Testing a Depletion Nutrient Supply Strategy to Improve the Fertilization Management of “Cipollotto Nocerino” Spring Onion: Effect on Produce Yield and Quality Attributes

Abstract

Background: Conventional practices for the cultivation of “Cipollotto Nocerino” spring onion are mainly based on growers’ experience, and up to 250 kg/ha for N is commonly furnished among growing cycles. Facing the issue of reduced availability of natural resources for crop production (for example mineral resources), we investigated the optimization of the productivity. Methods: In our research, we tested the use of depletion nutrient supply strategy (CAL-FERT^®) to enhance fertilization in accordance with the principle of sustainable agriculture included in the Farm to Fork strategy. In our study, besides the common initial fertilization, three different strategies for cover fertilizations have been elaborated with the support of CAL-FERT^® software. The treatments were as follows: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); and (iv) strongly reduced fertilization compared to the control (named F-0). The parameters investigated included the following: plant height, yield, SPAD index, nitrogen use efficiency, dry matter, soluble solid content, and pyruvate contents in bulbs and leaves. Nitrogen content was also analyzed for both hypogeous and epigeous apparatuses. Results: Among the most interesting vegetative results, plant height and SPAD readings were reduced only by the extreme treatment F-0 compared with the other treatments at 104 days after planting. Regarding qualitative and productive parameters, the treatments F-50 and F-25 showed the highest yield without prejudging Soluble Solid Content and reducing pungency. Conclusion: In nutritional experiments, onion could be considered as a crop model to investigate quality in vegetables due to its consumption as fresh product and for its particular response, in terms of yield and quality, to fertilization. The use of simulation software can support the identification of strategies to reduce the nutrient supply without any detrimental effect on yield and other vegetative and qualitative parameters in onion crops.

1. Introduction

Among 800 plant species, which constitute the Allium genus, onion (Allium cepa L. 2n = 2x = 16) is the most important crop, grown on over 5.2 million hectares (Mha) with a yield of 111 metric tons (Mt) of product per year, including shallot [1]. This crop is cultivated in several climatic areas, and it furnishes several products. Onion is in fact consumed as a fresh, stored, or dehydrated (powdery) product; as well as onion rings, among a multitude of landraces, ecotypes, and varieties [2]. In Italy, despite the reduced amount of onion surface in a worldwide scale (approximatively 13,000 hectares (ha), [3]) the portfolio of cultivated genotypes for high quality production is higher [4].

The ‘Bianca di Pompei’ onion variety includes several landraces distinguished by their harvest time as follows: Febbrarese, Marzatica, Aprilatica, Maggiaiola, and Giugnese which are harvested in February, March, April, May, and June, respectively [5]. The landrace Marzatica is a white spring onion commonly known as “Cipollotto Nocerino” (CN) in the Campania region, Italy, in the territory corresponding to Agro Nocerino Sarnese and Pompeii-Stabio in the Province of Salerno and Naples, respectively [6]. Its cultivation has been reported starting from ancient time, approximatively 2000 years ago, in historical paintings and references, as well as in the Middle Ages. Nowadays, CN is granted as Protected Designation of Origin according to Reg. CE n. 656/2008, and its annual production is ranging between 25 and 55 tons (t) of fresh produce, generating a turnover of 200–520 million euros (M EUR) on a growing area of approximatively 1400 ha [7,8].

Commonly, CN is a transplanted crop, harvested by hand or with machinery as spring onion from March to June without storage. The commercial maturity for CN is reached at the stage of 2–5 cm bulbification, and the best plants are selected, cleaned, and peeled to eliminate undesired external tunic(s). The shallow root system is mostly removed, and the dark-green leaves are cut on top, as required for marketing [6,8]. CN is sold in bunches of 400–500 g, and bulbs have a bright and shiny white color on the external and internal fleshy scales. At physiological maturity, the taste is sweet and slightly pungent, and the bulb shape is basically “transverse elliptic” (thick flat)—mainly cylindrical on the sides and flattened on the top, with a slight thickening close to the basal plate, as also reported in the CN Protected Designation of Origin production regulation [7,8]. The agronomic practices for the cultivation of this crop are mainly driven by empirical protocols, consolidated along the time at the local level and based on growers’ experience and practices, such as fertilization. Onion fresh bulb quality and yield are strictly affected by nutrient management and agronomic techniques [9,10] and can be improved using simulation-based decision support systems and computational methods [11]. Nitrogen, P, K, Ca, and S are indeed essential elements for plant growth, playing a crucial role in addressing primary (photosynthesis process) and secondary metabolic pathways [12]. For fresh spring onion, S-containing compounds strictly affect quality in terms of pungency, which is commonly expressed in terms of pyruvic acid content [13].

