Real-Time Nutrient Management in Hydroponic Controlled Environment Agriculture Systems Through Plant Sap Analysis

Abstract

Global food production must meet the dietary requirements of a growing population, which is expected to reach 8–11 billion by 2100, while reducing the environmental impact of agricultural practices. The agricultural sector accounts for 21–37% of global greenhouse gas emissions, 70% of freshwater, and contributes considerably to biodiversity loss and challenges that are further intensified by climate change. Controlled Environment Agriculture (CEA) serves as a sustainable strategy to address global food production and promote consistency and resource-efficient crop production. However, nutrient imbalances remain a key challenge in hydroponic CEA systems. To address these nutrient-related challenges, plant sap analysis is being considered as real-time monitoring tool and precise nutrient management in CEA systems. Compared to traditional nutrient tissue analysis, sap analysis shows stronger correlations with crop performance during active growth. For instance, petiole sap nitrate-nitrogen (NO₃⁻-N) and total nitrogen (N) in tomato leaves show correlation coefficients of r = 0.6–0.8 during their rapid vegetative growth stages. Sap analysis shows potential improvements in nutrient efficiency, crop quality, and sustainability within CEA. This review investigates the principles, methodologies, and advancements in plant sap analysis, contrasting it with traditional nutrient testing methods. It also addresses challenges such as variability in sap composition, the lack of standardized protocols, and economic considerations, while emphasizing real-time nutrient management to achieve and sustainability in CEA.

1. Introduction

Global food production faces the dual challenges of meeting the needs of a population projected to reach 8–11 billion by 2100, while reducing agriculture’s environmental impact. Agriculture currently occupies approximately 38% of the Earth’s land surface, accounts for nearly 70% of freshwater withdrawals, and remains the primary driver of biodiversity loss due to land use change, agrochemical inputs, and pollution [1,2].

CEA has emerged as an innovative approach to address these challenges by enabling sustainable, climate-resilient food production in greenhouses and vertical farms or indoor plant factories, where key environmental factors, including light, temperature, humidity, carbon dioxide (CO₂) concentrations, and nutrient delivery, are precisely regulated to optimize crop performance and resource efficiency [1,3]. Climate change aggravates global agriculture challenges, including extreme climatic conditions such as drought, flooding, and heatwaves—an alarming situation for global food security and the long-term sustainability of agriculture [4]. Meeting the rising global food demand using conventional farming is becoming more challenging due to issues around soil degradation, eutrophication, and deforestation [5,6]. CEA systems are designed to improve efficiency, resilience, and sustainability by managing variables such as humidity, temperature, and the movement of water and nutrients in vascular tissues, allowing for the precise management of crop growth conditions and providing production throughout the year, with significantly reduced resource requirements [7,8]. CEA reduces pest and disease pressure, minimizes resource degradation, and incorporates advanced technologies, such as optimized light-emitting diodes (LEDs), Internet of Things (IoT)-driven automation, and renewable energy sources, that enhance both productivity and effectiveness [9]. For example, urban CEA operations in cities such as Paris and Dubai have demonstrated the adaptability of these systems to metropolitan areas and extreme climatic conditions [10,11]. However, CEA technologies have expanded into space biology, as confirmed by the National Aeronautics and Space Administration (NASA) project called “Veggie”, which has more advanced techniques used in self-sustaining food systems in space [12].

In CEA, nutrient management plays a crucial role in optimizing crop performance, promoting environmental sustainability, and enhancing the efficiency of resource use. Most CEA facilities use hydroponics systems for water and nutrient delivery. Unlike soil-based systems with inherent nutrient buffering capacity, hydroponic systems carry a higher risk of nutrient imbalances due to limited buffering capacity, rapid nutrient mobility, the potential accumulation of toxic ions, and vulnerability to pathogen proliferation under suboptimal conditions [13]. Effective nutrient management is crucial for CEA systems to mitigate nutrient-related issues, ensure high yields, and reduce environmental impacts such as N and phosphorus (P) contamination [1]. As a result, advanced diagnostic techniques are necessary for real-time monitoring of nutrient movement in sustainable CEA production.

Plant sap analysis is an emerging diagnostic method in CEA that allows for the immediate monitoring of plant nutritional status via the analysis of fluid obtained from xylem and phloem tissues, while comparing it with traditional soil and tissue testing. It enables the early detection of nutrient deficiencies, toxicities, and imbalances, allowing for timely corrective actions before visible symptoms appear [14,15]. Plant sap analysis differs from traditional tissue testing by measuring nutrient status in real-time through mobile ions in xylem or phloem. While tissue testing reflects accumulated nutrient contents over weeks, sap analysis reflects immediate uptake and absorption of nutrients, providing dynamic findings to guide timely nutritional strategies that enhance plant health and crop productivity [16]. Plant sap analysis provides significant advantages for CEA systems by enabling real-time assessments of plant nutrient status and supporting timely fertigation adjustments [17]. Despite these advantages, challenges, such as variability in sap composition, the absence of standardized sampling and analytical techniques, and the high cost of advanced analytical equipment, remain bottlenecks for broader implementation [15].

This review critically evaluates the principles, methodologies, and applications of sap analysis in hydroponic CEA systems. It examines extraction techniques, analytical tools, nutrient interpretation frameworks, and implementation barriers, and compares sap analysis with traditional nutrient testing methods. This review emphasizes the importance of sap in the real-time monitoring of nutrients, deficiency detection, and precise fertilization management, and discusses various challenges, including consistency, cost-effectiveness, and research gaps, while highlighting the future improvements and potential applications of plant sap analysis when combined with advanced technologies such as machine learning (ML), automation, and IoT.

