 28.9% (Marco Aurelio) (Table  4). A signifi - and for the modern variety Marco Aurelio, which cant presence of the Se60 application was evident in C2, obtained the highest positive coordinate, and for Se60 whereas Se0 data were significantly under-represented. plots (Table  3). Finally, the barycenter of Cappelli and The values of all quantitative variables belong - Old Saragolla was placed on the negative side of PC2, ing to C2 were significantly higher than their average, along with 2019 and Se0 (Table 3). Carucci et al. Agriculture & Food Security (2023) 12:12 Page 6 of 11 Fig. 3 PCA biplot (a) with clusters delimitation (solid black lines and italics numbers); the barycenter of the supplementary variables most contributing to cluster variances are highlighted with colors (2018, orange; 2019, green; Se0, red; Se60, blu) and symbols (Cappelli, circle; Marco Aurelio, triangle). The other supplementary variables are reported in grey. Boxplots of distributions of yield (b) and grain protein concentration (c) resulting from the cluster analysis. Symbols and colors of boxplot charts reflect the visuals used in the PCA biplot especially GPC and yield (Table  5). Data from C2 were Finally, focusing on Se application, a boxplot analysis mainly positioned on the positive side of both “qualita- was conducted using the distributions of yield and grain tive” and “quantitative” factors PC1 and PC2 (Fig.  3a). protein concentration, i.e., the key indicators of the value Cluster 3 (C3) was the only cluster, where the two grow- of durum wheat productions from a farmer’s perspective. ing seasons were concurrently present, despite 80.3% of In C1, Se application did not significantly affect yield ( x −1 −1 the data being collected in 2019. Nearly half of the data Se0 = 2.88 t ha with SD = 0.49 t ha ; xSe60 = 2.68 t −1 −1 in C3 belonged to Cappelli, while Marco Aurelio was ha with SD = 0.44 t ha ) and GPC ( xSe0 = 10.2% with absent. Se0 treatment was over-represented (Table  4). SD = 0.49%; xSe60 = 10.1% with SD = 0.41%) (Fig.  3b, This cluster was characterized by high plant dry weight, c). Conversely, in C2 Se application was determinant in average GPC, and low HI and yield (Table 5), and it was increasing durum wheat yield, as Se60 treatment led to −1 −1 positioned on the negative side of the “quantitative fac- 3.32 t ha (SD = 0.51 t ha ), which was 19.4% higher −1 tor” PC1 (Fig. 3a). than the mean yield in Se0 ( xSe0 = 2.78 t ha with C arucci et al. Agriculture & Food Security (2023) 12:12 Page 7 of 11 Table 4 Within-cluster distributions (Mod.Cla), v test, and p value of supplementary qualitative variables Cluster 1 Cluster 2 Cluster 3 Mod.Cla (%) v test p value Mod.Cla (%) v test p value Mod.Cla (%) v test p value Growing season 2018 0.0 − 8.2 < 0.001 100.0 13.4 < 0.001 19.7 − 6.2 < 0.001 2019 100.0 8.2 < 0.001 0.0 − 13.4 < 0.001 80.3 6.2 < 0.001 Variety Cappelli 0.0 − 5.0 < 0.001 19.3 − 1.6 0.1 48.5 5.3 < 0.001 Old Saragolla 16.3 − 1.5 0.1 25.3 0.1 0.9 30.3 1.2 0.2 Marco Aurelio 55.8 5.0 < 0.001 28.9 1.1 0.3 0.0 − 6.6 < 0.001 Nadif 27.9 0.5 0.6 26.5 0.4 0.7 21.2 − 0.9 0.4 Organic fertilizer CTR 20.9 − 0.7 0.5 24.1 − 0.3 0.8 28.8 0.9 0.4 CTR + N 16.3 − 1.5 0.1 25.3 0.1 0.9 30.3 1.2 0.2 CTR + S 27.9 0.5 0.6 25.3 0.1 0.9 22.7 − 0.5 0.6 CTR + NS 34.9 1.6 0.1 25.3 0.1 0.9 18.2 − 1.6 0.1 Se application Se0 44.2 − 0.9 0.4 42.2 − 1.9 0.04 63.6 2.7 0.01 Se60 55.8 0.9 0.4 57.8 1.9 0.04 36.4 − 2.7 0.01 CTR, control; CTR + N, control plus N foliar application; CTR + S, control plus S foliar application; CTR + NS, control plus N and S foliar application; Se0, no selenium application; Se60, one foliar application of sodium selenite Table 5 v test, mean in the cluster, overall mean, standard deviation (SD) in the cluster, overall standard deviation, and p value of the active quantitative variables v test Mean Overall mean SD Overall SD p value Cluster 1 −1 Yield, t ha 1.7 2.8 2.7 0.5 0.7 0.1 GPC, % − 9.8 10.2 11.8 0.4 1.3 < 0.001 −1 Plant dry weight, t ha − 6.8 6.7 8.5 1.1 2.0 < 0.001 −1 Plant N content, kg ha − 5.4 75.2 93.1 16.7 24.7 < 0.001 HI 7.6 0.4 0.3 0.1 0.1 < 0.001 Cluster 2 −1 Yield, t ha 7.8 3.1 