Nowadays, the growing population and climatic evolution are influencing agronomic protocols of cultivation towards more resilient and sustainable agricultural models, which include ensuring food security standards while preserving the nutritional quality and yield. Moreover, consumer demand is devolved to quality, but also in consumer-friendly cultivation; in addition, the programmatic legislation is oriented to reducing pollution due to the massive use of chemicals, according to the Farm to Fork strategies included in the European Green Deal (UE reg. n. 2021/2115). Among other agricultural products, vegetables consumers are more sensitive to the idea of healthy and sustainable food [14], which would facilitate growers to adopt precision management tools in the framework of product certification regulations.

To develop sustainable fertilization management, for example, several decision support systems are potentially available at farm scale for operational use by integrating simulation fertilization tools. Many of them have been specifically developed and validated for vegetable crops [15]. In Italy, the CAL-FERT^® model (software version 1.4) has been designed on a user-friendly platform, and it can predict fertilization requirement and planning through a nutrient balance (N, P₂O₅, and K₂O) for many vegetables and other crops cultivated in the Mediterranean area [16]. From the perspective of increasingly dynamic climate changes, the main advantage of simulation-based management tools is their capacity to predict crop behavior as a function of climatic parameters. Studies on different technologies for fast monitoring the nutrient status in vegetable productions are also exponentially increasing in recent years, and many of them have been successfully implemented at the operational level. Among all, optical (remote or proximal) sensors and equipment for fast root zone analysis are the most promising, especially for the non-destructive monitoring of N status in intensive vegetable production systems [17,18]. However, the evaluation of plant response to nutrient availability in the root zone, methodologically, remains the main reference parameter for the individuation of optimal thresholds for correct fertilization management, be it based either on simulation or direct measurements [19].

The main objective of the present research was to investigate the optimization of nutrient supply in a spring onion variety through the revision of the standard fertilization protocols and without prejudging quantitative and qualitative perspectives of yield and quality. A first evaluation of the nutrient supply, based on the growers’ practices, was carried out through CAL-FERT^® software to better assess the actual nutrient crop requirements. Furthermore, this study aims to provide insights into the product quality and vegetative responses of the spring onion to different macro-nutrient supply rates.

2. Materials and Methods

2.1. Field Experiment and Treatments

The spring onion CN (Allium cepa L., ‘Bianca di Pompei’ cv., Marzatica landrace) has been cultivated as bunching onion according to the guidelines included in the Protected Designation of Origin for CN in a farm located in Scafati (SA, Campania Region, Italy). The field experiment was conducted on sandy loam soil (4.8% clay, 18.6% silt, 76.6% sand) with a pH of 7.2, electrical conductivity of 0.501 dS m⁻¹, total nitrogen of 1.9 g kg⁻¹, and organic matter content of 3.56%.

Soil preparation for transplanting included plowing (40 cm depth), harrowing, and leveling to bring the soil into the ideal tilt for optimal water drainage. Seeds were sowed on 3 August 2021 in a seedbed and transplanted after 33 days in the experimental field with a final density of approximatively 60 plants m⁻², according to a plant spacing of 2 rows across 70 cm in beds with 10 cm and 5 cm spacing between plants on the rows and between rows, respectively.

After transplanting, initial (starter) fertilization was performed for all treatments, supplying 97 kg ha⁻¹ of N and 111 kg ha⁻¹ of S. Further nutrient supplies have been elaborated using CAL-FERT^® software for a preliminary evaluation of plant N uptake as compared with the standard dose (commercial control) adopted by the grower.