2. Principles of Plant Sap Analysis

2.1. Definition

Plant sap analysis is considered a real-time diagnostic technique used to monitor plant nutrient status by analyzing the fluid extracted from vascular tissues. Xylem sap, primarily composed of inorganic ions such as NO₃⁻, K⁺, and Ca²⁺, transports nutrients from roots to shoots, while phloem sap is enriched with sugars, amino acids, and organic-N compounds, moving from source to sink tissues [14,18]. Traditional soil and plant tissue analysis offers a comprehensive historical record of nutrient accumulation, but does not reflect current uptake. In contrast, plant sap analysis can detect early nutrient imbalances before they affect plant growth and allows for timely adjustments of fertilization strategies [19]. Plant sap is analyzed for NO₃⁻-N and sugar content to evaluate plant metabolism and water uptake efficiency [20,21]. Unlike traditional methods, sap analysis allows growers to monitor uptake in real-time. Table 1 summarizes the differences between conventional nutrient testing and plant sap analysis.

Sap extraction from petioles has been practiced since the early 20th century, when Treub (1923) first correlated sap nutrient levels with plant growth [22,23]. Later, Hochmuth (1994) developed a semi-quantitative method for assessing inorganic nutrient levels [19]. These advancements enable growers to compare sap nutrient concentrations with established sufficiency ranges to identify nutrient deficiency, sufficiency, excess consumption, or toxicity [24,25]. Plant sap composition is influenced by several environmental and physiological factors, including light intensities, fertilization regimes, phenological stage, and sampling protocols, highlighting the need for standard protocols for accurate interpretation [26,27].

Table 1. Comparison between traditional nutrient testing and plant sap analysis.

Features	Traditional Nutrient Testing	Plant Sap Analysis	Reference
Time for Results	Hours to days	Real-time	[19]
Sample Type	Dried leaves	Fresh plant sap	[24]
Precision	Retrospective	Immediate	[15]
Application	Post-harvest	Real-time crop monitoring	[14]
Nutrient Availability	Limited and shows past nutrient levels	Immediate and reflects current plant uptake	[18]
Technical expertise	Laboratory staff needed to perform sample digestion and operate autoanalyzer	Grower or technician must be trained to extract sap	[28]
Equipment	Drying ovens, grinders, and digestion apparatus	Sap press or portable meters required	[28]
Accuracy and precision	Standardized method with established sufficiency ranges	Expertise required because of variability	[28]
Cost analysis	Lower due to established standards	Higher due to special equipment and processing	[28]
Environmental sensitivity	Less sensitive to short-term changes	Highly sensitive to time of day, hydration, and temperature	[28]
Application frequency	Often used at specific stages or annually	Suitable for frequent monitoring during key growth stages	[28]

Table 1. Comparison between traditional nutrient testing and plant sap analysis.

Features	Traditional Nutrient Testing	Plant Sap Analysis	Reference
Time for Results	Hours to days	Real-time	[19]
Sample Type	Dried leaves	Fresh plant sap	[24]
Precision	Retrospective	Immediate	[15]
Application	Post-harvest	Real-time crop monitoring	[14]
Nutrient Availability	Limited and shows past nutrient levels	Immediate and reflects current plant uptake	[18]
Technical expertise	Laboratory staff needed to perform sample digestion and operate autoanalyzer	Grower or technician must be trained to extract sap	[28]
Equipment	Drying ovens, grinders, and digestion apparatus	Sap press or portable meters required	[28]
Accuracy and precision	Standardized method with established sufficiency ranges	Expertise required because of variability	[28]
Cost analysis	Lower due to established standards	Higher due to special equipment and processing	[28]
Environmental sensitivity	Less sensitive to short-term changes	Highly sensitive to time of day, hydration, and temperature	[28]
Application frequency	Often used at specific stages or annually	Suitable for frequent monitoring during key growth stages	[28]

2.2. Historical Evolution and Contemporary Advancements

The methodology and interpretation of sap analysis have evolved significantly over the past century. Gilbert & Hardin (1927) [29] pioneered sufficiency ranges in plant sap analysis, while Dr. Pettinger and Arnon (1930s) in the United States (US) established the relationship between plant sap nutrient concentrations and fertilizer regimes [19,30,31]. In Europe, Carolus (1935) [32] and Bray (1945) [33] investigated sap testing for elements such as N, P, K, Mg, and Mn. Technological advancements in the 1970s introduced ion-selective electrodes and portable colorimeters for on-site testing [19,34].

The introduction of ion meters (Cardy; Horiba Ltd., Kyoto, Japan) in the 1980s enabled growers to measure sap NO₃⁻ and K⁺ within minutes and improved accuracy [35]. By the early 2000s, sap analysis techniques had begun to make significant advancements, focusing on quick nutrient testing with the help of portable devices in both vegetable and greenhouse crops [36,37]. Those innovations provided immediate decision-making and enhanced nutrient use efficiency, ultimately improving productivity and sustainability.

Recent advancements in sap analysis are addressing several challenges, such as nutrient imbalance and diseases like Huanglongbing (HLB) in citrus [17]. By enabling the early detection of nutrient deficiencies, sap analysis serves as a valuable tool for improving fertilizer efficiency and managing crop health. Integrating sap analysis in nutrient management strategies in CEA can allow for growers to make early adjustments in nutrient solution to avoid disease outbreaks and enhance crop quality and yield [17].