2.7 0.5 0.7 < 0.001 GPC, % 10.4 12.9 11.8 0.5 1.3 < 0.001 −1 Plant dry weight, t ha 1.7 8.8 8.5 1.3 2.0 0.1 −1 Plant N content, kg ha 3.9 101.2 93.1 21.1 24.7 < 0.001 HI 3.3 0.4 0.3 0.1 0.1 0.0 Cluster 3 −1 Yield, t ha − 9.7 2.0 2.7 0.3 0.7 < 0.001 GPC, % − 2.3 11.5 11.8 0.9 1.3 0.02 −1 Plant dry weight, t ha 4.2 9.4 8.5 2.4 2.0 < 0.001 −1 Plant N content, kg ha 0.6 94.7 93.1 27.1 24.7 0.5 HI − 10.1 0.2 0.3 0.1 0.1 < 0.001 GPC, grain protein concentration; HI, harvest index −1 −1 −1 SD = 0.38 t ha ) (Fig. 3b). The effect of Se application on SD = 0.31 t ha ; xSe60 = 1.88 t ha with SD = 0.31 t −1 GPC was negligible (Fig. 3c). ha ) (Fig.  3b) and a slight reduction in average GPC Finally, the effect of Se application in cluster 3 led ( xSe0 = 11.7% with SD = 1.08%; xSe60 = 11.3% with −1 to 13% decrease in mean yield ( xSe0 = 2.13 t ha with SD = 0.57%) (Fig. 3c). Carucci et al. Agriculture & Food Security (2023) 12:12 Page 8 of 11 Discussion lines from Italian, Syrian–Palestinian, and North Afri- In this study we combine Principal Component Analysis can landraces [44], characterized by high stability levels (PCA) and Cluster Analysis to give an analytic workflow of protein, dietary fiber, and antioxidants [45] also under capable to synthesize experimental evidence and cur- water stress condition. Our results suggest that the vari- rent knowledge on organic wheat systems in semi-arid etal choice in organic durum wheat systems can be con- environments, entailing traditional and modern varie- sidered the most crucial agronomical factor, especially ties, alternative foliar fertilization strategies and the addi- under water scarcity conditions like those foreseen in the tion of Selenium as bio-stimulant to plant metabolism to coming years. Moreover, the varietal choice in organic improve yield and quality response. durum wheat systems could reflect a different farmer’s The occurrence of drought stress will likely be even attitude. The modern variety Marco Aurelio is the right more impacting in the coming years in the Mediterra- choice when high yield is sought. On the contrary, the nean area [41], leading to a reduction of crop yield on old variety Cappelli seems to be the most feasible alterna- major crops, with a negative impact on food security [10]. tive when seeking stability in grain protein concentration, Wheat is one of the most important crops affecting global even accepting lower yields. food security and is known as the source of food for more Cluster 2 showed the best quantitative and qualitative than 50% of the world’s population. Since it often is a performance, since it included all data from the 2018, the rainfed crop, prolonged period of water scarcity condi- milder growing season. Selenium application was selected tions severely compromises its grain yield [9]. In our as a determinant contributor to Cluster 2, where it was field experiment, particularly harsh conditions occurred associated with about 20% yield increase, consistently on in 2019, which was characterized by very low precipita- all varieties. To date, Selenium is not listed among eligi- tions, 299 mm, compared with 401 mm in 2018. The field ble microelements in organic agriculture by the Euro- data from 2019 obtained negative coordinates on both pean Commission Regulation (EC) No. 889/2008. The ‘qualitative’ and ‘quantitative’ PCA factors (PC1 and PC2, rationale for including foliar Selenium application in our respectively) and grouped together in Cluster 1. How- experimental trial relies on scientific evidence of its bene - ever, Cluster 1 was mainly positioned on the positive side ficial effects on plant stress tolerance [25, 46]. Our results of the ‘quantitative’ PC2 factor, showing a slightly higher agree with several authors who reported increases in yield level than the overall mean due to the higher yield grain yield grown under conventional agronomic systems potential of Marco Aurelio. This result highlights that the after selenate foliar applications [27, 28, 30, 32], even if choice of the variety Marco Aurelio has buffered the neg - other authors did not report any significant effect [47– ative impact