The CAL-FERT^® model has been developed for the fertilization management of many herbaceous crops, with particular emphasis on open field vegetables. A detailed description of all algorithms implemented in the model and information on how to run simulations have been extensively reported by Massa et al. [16]. In brief, based on several pedoclimatic inputs, the software can simulate N, P₂O₅, and K₂O balance in the root zone. The main model outputs consist of the following: (i) the recommended quantity of N, P₂O_5, and K₂O to be supplied by fertilizers to the crop, and (ii) a dynamic simulation throughout the cultivation of the nutrient balance into the soil to make decisions on the correct fertilizer distribution. However, for the abovementioned preliminary evaluation, in this study, we used the software to only evaluate the crop N uptake, assuming optimal soil initial conditions, as estimated by the software at 22.5 mg kg⁻¹ soil dry matter, and using the meteorological data for the closest reference climatic area, stored in the software database. Soil texture, organic matter, pH, and total N were set using the abovementioned soil analysis. Root depth was set at 30 cm as the standard depth as suggested by the software [16]. Then, the fertilization supply planned by the grower was proportionally adjusted to the crop N requirements to draw the other tested treatments. N was indeed chosen as a reference nutrient element for its several agronomic and environmental implications in agriculture.

Table 1. Treatments and quantity of all macronutrients delivered in each treatment with the initial and cover fertilization. The averaged percentage of all nutrients applied (Nut) is also reported relatively to the commercial control (CF). Other treatments consisted of: (i) fertilization equivalent to 50% of the N applied in the control (named F-50); (ii) fertilization corresponding to 25% of the N applied in the control (named F-25); (iii) strongly reduced fertilization compared to the control (named F-0).

Treatment	N kg ha−1	P kg ha−1	K kg ha−1	S kg ha−1	Ca kg ha−1	Mg kg ha−1	Nut %
Initial fertilization
All treatments	97	0	0	111	2	0	100
Cover fertilization
CF	159	83	158	86	70	17	100
F-50	80	41	79	43	35	8	50
F-25	40	21	40	21	17	4	25
F-0	2	0	0	0	2	0	0
Total fertilization
CF	256	83	158	196	70	17	100
F-50	176	41	79	153	35	8	58
F-25	136	21	40	132	17	4	37
F-0	99	0	0	111	2	0	16

reports a summary of the four treatments tested in the experiment as follows: (i) the commercial control treatment CF, corresponding to the standard fertilization plan of the local producer (100% of the dose); (ii) treatment F-50, where all fertilizers were reduced according to the evaluation performed with the CAL-FERT^® model, as above described, corresponding to roughly 58% of total fertilizers and 50% of cover fertilizers supplied with treatment CF; (iii) treatment F-25, where all fertilizers were reduced to roughly 37% of total fertilizers and 25% of cover fertilizers supplied with treatment CF; and (iv) treatment F-0, where all fertilizers were reduced to roughly 16% of total fertilizers and 0% of cover fertilizers supplied with treatment CF. In all treatments, except for F-0, fertilizations occurred at 36 Days After Planting (DAP), 54 DAP, 70 DAP, and 116 DAP. A detailed description of the temporal applications for each nutrient and treatment is provided in

Table 2. Detailed description of the quantity of all macronutrients delivered to the crop in each treatment as a function of the day after transplanting (DAP). Treatments consisted of the following: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); and (iv) strongly reduced fertilization compared to the control (named F-0).

Treatment	DAP	N kg ha−1	P kg ha−1	K kg ha−1	S kg ha−1	Ca kg ha−1	Mg kg ha−1
CF	36	97.0	-	111.0	-	-	-
	54	9.0	-	-	0.4	9.5	-
	70	96.0	44.2	64.0	112.9	-	9.6
	116	54.0	38.6	22.0	44.8	60	7.2
F-50	36	97.0	-	111.0	-	-	-
	54	5.0	-	-	0.2	4.7	-
	70	48.0	22.1	32.0	56.4	-	4.8
	116	27.0	19.3	11.0	22.4	30	3.6
F-25	36	97.0	-	11.0	-	-	-
	54	2.0	-	-	0.1	2.4	-
	70	24.0	11.0	16.0	28.2	-	2.4
	116	14.0	9.7	5.0	11.2	15.0	1.8
F-0	36	97.0	-	111.0	-	-	-
	54	2.0	-	-	0	2.4	-
	70	0	0	0	0	-	0
	116	0	0	0	0	0	0

.

Plants were irrigated using a drip irrigation system to restore the field capacity when rainfall events were not sufficient to preserve the quantity of easily available water in the root zone. The same equipment was also used for fertigation. Meanwhile, pest and disease management referred to the local standard agronomic techniques and CN guidelines, except for fertilization that was administered as previously detailed.

The maximum and the minimum daily air temperature was recorded throughout the cultivation period (Figure S1). The experiment lasted 160 DAP, according to CN Protected Designation of Origin protocol, when the bunching onions have been harvested.