2.3. Comparison with Traditional Soil and Tissue Analysis Methods

Traditional plant tissue and soil analysis have long served as the foundation of nutrient management in agriculture. Soil tests determine the critical information of nutrient availability in growing medium, while tissue analysis measures the concentration of nutrients in plant parts, particularly in leaves and stems, to guide fertilization and ensure optimal growth. However, in CEA, where the rapid modification of nutrients is essential, traditional methods are limited and demand real-time diagnostic methods for precise nutrient management [18,26]. Sap analysis provides immediate data for mobile nutrients such as N in the form of nitrates (NO₃⁻), enabling growers to test quickly and evaluate the plant’s N status. However, it is important to note that not all N in sap exists as NO₃⁻. Depending on the tissue and transport pathway, N is also present in organic forms such as amino acids or amides, especially in phloem sap. Thus, accurately assessing sap N forms is critical in hydroponic systems, where N is the primary constituent for plant growth and productivity. While sap analysis does not replace traditional tissue analysis, it serves as a complementary method by offering a rapid, on-site diagnostic tool that supports real-time nutrient management [19,27]. This capability is particularly valuable in CEA, where nutrient imbalances can rapidly affect crop performance. However, sap analysis does not always correlate well with traditional tissue nutrient analysis, especially during vegetative stages. For example, Locascio et al. [38] found correlation coefficients (r) ranging from −0.2 to 0.8 between petiole sap NO₃⁻-N and total nitrogen (TN) in tomato (Solanum lycopersicon) leaves. These strongest correlations (r = 0.6–0.8) were observed during 6–8 weeks after transplanting, corresponding to rapid vegetative growth. In contrast, Carson et al. [39] reported no significant correlation between sap NO₃⁻-N and tissue TN 14 weeks after transplanting, when the plants are in the fruiting stage. Shamshiri and Taiz et al. [40,41] noted that, during the fruiting and senescence stages, NO₃⁻-N is redirected to reproductive sinks, thus weakening the sap–tissue relationship. Several studies indicate that sap analysis is a faster and reliable method compared to the standard method. Hence, it is an attractive option for monitoring nutrients in CEA, which requires continuous monitoring of nutrients. For example, Nagarajah et al. [42] highlighted the efficiency of nutrient management through sap analysis in grapevine (Vitis vinifera), while Gangariah and Rodriguez et al. [43,44] emphasized the potential for improving nutrient diagnostics in high-intensity agriculture systems.

Despite its advantages, sap analysis is influenced by environmental factors such as light, humidity, temperature, and plant developmental stages, requiring the careful interpretation of results. For instance, the nutrient solution composition influences the readings, indicating that decreased concentration of NO₃⁻, H₂PO₄⁻, calcium (Ca²⁺), and magnesium (Mg²⁺) in tomato plant sap [45], and reduced light intensity during the autumn–winter cycle negatively affects the nutrient uptake in tomato plants [46]. Those findings underscore the significance of environmental factors in interpreting sap analysis results in CEA.

In CEA systems, sap analysis is widely used for monitoring NO₃⁻ levels in crops, such as tomatoes and grapevines, where precise N management is critical. For example, Tei et al. [47] demonstrated a critical N curve for processing tomatoes, providing a tool to growers to optimize N application. Similarly, measuring sap NO₃⁻ extracted by petioles is widely applicable for processing tomatoes, showing its effectiveness in nutrient management [48,49], while research on the ‘Sultana’ grapevine [42] has demonstrated the benefits of sap testing with test strips used to measure NO₃⁻ and K⁺ concentrations in petiole sap, giving a rapid and accurate assessment of nutrient status. Although this approach correlates well with traditional tissue analysis, variation in nutrient concentration due to factors such as time of day emphasizes the importance of standardized protocols.

3. Methods for Sap Extraction and Sampling Protocol

3.1. An Overview of Extraction Methodologies

The reliability and accuracy of sap analysis are highly dependent upon the extraction method used. In CEA, where environmental factors are meticulously controlled, standardized sap extraction protocols are essential to ensure consistency and comparable results. Several sap extraction methodologies exist, each with its own limitations and advantages, depending on the plant species, cultivar, tissue type, and target nutrient. Sap extraction methods can be broadly categorized into mechanical, physical, and chemical extraction techniques. Mechanical pressing of plant tissues is the most widely used method, which involves crushing plant tissues from 5 to 10 mm to 1 cm in diameter, such as leaves/petioles, using a garlic/hydraulic press to release the sap. Different non-reactive materials, such as PVC, stainless steel, or nylon, are often used to prevent contamination that could interfere with nutrient readings inside the sap [16].

Several studies have confirmed that this technique can be effective for crops such as sweet peppers (Capsicum annuum) and tomatoes, where petioles can be easily crushed into 5–10 mm slices to extract the sap [50]. Rodríguez et al. [44] employed a similar technique, using large petioles and approximately 1 cm slices for sweet pepper sap analysis in the greenhouse. However, a significant amount of variation in sample handling, such as washing petioles before pressing, can substantially impact nutrient concentrations. For instance, Ferneselli et al. [14] found that washing petioles before pressing muskmelon (Cucumis melo) and sweet pepper decreased NO₃⁻ and K⁺ levels compared to pressing entire petioles.

Physical methods, such as the freeze–squeeze method, are another common approach that can be used in CEA systems to enhance nutrient release. In this method, plant tissues are placed inside a syringe and are sealed and stored at −20 °C for two hours before being thawed and pressed to release the sap [42]. The freezing process induces intracellular ice crystal formation, which breaks down cells, facilitating the release of more K. Studies showed that this method, by dipping plant tissues in 98% ethyl ether before freezing, increases crystallization of tissues and improves N and K during pressing [51]. The dry-freezing extraction method was adapted from Ostapowicz et al. [52] using liquid N, with the modification of plant tissue. Fresh plant tissues were immediately frozen in liquid N, ground into a fine powder, and extracted with ammonium acetate (Fisher Scientific, Waltham, MA, USA), followed by the addition of deionized water [53]. This technique minimizes oxidation and preserves nutrient integrity and making it ideal for nutrient analysis.

Chemical extraction methods, which utilize various chemical reagents such as potassium chloride (KCl; Sigma-Aldrich, St. Louis, MO, USA) and ammonium acetate, are often employed in CEA for detaching nutrients. In KCl extraction, leaves and petioles are chopped into different pieces and incubated in a 0.1 N KCl solution, shaken for 15 min, and filtered the solution by using Whatman No. 1 filter paper (Cytiva, Buckinghamshire, UK) [54]. Similarly, ammonium acetate extraction involves incubating plant petioles and leaf tissues in a 0.1 N ammonium acetate solution, followed by shaking and filtration [53]. These methods are simple and extract both free and loosely bound ions for real-time plant nutrient status. In ethyl ether extraction, plant tissues are cut into 1–2 cm pieces, frozen overnight in ethyl ether, and then shaken and filtered. The resulting sap settles at the bottom and is separated from the plant pigment dissolved in ether [55]. This method is effective, but is impractical for regular use due to the use of volatile solvents and the requirement for overnight freezing. Although not a sap extraction method, traditional dry-tissue analysis remains a common approach for long-term nutrient determination in CEA. This method involves collecting plant leaves or stems, which are oven-dried at 65 °C to remove moisture, ground into a fine powder with a Wiley Mill (Thomas Scientific, Swedesboro, NJ, USA), and digested with nitric acid (Fisher Chemical, Waltham, MA, USA) at 115 °C for two hours before nutrient analysis [56]. Although this method provides comprehensive nutrient data, including a wide range of macro- and micronutrients, it lacks the real-time diagnostic capabilities of sap analysis, which is important for fertigation strategies in CEA.