of water scarcity on quantitative parameters, 49]. On the contrary, the absence of beneficial effects of such as yield and HI. Marco Aurelio is a modern variety Selenium in the drier growing season disagree with stud- released in 2010, recently approved for use in organic ies conducted under conventional agronomic systems, farming [42], and is among the highest yielding varieties. in which late foliar applications of microelements dem- u Th s, this result does not comply with the hypothesis onstrated to enhance wheat growth parameters under that varieties that perform well under conventional farm- drought stress only [50]. To date, the effect of foliar appli - ing may not perform well under organic management cations of micronutrients is still controversial [51] and [20] and confirmed the assumption that modern varieties requires further experimental insights and a careful case- derive from breeding programs that aim to both satisfy by-case evaluation. Any deviation from the correct ratio food demand and support sustainable agricultural pro- of elements may lead to antagonism phenomena deter- ductivity for adaptation to climate change [9]. Besides, mining impairment of absorption and transport [52]. The Marco Aurelio is also characterized by high variability decisive yield increase obtained in response to Selenium in GPC. This latter aspect was confirmed by the negative applications in our experiment claims for a more articu- coordinates obtained by Cluster 1 on the ‘qualitative’ PC1 lated research program. Alternative solutions, doses, and factor, highlighting the detrimental impact of drought timing of applications have to be tested to evaluate the stress on GPC on this modern variety [43]. On the con- inclusion of Selenium in commercial formulations for trary, despite Cluster 3 grouped 80.3% of the data from organic agriculture. the drier growing season, this Cluster was mainly posi- Finally, we tested the effect of organic N- and S-based tioned on the positive side of the ‘qualitative’ PC1 factor, foliar fertilization on durum wheat for the first time, even showing a significative higher GPC value than the over - if at a low N concentration in the solutions (4% of total all mean. This behavior can be attributed to the positive N). Our choice was driven by the evidence that foliar effect of Cappelli, the most represented variety in Clus - N applications at heading demonstrated to be effec - ter 3, on the qualitative traits. Indeed, Cappelli is an old tive in improving wheat nutrition [21, 23], being leaves variety (year of release 1915), selected from individual more efficient than roots at absorbing nutrients at late C arucci et al. Agriculture & Food Security (2023) 12:12 Page 9 of 11 −1 CTR + S Organic fertilization with 50 kg ha of dry blood meal applied at development stages [53, 54]. However, the foliar organic −1 sowing and 45 kg ha of foliar S applied at flag leaf stage fertilization did not significantly contribute to explain - −1 CTR + N Organic fertilization with 50 kg ha of dry blood meal applied at −1 ing the clusters’ difference considering frequency dis - sowing and 45 kg ha of foliar N applied at heading −1 CTR + NS Organic fertilization with 50 kg ha of dry blood meal applied tribution. These results suggest the need for further −1 at sowing, plus 45 kg ha of foliar N applied at heading and investigations to develop more effective organic foliar −1 45 kg ha of foliar S applied at flag leaf stage fertilizer formulations, particularly with increased N con- Se0 No selenium f oliar application Se60 F oliar application of sodium selenate (Na SeO ) at the rate of centration. Moreover, recent trends in fertilizer costs, 2 4 −1 60 g ha along with their scarcity on the international market, BBCH Biologische Bundesanstalt, Bundessortenamt and Chemical are shrinking crop yields and food security [55]. This industry HI Harvest index situation and the need to foster the sustainability of the GPC Grain protein concentration agricultural farming practices sector must push organic PCA Principal component analysis fertilizers as an alternative to massive mineral fertilizers. PC