2.2. Biomass Measurements and Tissue Analysis

Plant height and SPAD index have been recorded as non-destructive analyses to monitor the effect of the treatments during the cultivation at 104 DAP and 158 DAP (i.e., close to harvest time). The determination was performed in triplicate collecting a total of 180 measurements (60 plants per replicate) in each treatment. Plant height was measured manually using a centimeter. SPAD index readings (502 Plus, Konica Minolta Inc., Tokyo, Japan) were recorded using the middle portion of fully expanded leaves.

At the end of the cultivation, according to CN Protected Designation of Origin guidelines at the first stage of bulbification, 180 mature plants (60 plants per replicate, corresponding to 1 m²) per treatment have been harvested, cleaned, and the fresh weight of the edible part was measured using a balance. A part of the harvested product (10 plants per replicate) was then collected and stored for the successive laboratory analysis.

The sub-samples were divided into leaves and bulbs. The vegetative organs were dried in a ventilated oven at 70 °C until a constant weight for dry matter (DM) determination and mineral analyses were achieved. The bulbs were peeled and homogenized in order to prepare a uniform onion puree. The dry matter content was determined in an aluminum tray after dehydration in a ventilated oven at 70 °C until a constant weight was reached. Part of the onion puree was instead filtered through two layers cheesecloth and then centrifuged at 12,000 rpm for 3 min. The extract has been used to measure both as follows: total sugar content (°Brix) using a portable refractometer and pungency expressed as pyruvic acid content (pyruvate assay), as reported by Gallina et al. [13].

NO_3- content has been analyzed in the leaf and bulb dry matter according to Cataldo et al. [20]. In brief, the assay is based on water extraction and the measurement of the spectrophotometric absorbance detected for the complex formed by nitration of the salicylic acid under highly acidic conditions [21]. The determination of organic Total Kjeldhal Nitrogen (TKN) was performed by titration with 0.1 N HCl.

Finally, the agronomic fertilizer use efficiency (NUE, t kg⁻¹ N) was calculated, using N as the reference element of all macronutrients and as the ratio between yield (Y, t ha⁻¹) and the amount of N supplied in each treatment (kg ha⁻¹).

2.3. Statistics

Each treatment was applied to an area of approximatively 500 m² and the measurements were performed randomly with three replications of 1 m² of 60 plants each.

Data were subjected to one-way analysis of variance (ANOVA) separately per nutrient treatment effect (namely, CF, F-50, F-25, and F-0). Differences among means were performed by the least significant difference (LSD) multiple range test (p < 0.05).

Analysis of variance (ANOVA) and LSD test were computed using Statgraphics XV.II software. GraphPad Prism 6.0 software was used to perform graphs.

3. Results

Plant height and SPAD readings have been recorded at 104 DAP and 158 DAP to evaluate the vegetative and chlorophyll response of the crop trough non-destructive measurements to different nutrient applications (Figure 1). Plant height, at 104 DAP (Figure 1A), was reduced only by the extreme treatment F-0 compared with the other treatments. Subsequently, at 158 DAP (Figure 1B), higher plant growth was observed for the F-50 treatment compared with CF, while the other two treatments were furtherly reduced, with F-0 ranking last. The SPAD index revealed a lower chlorophyll content for reduced fertilization with the lowest value observed for F-0 at 104 DAP (Figure 1C) and 158 DAP (Figure 1D). CF treatment indeed showed the highest SPAD indexes at 104 DAP, but no significant difference was observed between CF and F-50 at 158 DAP.

Total yield and NUE are reported in Figure 2A,B, respectively. Despite the lowest production, the F-0 treatment showed the highest NUE, whilst F-50 showed a superior yield compared with CF and F-25 but the same NUE of F-50. Indeed, CF nutrient supply showed the lowest NUE with an intermediate value for the production of edible fresh onion bulbs.

DM content for leaves and bulbs, as well as other qualitative parameters of the fresh bulb are reported in

Table 3. Effect of nutrient treatment on qualitative parameters for leaves and bulbs of “Cipollotto Nocerino” spring onion fertilized with: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); (iv) strongly reduced fertilization compared to the control (named F-0). Data are mean values (n = 30). Different letters between brackets within each treatment indicate statistical difference according to LSD multiple range test after one-way analysis of variance (ANOVA). Letters were not reported when the effect of the treatment was not statistically significant. Significance level:; ** p ≤ 0.01; * p ≤ 0.05; ns = not significant.