3.2. Factors Affecting Sap Extraction Effectiveness

The effectiveness of sap extraction methods depends on several factors, including pre-sampling environmental conditions, processing time, tissue type and age, and pressing methods, which must be carefully controlled to ensure reproducible and accurate results in CEA. The plant’s hydration directly affects the volume of sap and the concentration of solutes. Well-watered plants yield more sap, while drought-stressed plants may have very little sap to extract and higher solute concentrations. To ensure consistency, sap samples should be collected at a time when plants are fully turgid (e.g., a couple of hours after irrigation) for maximum sap and consistent readings [17,57]. Extreme conditions, such as very high light or heat right before sampling, can temporarily concentrate or dilute sap due to transpiration effects [36]. For consistent results, maintain the same light and temperature conditions at sampling times, or at least note them. In indoor vertical farms, if lights turn on at 8 AM and we always sample at 9 AM, that condition should be reproducible daily. The type of plant tissue selected for sap extraction plays a critical role in determining the accuracy of the results. Petioles from the most recent fully expanded leaves are commonly useful for monitoring mobile nutrients like N, P, and K, as they reflect the plant’s current nutrient uptake and translocation pattern [50]. However, this recommendation is not universal. For example, crops like sugarcane (Saccharum officinarum) and broccoli (Brassica oleracea) variety ‘Italica’ have midribs/leaf blades that are more effective for sap extraction due to their higher nutrient concentration and structural suitability [58,59]. The selection of tissue type should be aligned with the nutrient and remain consistent across the samples to ensure the results.

The age of the tissue sampled is another factor that influenced sap nutrient concentration in CEA. Commercial labs offer both old and new leaves for checking nutrient concentrations. In many greenhouse crops, sap analysis is performed using recently matured leaves, particularly when targeting mobile nutrients like N that translocate from older tissues to younger growth [14]. A factor often ignored is the pressure applied in extraction. Hand pressure will vary by user, but a hydraulic press can be set to a certain desired pressure. If one sample is pressed gently and another is pressed very hard, nutrient concentrations in the sap might differ (pressing extremely hard might squeeze out extracellular contents or even grind some structural material into the sap). Setting standard pressures or pressing times improves consistency. For most practical purposes, “press until no more juice comes out” is the rule of thumb. However, in research, quantifying that pressure ensures that each sample is processed equally. Hence, pressing and crushing are part of the sap extraction process; therefore, it is essential to use presses or crushers made of non-reactive materials, such as PVC, stainless steel, or nylon, to prevent contamination and ensure reliable and accurate sap results. Garlic crushers are particularly effective for extracting sap from fleshy plant tissues such as potatoes, sweet peppers, and tomatoes [17].

4. Improving Sampling Strategies for Sap Analysis

4.1. Considerations of Timing and Frequency

The environment is controlled in CEA facilities, so diurnal changes are less extreme than in the field. Nevertheless, light and temperature cycles in greenhouses will cause fluctuation in nutrient uptake and water content. Diurnal variations mean that timing can influence sap readings. Studies have demonstrated that tomato sap showed higher concentrations of NO₃⁻, ammonium (NH₄⁺), and H₂PO₄⁻ in the afternoon [60]. In grapevine, sap K⁺ levels show a 50% reduction in the afternoon compared to the morning values, due to diurnal transpiration peaks affecting ion transport and dilution within xylem sap [42]. Such temporal variability underscores the need to standardize sampling times (e.g., early morning) to minimize diurnal effects and ensure comparability between samples. One study on potatoes (Solanum tuberosum) found sap NO₃⁻ levels peaked around noon to mid-afternoon, then declined at night, suggesting strong diurnal variation [61]. While this trend was observed under specific conditions, it may vary depending on cultivar, developmental stage, and environmental factors, such as light intensity and irrigation timing. Sampling at different times (e.g., 6 PM vs. 10 AM) can produce variable results due to diurnal effects. Establishing a fixed daily schedule and consistent weekly frequency improves data reliability. In tomatoes, stable N levels are obtained when petioles are consistently sampled from the most recent fully expanded leaves, allowing for the representation of both old and new tissues. Perennial crops crop in open field conditions require multiple seasonal samples to measure nutrient dynamics across different developmental stages [14]. In terms of frequency, sap sampling should be aligned with crop-specific nutrient dynamics, growth stages, and production systems. In greenhouse crops, frequent, lower-dosage fertigation via drip irrigation maintains stable nutrient levels. For example, in sweet pepper (Capsicum annuum L.) petiole sap NO₃⁻-N content remained relatively constant during the entire crop cycle under greenhouse conditions [44]. In contrast, Ferneselli et al. [14] reported a strong correlation (r = 0.854) between petiole sap NO₃⁻ and the nitrogen nutrition index (NNI) in processing tomato, particularly during the mid-season period, which represents the crucial phase for N management. These results indicate that sap testing can reliably guide fertigation decisions when conducted at strategic intervals, reducing the need for excessive sampling while ensuring N supply matches crop demand during peak uptake periods.

4.2. Selection of Suitable Parts and Number of Leaves

Selecting the appropriate plant tissue is critical for accurate sap analysis in CEA. The choice of plant part (petiole and leaf blade) has a significant influence on sap composition. Most established sap analysis protocols focus on leaf petioles, typically the sap-rich fleshy petioles of the most recent fully expanded leaves [15,44,48,50]. In some cases, leaf midribs (the central vein) are used instead of petioles, such as in broccoli and sugarcane, for sap tests due to their nutrient concentration [58,59]. Taking a sample from the youngest mature leaf ensures that the sample collected reflects current nutrient uptake while avoiding older tissues that may have unstable nutrient remobilization. A few private laboratories in the Netherlands even prefer extracting sap from whole leaf blades for certain crops [17]. In practice, petioles are favored for most crops due to their ease of handling and high sap content, but the optimal tissue may vary. It is essential to note the type of tissue used when comparing sap data between sources.