Principal component HCPC Hierarchical clustering on principal components Conclusion and future studies Acknowledgements The debate regarding the role of organic agriculture This research was part of project SOFT (Smart Organic Farming Tecniques) financed under the PSR Puglia 2014–2020 funds, Measure 16—Cooperation, remains open, particularly when related to food security Submeasure 16.2—Support for pilot projects and the development of new and climate change [8]. We do agree with the idea that products, practices, processes, and technologies (CUP B79J20000080009). the conventional and organic systems do not have to Author contributions necessarily be considered competing entities with each Conceptualization, MMG. Methodology, MMG, GG and FC. Validation, MMG, other nor necessarily be compared in terms of produc- GG, and SB. Formal analysis, FC, GG, MMG, and SB. Investigation, FC and AG. tivity [8]. However, considering the objective set by the Writing—original draft preparation, FC. Writing—review and editing, MMG, GG, and SB. Visualization, AG and FC, and SB. Supervision, MMG, and GG. Pro- European Commission to reach at least 25% of agricul- ject administration, MMG. All authors have read and agreed to the published tural land in organic farming by 2030, it is crucial to version of the manuscript. investigate agronomic strategies capable of improving the Funding productive response of organic systems and, therefore, This research did not receive any specific grant from funding agencies in the their contribution to food security. This study provides public, commercial, or not-for-profit sectors. practical agronomic information based on experimental Availability of data and materials evidence to support organic farmers in advancing their The data sets used and/or analyzed during the current study will be available practices to sustain durum wheat yield and quality in the from the authors on reasonable request. Mediterranean. We tested the effects of the main alter - natives in the hands of farmers, from the varietal choice Declarations (two ancient and two modern wheat varieties) up to the Ethics approval and consent to participate possible foliar applications of nutrients. We then added Not applicable. Selenium to evaluate its possible bio-stimulant effect. This micro-nutrient, still not listed as an eligible nutri - Consent for publication Not applicable. ent in organic legislation, demonstrated its efficacy in the milder season. The analytic workflow based on multivari - Competing interests ate statistical techniques proposed here permitted us to The authors declare no competing interests. identify the most promising combination of agronomic Author details practices according to different environmental condi - Department of Agricultural and Forestry Sciences (DAFNE), University of Tus- tions. Further experiments are needed to shed more light cia, 01100 Viterbo, Italy. Department of Agricultural Sciences, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, on these complex cropping systems, also considering the FG, Italy. Council for Agricultural Research and Economics, Research Centre consequences of the adoption of agronomic management for Agriculture and Environment (CREA-AA), 40128 Bologna, BO, Italy. practices on the socio-economic and environmental Received: 5 August 2022 Accepted: 7 March 2023 sustainability. Abbreviations ANOVA Analysis of variance References N Nitrogen 1. IFOAM; 2008. https:// www. ifoam. bio/ why- organ ic/ organ ic- landm arks/ S Sulfur defin ition- organ ic#: ~: text= in% 20Vig nola% 2C% 20Ita ly.- ,Organ ic% 20Agr Se Selenium icult ure% 20is% 20a% 20pro ducti on% 20sys tem% 20that% 20sus tains% −1 CTR Organic fertilization with 50 kg ha of dry blood meal applied at 20the% 20hea lth,of% 20inp uts% 20with% 20adv erse% 20eff ects. Accessed sowing on 23 Dec 2021. Carucci et al. 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Journal

Agriculture & Food SecuritySpringer Journals

Published: May 19, 2023

Keywords: Foliar fertilization; Organic farming; Nitrogen; Selenium; Sulfur; PCA; Cluster analysis

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