Treatment	DM 1 Leaves (%)	DM 1 Bulbs (%)	Soluble Solid Content (°Brix)	Pyruvate (µM g−1 FW 2)
CF	10.3 (bc)	51.47 (bc)	9.8	2.62 (a)
F-50	9.67 (c)	48.37 (c)	9.4	0.96 (b)
F-25	10.63 (ab)	53.17 (ab)	9.9	1.05 (b)
F-0	11.27 (a)	56.23 (a)	10	1.01 (b)
ANOVA	*	*	ns	**

¹ dry matter (DM); ² fresh weight (_FW).

. CN spring onion managed according to the F-0 strategy revealed the highest level for the DM content in the epigeous apparatus (leaves), whilst F-50 reported the lowest value. Similarly, the fresh bulbs collected from CN plants cultivated according to F-0 nutrient supply reached 56.2% for DM content, almost 9% higher compared with the mean value reported for F-50. For both organs, F-25 and CF showed intermediate DM contents. Regarding soluble solid content, expressed as °Brix, there were no differences among treatments. Whilst the pyruvate content was significantly affected by the nutrient supply strategy adopted, indeed its content was almost double for the control (CF) compared to F-50, F-25, and F-0. According to the literature, the pungency classification reports the following scales based on pyruvic acid concentration: 0–3 µmol g⁻¹ _FW corresponded to the low pungency category, >3–7 µmol g⁻¹ _FW refers to an intermediate level of pungency, and >7 µmol g⁻¹ _FW refers to highly pungent onions [21,22]. Based on the abovementioned classification, all fertilizations produced low-pungency onions, as expected for CN bunching onion.

Nitrogen content in leaves and bulbs is reported in

Table 4. Effect of treatments on tissue nitrate (NO³⁻), TKN (Total Kjeldahl Nitrogen) content (expressed on dry weight, except for nitrate) for leaves and bulbs of “Cipollotto Nocerino” spring onion fertilized with: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); (iv) strongly reduced fertilization compared to the control (named F-0). Data are the mean values (n = 30). Different letters between brackets within each treatment indicate statistical difference according to LSD multiple range test after one-way analysis of variance (ANOVA). Letters were not reported when the effect of the treatment was not statistically significant. Significance level: *** p ≤ 0.001; ns = not significant.

Treatment	NO3− (mg kg−1 Bulbs FW 1)	TKN (g kg−1 Leaves)	TKN (g kg−1 Bulbs)
CF	2011.8	24.9 a	9.93
F-50	2232.7	24.4 a	11.1
F-25	2482.7	23.3 a	8.83
F-0	1963.8	16.7 b	7.67
ANOVA	ns	***	ns

¹ fresh weight (_FW).

. No differences among treatments were recorded for NO³⁻ and TKN in bulbs. Instead, TKN levels in the leaves were higher for CF, F-50 and F-25 compared to F-0.

4. Discussion

4.1. Crop Vegetative Parameters

Preserving nutritional quality and yield while matching legislative strategies focused on the reduction in agrochemicals is one of the main challenges of the current agriculture. The use of decision support systems to improve agronomic techniques can play a crucial role in modifying compositional methods and in promoting quality-oriented sustainable agriculture. Furthermore, the optimization of the use of chemical fertilizers may have direct implications for environmental safety and both food security and quality [12], in particular for vegetables consumed as fresh products, such as bunching onion.

The results of the present research demonstrated a possible notable reduction in the application of fertilizers commonly used for CN spring onion without any detrimental effect on yield, qualitative, and vegetative parameters.

Plant height and SPAD are two important parameters related to vegetative growth which have been deeply investigated as a response to N applications in several crops [17,23]. Indeed, it is well known that the reduction in essential macronutrient can negatively affect plant growth by impairing nutrient absorption and then plant metabolism trough the inhibition of the synthesis of many important molecules like amino acids, proteins, nucleic acids, chlorophyll, etc. [24,25]. In our research, both the vegetative parameters have been recorded at two growing stages as follows: 104 and 158 DAP, in order to emphasize the effect of different temporal applications of fertilizers. The results (Figure 1A–D) clearly demonstrated no differences among treatments F-50 and F-25 at 104 DAP, whilst F-50 revealed the highest height and SPAD readings at 158 DAP. Conversely, only the F-0 treatment showed the lowest height and SPAD readings at 104 and 158 DAP. Therefore, during the growing cycle, a significant reduction in the applied fertilizer (up to 50% compared to CF) did not affect the vegetative growth. Only the chlorophyll content at 104 DAP for the CF treatment was higher, but no differences were detected compared with F-50 at the end of the cultivation.