The optimum number of leaves required for sap extraction varies across crops due to differences in tissue moisture content, structure, and sap in CEA. In tomatoes and potatoes, researchers commonly collect about 20–25 petioles and leaves from the most recent fully expanded leaves per sample, typically providing sufficient sap [14,61]. Whereas protocols differ in strawberries (requiring 60–100 petioles and leaves [62]) and grapevines (up to ~200 petioles due to lower sap volume in the tissues [42]). These variations reflect physiological traits, e.g., succulent stems, such as those of tomatoes, yield more sap per petiole than the fibrous petioles of grapevines. This highlights that the sampling protocol may be tailored not only to the crop, but also to the target nutrient and instrument sensitivity. In CEA systems, researchers typically pool a similar number of leaves (e.g., 15–30 leaves) per sample in crops like lettuce or herbs to obtain an adequate sap volume. The best practice is to collect a generous sample (more leaves/petioles than minimally needed) and then composite and mix them before extraction to obtain a representative sample of the entire crop area. For uniform CEA crops, a sample may represent one bench or section of a greenhouse. In multi-variety areas or trials, each cultivar or treatment should be sampled separately [36].

4.3. Selection of the Age of Tissue

A unique aspect of sap analysis is the ability to sample from different ages of tissues (old vs. new) separately to assess nutrient mobility in CEA. Some commercial labs request both “old” and “young” paired samples from the same crop. For instance, Nova Crop Control in the Netherlands (commonly paired from growers, which include the oldest still healthy leaves and the youngest fully developed leaves), request separate sample bags for comparative analysis. To reduce subjectivity and promote consistency, “old” leaves are generally defined as fully mature dark-green leaves, which are considered as an older part of the plant, while “new” leaves are the most recently fully expanded leaves near the shoot apex with a lighter green color. The rationale is that mobile nutrients such as N and K will move from older to younger tissue when deficient, so differences in sap between old vs. new leaves indicate how nutrients translocate [63]. For greenhouse crops, several studies have indicated that N is the most important nutrient for sap analysis, with samples typically collected from the most recently mature leaves [14,44,50,57]. In contrast, immobile nutrients like Ca and B, which are unable to move, accumulate easily in older leaves due to their limited phloem mobility. Thus, analyzing both young and old leaves can provide a comprehensive profile of nutrients and valuable insights for plant health. For example, a sap test might show more Ca in old leaves but low Ca in new leaves, signaling an emerging Ca deficiency (which could manifest as tipburn or blossom-end rot) [64]. To support this interpretation, labs look for differences between old and new tissues as a potential indicator of nutrient imbalance issues. Thus, the dual-sampling strategy (old vs. new) is a powerful approach for diagnosing nutrient redistribution and deficiencies resulting from differences in nutrient mobility. In perennial crops, this strategy is particularly useful for monitoring nutrient status throughout the canopy.

Table 2. Leaf sampling guidelines for sap analysis in CEA crops [65].

Crops	Indicator Leaf and Leaves/Sample	Sampling Frequency	Sample Preparation
Cucumber	Most recent mature leaf (3rd–4th from the growing point), and recommended 8–10 leaves	Begin ≥2 weeks before flowering; sample weekly or at symptom onset	Place in paper bags; avoid plastic to reduce condensation; ship within 24 h
Lettuce	Recently matured, fully expanded leaf (3rd–4th from the growing point), and recommended 8–10 leaves	Routine monitoring every two weeks; collect immediately if symptoms appear	Collect mid-morning; store in paper envelopes; ship same day if possible
Spinach	Fully expanded, recently matured leaf (3rd–4th from growing point), and recommended 8–10 leaves	Every two weeks; anytime for problem diagnosis	Shipped to the laboratory in paper containers
Tomato	Most recent mature or fully expanded leaf (3rd–4th from growing point), and recommended 8–10 leaves	Begin ≥2 weeks prior to flowering; sample weekly or when issues arise	Remove midribs before placing in paper bags for shipment

summarizes the recommended sap sampling methods for greenhouse crops, including cucumbers (Cucumis sativus), lettuce (Lactuca sativa), spinach (Spinacia oleracea), and tomatoes, as outlined in the US Southern region Bulletin [65], including indicator leaf and leaves/sample, sampling frequency, and preparation steps to ensure reliable sap analysis results.

4.4. Strategies to Mitigate Sample Contamination and Deterioration

Consistency, uniformity, and contamination prevention are the keys to sap analysis, and all samples should be collected and treated in the same manner for comparability in CEA. Ensuring sample integrity is crucial to prevent deterioration, as improper handling can lead to nutrient degradation, contamination, and data inconsistencies in sap analysis in CEA. Immediately after collection, it is important to handle the tissues properly to preserve sap integrity. Leaves or petioles should be kept cool (e.g., in a chilled cooler) and turgid. In field operations, extension specialists recommend detaching petioles from leaves right away to prevent water loss through transpiration of the leaf blades [36]. In practice, many protocols recommend placing the cut samples in plastic-sealed bags (e.g., Ziplock) and ensuring that air is removed from the bags. They also advise keeping the samples shaded and cool until extraction. Samples should also be free of surface contamination: avoid leaves with soil, dust, or foliar spray residues that could taint the sap. If necessary, gently wipe or briefly rinse leaves and dry them (without soaking the petiole) to remove external residues. It is better to use presses or crushers made of non-reactive materials, such as PVC, stainless steel, or nylon, to avoid cross-contamination from metallic elements in the sap and ensure the reliability and accuracy of the sap results. The shorter the interval between collection and extraction, the better. During on-site testing, try to perform sap extraction within a few hours. For off-site analysis, overnight shipping or same-day courier delivery is ideal. Research has shown that delaying extraction or analysis beyond 24 h at room temperature leads to incorrect results and interpretations [16]. For longer storage, freezing the extracted sap (rather than the tissue) is an option; however, the continuous freezing of raw tissue is generally not recommended, unless it is part of the extraction method. To prevent cross-contamination between samples, all cutting equipment (e.g., scissors or knives) should be properly sanitized after each use. Wipe tools with 70% isopropyl alcohol or a 10% dilute bleach solution (1 part bleach, 9 parts water) between samples to remove any nutrient residues. For example, if leaves from one sample contain nutrient solution residues and the same uncleaned scissors are used on the next, the second sample could be considered a contaminated sample. Use stainless steel or ceramic material to minimize metal contamination from rust [17].