The depicted results are in line with those of Abdissa et al. [26] who investigated the effect of different levels of N and P fertilizations on the growth, biomass, and fresh bulb yield of an onion crop in the Ethiopian environment. Interestingly, in that study too the highest vegetative response corresponded to intermediate levels of fertilization compared with the commercial fertilization practice in the country. In more detail, the application of 69 kg ha⁻¹ of N increased plant height, leaf length as well as bulb diameter, and average bulb weight compared with 138 kg ha⁻¹. Similarly, De Oliveira et al. [27] applied several organomineral fertilizers in order to investigate the release of different amounts of nutrients and agronomic response of onion crops. The authors showed the results of five different treatments corresponding to a rate reduction equivalent to 100%, 80%, 60%, 40%, and 20% of the N commercially applied, and they evaluated several parameters, including the following: SPAD index at different DAP and yield and chemical composition of onion bulbs. In their case too, De Oliveira and colleagues recorded the best performance for SPAD index and onion yield for the treatments corresponding to a 20% reduction in fertilization compared with conventional (commercial) practices.

In absolute terms, combining all results for plant height and SPAD readings at 158 DAP, the treatment F-50 corresponded to the best vegetative growth, even if a reduction of 50% of total macronutrients was applied compared with CF. In line with the vegetative parameters, the maximum yield (Figure 2A) was achieved in treatment F-50, which gave a production of 88.7 t ha⁻¹, roughly 10% higher compared with CF. Remarkably, the “intermediate” treatment F-25 showed a production of 76 t ha⁻¹, which is not significantly different from CF. Therefore, the F-50 and F-25 treatments showed NUE values 40% higher compared with CF, but without any significant reduction in the final yield. These findings are in line with Salo [28] and Jensen and Sanders [29], who demonstrated that reduced fertilizations compared with commercial practices, or even residual N mineralization, are enough to sustain an appreciable yield [28,29].

Onion is a relatively salt-sensitive crop; indeed its electrical conductivity (EC) threshold level is low because it belongs to glycophytic vegetables [30]. For instance, Venâncio and colleagues conducted experiments with saline water (0.65, 1.7, 2.8, and 4.1 dS m⁻¹) on ‘Rio das Antas’ onion plants [31]. The authors detected negative effects of water salinity to onion crop physiology in terms of bulb fresh weight, yield, water use efficiency, firmness, bulb pH, and membrane stability. Furthermore, an investigation conducted on the bunching onion variety ‘Merveille de Pompei’ (a closely related variety to CN) demonstrated the detrimental effect of saline water (EC higher than 1.41 dS m⁻¹) on bulbification and vegetative parameters that lead to a reduction in commercial yield up to 50% [32]. Therefore, in line with our findings, the treatments corresponding to the highest level of fertilization likely had a negative effect on vegetative and qualitative parameters as previously observed.

However, the results shown for plant height and SPAD readings, referred to the initial time lag (from 0 to 104 DAP), revealed the need to deeply investigate the effect of splitting N fertilizations into several applications and its effect in CN bunching onion to optimize nutrient supply and distribution throughout the cultivation. A recent investigation on short-day onion showed the higher efficiency of splitting total crop N fertilizer into several applications throughout the growing season [33]. The authors found that the timing of application should be synchronized with actual plant N demands at different stages of growth [33]. Indeed, splitting N fertilizer applications can enhance yield and NUE compared to fewer applications [34]. Abundant fertilizations after transplanting are not useful, because the absorption ability of the young plant is low. Moreover, soil N levels in the root zone should not exceed the crop requirements, in order to reduce the residence time of N in the soil and lower the risk of leaching [33]. In onion crops, fertilizer use efficiency (e.g., NUE) is generally low due to its sparse root system, which increases the risk of nitrate leaching below the root zone with percolating water. The agronomic practices that avoid a buildup of N in the root zone (N exceeds the crop requirement) are crucial to achieving a high NUE and decision support systems could foster this achievement [15,35]. In this work we used CAL-FERT^® to evaluate plant nutrient uptake and support the setup of the different treatments. CAL-FERT^® is a software that performs simulations based on a crop database built with data collected from the literature. One of the secondary objectives of this kind of study was indeed the validation of the model under real cultivation conditions. As a matter of fact, the model was able to suggest different treatments for the optimal and suboptimal fertilization of the onion crop. Our findings demonstrate that simulation models are useful tools for properly managing nutrient fertilization, preserving environmental features, and reducing production costs.