5. Analytical Methods for Quantifying Nutrients with the Help of Sap Analysis

5.1. Laboratory Established Techniques

Several analytical laboratory techniques are available for quantifying nutrients in plant sap, including High-Performance Liquid Chromatography (HPLC), the Kjeldahl method for total N, and Inductively Coupled Plasma-based techniques such as Optical Emission Spectroscopy (ICP-OES) and Mass Spectrometry (ICP-MS). Ion chromatography (IC) has also been used to quantify nutrient ions in petiole sap as an alternative to HPLC [18].

The Kjeldahl method is suitable for determining total N in sap, including both organic (including amino acids) and inorganic N forms, although it is more commonly applied to tissue analysis rather than sap, since sap usually has mostly inorganic N species such as NO₃⁻ and NH₄⁺ if taken from xylem, but phloem sap can have amino compounds [59]. ICP-OES and ICP-MS are considered gold-standard methods for multi-element nutrient quantification in plant samples, including sap [66]. For sap analysis, samples are typically subjected to basic pre-treatment (e.g., filtration, dilution, digestion, acidification) to minimize matrix interference and prevent clogging. ICP-OES detects elements based on the light emitted from excited atoms in plasma, while ICP-MS quantifies ions based on mass-to-charge ratio. These ICP-based methods, often referred to as “plasma spectrometers”, can successfully detect a wide range of elements, including both macronutrients and micronutrients, in a single run. While ICP spectrometry is highly accurate and effective for detailed nutrient profiling, it is a destructive technique, meaning the sample must be dissolved in acid, typically nitric acid, before analysis [43]. However, ICP-based methods are destructive (requiring the sample to be dissolved in acid, usually nitric acid) and are better suited for periodic, in-depth assessments rather than real-time monitoring in production systems [66].

5.2. Rapid Test Technologies

Rapid testing has revolutionized nutrient management by enabling growers to conduct on-site tests with minimal equipment in CEA. Reflectometer-based test strips (RQflex^®; Merck KGaA, Darmstadt, Germany) remain among the most widely used rapid tools due to their simplicity, portability, and cost-effectiveness. The process involves dipping a test strip into a sap sample, allowing for a chemical reaction that produces color changes over a set period. After a set reaction time, the strip is inserted into a handheld reflectometer, which measures the reflected light intensity and calculates sap nutrient concentrations. These test strips are particularly useful for monitoring nutrients such as NO₃⁻ and K⁺, but one limitation is that the high concentration of ions in the sap can interfere with accurate readings [67]. Meters such as handheld NO₃⁻ meters (Cardy meter Model CA-104, Horiba, Kyoto, Japan, and LAQUAtwin Model B-741, Horiba, Kyoto, Japan) use flat ion-selective membranes for measuring nutrients directly from the plant sap. These devices typically require a small drop (0.3 mL or even less) of sap or diluted sap. Those sensors are currently used for measuring NO₃⁻ and other nutrient concentrations in plant sap for real-time nutrient monitoring [68]. Many growers use NO₃⁻ and K⁺ as their primary sap tools. Many extension agents successfully used such meters in the 1990s to develop nutrient sufficiency ranges for sap. For example, the University of Florida has developed those ranges for vegetable crops with the help of these portable sensors [17]. Rapid sap testing is not limited to short-cycle crops. For perennial crops, RQflex^® test strips (Merck KGaA, Darmstadt, Hesse, Germany) have been successfully applied for monitoring N levels in crops like ‘Sultana’ grapevines [42]. In conclusion, rapid test technologies are the workhorses of day-to-day sap analysis in CEA, but have one limitation: rapid tools for micronutrients in sap are not widely available.

5.3. Innovative Analytical Methodologies and Their Future Significance in CEA

Analytical methodologies for sap analysis are evolving toward greater automation, integration, and even continuous monitoring of nutrients in CEA. A rapidly emerging area involves the development of sensors that can attach to a plant and measure analytes in vivo continuously. Recent advancements in microneedle (MN) technology have demonstrated the feasibility of non-destructive, real-time monitoring of essential ions such as K⁺ and Na⁺ in living plants [69]. These MN-based potentiometric sensors can penetrate vascular tissues with minimal damage, provide near-instant responses, and track ion transport dynamics under hydroponic conditions, enabling unprecedented insight into plant nutrient uptake. Furthermore, researchers have developed MN-based biosensors that can be inserted into plant tissue to detect compounds, such as glucose fluctuations, in vascular tissues. One example is an implantable organic electrochemical transistor that measures glucose in real-time [70]. Building on these advancements, next-generation MN sensors are being designed for long-term in planta ion detection tailored to diverse growing environments in CEA, representing a transformative step toward smart agriculture [71]. That device provided new insights into the diurnal fluctuations of sugar in the tree. Similarly, wearable sensors equipped with microneedles have been developed to detect phytohormones, such as salicylic acid and abscisic acid, as early indicators of stress [72]. Such technologies mainly target plant defense compounds, and the technology could be adapted for nutrients like NO₃⁻. In fact, genetically encoded fluorescent sensors for NO₃⁻ have been used in model plants to visualize NO₃⁻ dynamics [73]. This would enable truly real-time nutrient management, as the fertigation system could adjust nutrient concentrations based on plant feedback. On the less high-tech side, but still innovative, some are exploring the automation of the sampling process. Perhaps using a small robot or drone in a greenhouse to collect sap from designated leaves and run it through an onboard sensor. Microfluidic devices can take very small volumes of liquid and perform chemical analyses on a chip with tiny channels and sensors. Researchers are exploring microfluidic platforms that can take a sap sample and split it into channels, each of which tests for a different nutrient using embedded reagents or sensors. For example, a chip might have mini-ion-selective electrodes or chromogenic reagent spots for NO₃⁻, K⁺, and other nutrients, and a small sap droplet could yield a multi-nutrient readout. In principle, such a device could be a handheld or even embedded in a sensor node in the greenhouse. While not yet commercially available for sap, prototypes for analogous fluids (like human sweat or blood sensors in microfluidics) are being actively developed [74,75]. Lastly, artificial intelligence (AI) and ML are being integrated into monitoring nutrient management in CEA. While the measurements themselves might still be performed by conventional means, AI can greatly assist in interpreting sap analysis data and correlating it with other data streams (like climate conditions, growth rates, etc.). For instance, ML models could predict an impending nutrient deficiency 5 days in advance by recognizing subtle trends in sap nutrient ratios combined with environmental data. Companies currently are most likely to use algorithms to sort through sap data and provide specific nutrient recommendations [76]. AI may also analyze large datasets from multiple growers to adjust sufficiency ranges. For instance, it may be adequate to use 500 mg·L⁻¹ of lettuce sap NO₃⁻ under high light, but deficient under low light.