In our research, the treatment corresponding to the negative control (F-0) showed the highest DM content for both leaves (11.27%) and bulbs (56.23%), whilst the lowest values were recorded for F-50 in both epigean (9.67%) and hypogeum (48.37%) apparatuses (Table 3). In a recent investigation on the effect of organic and conventional management at different N doses, the higher the amount of fertilizer applied, the higher the DM content in bulbs [9]. Furthermore, our results suggest a similar behavior in DM partitioning among treatments and, according to Kinoshita and co-authors, in onion, the DM content in leaves constitute around 20% of total DM [36]. Our findings are in accordance with Amare, who reviewed the effects of mineral nutrition on onion crop physiology [37]. Indeed, under N deficiency, the onion plant prioritizes allocating the limited N amount to the bulb, leading to a higher dry matter content [37].

4.2. Tissue Analysis and Quality Parameters

Regarding qualitative parameters, no differences among treatments were recorded for soluble solid content, whilst pyruvate content (indicator of pungency) was higher in the control compared with the treatments. Our findings are partially in contrast with Golubkina and co-authors, most probably because our investigations were conducted on bunching onion (immature bulbs) instead of full mature bulbs and also because we used a different genotype [9]. Indeed, the influence of environmental conditions on onion performances of several genotypes have been clearly demonstrated for yield and other quantitative and qualitative features [38]. Actually, our findings demonstrate an improvement of qualitative attributes (low pungency) through an optimization of nutrient supply for F-50, F-25, and F-0 treatments. Indeed, CN is mainly consumed as fresh bunching onion in salad and its low pungency is a positive characteristic for consumer demand [6].

In onion, N concentration in leaves depends on the application rate of the fertilizer and growth stage, being high in young and well-fertilized plants and low in the case of nutrient deficiency, or when close to harvest [33]. Starting from bulbification, N is translocated from the leaves to the bulbs, but in CN spring onion, the translocation process is not concluded because it is harvested as immature bulbs (bunching onion). Nutrient partitioning, reported in Table 4, did not show any difference among treatments for N content measured as NO₃₋ and TKN in bulbs, but, we recorded different responses in leaves among treatments for the nutrient. Aisha and co-authors recorded an increase in leaf number and fresh weight when N application was increased [39]. As reported in Goloubkina and co-authors, the enhanced nitrogen fertilizer rate in the rhizosphere could increase the mineral availability in the soil solution, which in turn promotes onion plant development [9]. Furthermore, as reported in Bettoni and colleagues and reviewed by Geisseler and co-authors, at harvest, approximately 65% of the total N is localized in full mature bulbs, whilst 35% is in the leaves [35,40]. Combining these results with our findings, an increase in leaf nitrogen concentration without a corresponding increase in bulb nitrogen is due to N allocation from leaves to bulbs as storage organs. As the bulb develops, the nitrogen is translocated from the leaves to the bulb, resulting in a higher nitrogen concentration in the bulb at harvest, according to Goloubkina et al. [9]. In our experiment, CN spring onion are harvested as immature bulbs; therefore, N translocation to the storage organs (bulbs) did not occur.

Therefore, it is fundamental to address nutrient management in order to preserve quality in spring onion consumed as a fresh vegetable.

5. Conclusions

CN spring onion is consumed as a fresh vegetable, and its quality is strictly affected by agronomic techniques which are mainly based on consolidated protocols at the local level and based on the growers’ experience and practices. In our research, the Decision Support System CAL-FERT^® has been applied on CN spring onion as a crop model in order to optimize fertilization and to investigate qualitative and quantitative parameters. Our results clearly identified the highest NUE, SPAD readings at 158 DAP, without affecting SSC, pyruvate, and NO³⁻ contents of onion bulbs for the treatments F-50 and F-25. Moreover, further investigations (e.g., split applications in 0–104 DAP) are needed in order to match nutrient availability with nutrient demand, without any detrimental effect on qualitative parameters.