6. Interpretation and Application of Sap Analysis Results

6.1. Defining and Implementation Nutrient Sufficiency Ranges (NSRs)

In a CEA context, where conditions like light, temperature, and irrigation are tightly controlled, sap analysis outcomes can inform immediate adjustments to nutrient management programs. Understanding these outcomes requires clear definitions of NSRs tailored to specific crops and growth stages, acknowledgment of crop-specific nutrient behavior, and appreciation of the unique challenges greenhouses and indoor vertical farms present to interpreting sap data. NSRs are the target concentration ranges of essential nutrients within plant tissues that correspond to optimal growth and yield, representing benchmark sap nutrient levels associated with non-limiting growth. Defining NSRs for sap analysis in CEA is challenging, as these ranges must reflect the dynamic nutrient status of the plant, especially in xylem sap, which primarily transports water and inorganic nutrients. Nutrient concentration can fluctuate in response to environmental conditions, plant developmental stage, and sampling time, making it challenging to establish consistent sampling protocols. NSRs serve as diagnostic tools to determine if a plant is receiving adequate nutrients during critical growth stages and guide timely nutrient adjustments [77]. However, the accuracy of determining NSRs through sap analysis is highly influenced by several factors, including the plant’s developmental stage, nutrient interactions, climate, and the specific plant tissue analyzed [78].

To address this challenge, it is crucial to develop NSRs based on the phenological stages of crops, ensuring that they reflect the dynamic changes in plant nutrient requirements as they grow [79]. Determining NSRs typically involves extensive calibration trials, where crops are grown under varying nutrient levels, with periodic sap measurements correlated to growth rate, yield, and quality. For example, researchers in Florida developed sap sufficiency charts for vegetables by applying different N and K fertilization levels, using portable sap tests weekly, and then seeing which range of sap values aligned with maximum yield across treatments [36]. Statistical methods such as regression analysis were used to identify the sap concentration ranges most closely associated with optimal yield. From those trials, guidelines were developed: “tomato petiole sap NO₃⁻-N should be 800–1000 mg L⁻¹ during early fruiting”. Implementing NSRs in CEA is somewhat more straightforward than in open fields due to reduced environmental variability. Therefore, research is needed to establish standardized NSRs and validate them through experiments with physiological and yield outcomes under CEA systems.

Table 3. Petiole sap sufficiency ranges in CEA crops [36]. An asterisk (*) indicates that no published values are available.

Crop	Developmental Stage	NO3−-N (mg L−1)	K+ (mg L−1)
Cucumber	First fully expanded stage	800–1000	*
	When Fruits ~7.5 cm	600–800	*
	First final harvest	400–600	*
Eggplant	First fruit around 5 cm long	1200–1600	4500–5000
	First harvest	1000–1200	4000–5000
	Mid-harvest	800–1000	3500–4000
Pepper	First flower buds	1400–1600	3200–3500
	First open flowers	1400–1600	3000–3200
	Fruits half-grown	1200–1400	3000–3200
	First harvest	800–1000	2400–3000
	Second harvest	500–800	2000–2400
Strawberry	November	800–900	3000–3500
	December	600–800	3000–3500
	January	600–800	2500–3000
	February	300–500	2000–2500
	March	200–500	1800–2500
	April	200–500	1500–2000
Tomato (Greenhouse)	Transplant—2nd cluster	1000–1200	4500–5000
	2nd–5th clusters	800–1000	4000–5000
	Harvest season (December-June)	700–900	3500–4000

presents the petiole sap sufficiency ranges (ppm) for CEA crops, indicating nitrate-nitrogen (NO₃⁻-N) and potassium (K⁺) concentrations at various developmental stages [65].

6.2. Crop-Specific Concerns for Different Crops

Different crops and cultivars can exhibit distinct nutrient uptake patterns and sap composition profiles in CEA, necessitating the crop-specific interpretation of sap analysis results. For instance, fruiting vegetables like tomato may display rapid fluctuations in sap K⁺ levels, reflecting their intensive nutrient demands during the reproductive stage.

High-performing tomato vines have high K demands to support heavy fruit load, but maintaining this without antagonizing Mg or Ca uptake is a challenge. Sap analysis can be used in tomato to monitor K:Ca:Mg ratios. If sap K is too high relative to Ca, the risk of blossom end rot (Ca deficiency symptom in fruits) increases. Thus, even if K is within the sufficiency range, growers must monitor Ca. Sap Ca in the newest leaves is an indicator: if it drops too low, they might foliar feed Ca or adjust the nutrient solution to boost Ca uptake. Tomatoes can also accumulate excess NO₃⁻ if overfed N, leading to excessive foliage at the expense of fruit. Sap NO₃⁻ readings help ensure that N levels remain within an optimal range to prevent such imbalances [17].

In contrast, leafy greens (e.g., lettuce, spinach) or herbs may have more moderate sap nutrient levels, but are highly sensitive to certain imbalances, particularly with Ca. Crop-specific concerns also include how nutrients translocate between old and new tissues; many sap analysis methods involve comparing young (new) leaf sap to old leaf sap to infer mobility and uptake sufficiency. For example, a large difference in nutrient concentration between old and new leaf sap could indicate that mobile nutrients are being reallocated (potentially signaling a deficiency in the new tissue if the old leaves are being mined). Tipburn in lettuce, Ca deficiency symptoms in rapidly growing inner leaves, is a notorious issue in CEA. Sap analysis of young vs. old leaves for Ca can give an early warning. If young leaf sap Ca is significantly lower than old leaf sap Ca, this indicates that Ca is not moving fast enough toward the new growth [64]. Growers may then increase transpiration (by using fans) or add Ca to the solution. Also, NO₃⁻ accumulation is a concern both for plant health and food safety (excess NO₃⁻ near harvest can exceed regulatory threshold). Sap NO₃⁻ can be used to manage and keep sap NO₃⁻ in an optimal range, avoiding oversupply. For CEA-grown crops, such data might come from the published literature or extension guides that compile sap nutrient norms for specific growth stages. In the absence of published NSRs for a given crop, growers may need to generate their own baselines by sampling healthy high-yield plants over time and observing the sap nutrient ranges most closely associated with optimal performance.

6.3. The Challenges for NSRs in CEA Environments

There are several challenges associated with establishing NSRs in CEA. One major challenge is the variability in sap composition caused by several environmental factors. Although CEA offers a high degree of environmental control, factors such as diurnal light cycles, temperature fluctuations, humidity, and plant water status can cause short-term fluctuations in nutrient levels within the sap. For example, higher light intensity or temperature might temporarily boost transpiration and nutrient uptake, spiking certain nutrient levels in the sap due to solution concentration, whereas cloudy periods could have the opposite effect. Studies have demonstrated such diurnal effects. For example, in ‘Sultana’ grapevines, K⁺ concentrations declined by approximately 50% in the afternoon, attributed to dilution effects from increased xylem flow [42]. This variability makes it harder to distinguish true nutrient deficiencies from normal temporal fluctuations based on single sap measurements. We recommend establishing growth-stage-specific ranges, increasing sample frequency, and integrating environmental data to distinguish between nutrient imbalance and natural temporal fluctuations. Another study on tomatoes, sap NO₃⁻, NH₄⁺, and H₂PO₄⁻ concentrations were significantly higher in the afternoon compared to the morning [60]. Furthermore, growing media, fertilization strategies, and irrigation methods can significantly influence sap nutrient concentrations and should be systematically integrated into interpretation frameworks for CEA systems [16,18]. For example, tomato plants grown on various substrates (e.g., Rockwool, coco-coir) indicated differences in P concentrations in the sap due to soil-bound P fixation [16]. Similarly, nutrient interaction between NO₃⁻-N and Cl⁻ or between Ca²⁺ and Mg²⁺ in nutrient interactions can affect nutrient uptake and distribution, and affect the composition of sap and NSRs. Consistent and low application, combined with fertigation and drip irrigation, can maintain a stable petiole sap NO₃⁻-N concentration throughout the crop cycle in CEA systems [17]. To address those challenges, both growers and researchers should develop crop and substrate-based specific NSRs validated through controlled experiments, while growers should implement the frequent monitoring of sap, adjust nutrient formulation solely based on nutrient interactions, and implement the proper tracking of environmental parameters (e.g., electrical conductivity, pH, temperature) to ensure optimal crop performance. Regular sap monitoring during the phenological stages with adaptive nutrient management will help to ensure optimal crop health and establish NSRs for sap analysis in CEA.

6.4. Data Analysis for Rapid Nutrient Management Decisions

In CEA, the use of high plant densities raises the production costs and requires the ability for quick modifications to prevent potential deficiencies or toxicities in crops. The data analysis process typically involves comparing measured sap nutrient levels with target NSR values and identifying any inconsistencies. Modern sap analysis services typically provide results within hours to a day post-sampling, significantly faster than traditional dry tissue analysis, which can take more time. Portable devices that measure sap NO₃⁻-N concentrations enable on-site evaluation of N status, allowing for adjustments to fertilization strategies [36].

These methods enable immediate adjustments to developing crop needs, thereby optimizing nutrient use and minimizing surplus fertilizer application, which is crucial for sustainable agricultural practices in CEA. The process of sap analysis requires several steps: (1) collection and analysis of samples, (2) comparison of data with established standards, and (3) identification of nutrient deficiencies. By analyzing sap data over time and creating plots on a daily or weekly basis to monitor the data, growers can determine if a nutrient is consistently decreasing, indicating a potential deficiency, or if it is fluctuating due to variations in irrigation methods. Thus, the correlation between sap analysis and other techniques, including leaf analysis methods and the use of chlorophyll meters, improves the decision-making process. Prior studies have shown that sap analysis and chlorophyll meters may be mutually beneficial, with sap analysis providing a more accurate evaluation of N status in crops such as potatoes [80,81]. The combination of environmental data, fertilizer management systems, and sap analysis enables farmers to make real-time decisions, leading to increased nutrient efficiency and improved crop production. However, trained staff are highly recommended for handling sap analysis and interpretation.

Although sap analysis offers real-time insight into plant nutrient status, it should be systematically integrated with the traditional leaf analysis method to provide a precise and validated nutritional evaluation. For instance, elevated sap NO₃⁻-N concentrations may suggest N surplus, and interpreting these results alongside total N from traditional tissue analysis helps determine whether the excess N is actually affecting plant physiology [18,57]. Establishing baseline correlations between sap and tissue nutrient levels using the first calibration trial can enhance interpretation. Hence, regular laboratory confirmation of field-based tools is essential for maintaining accuracy and ensuring that rapid nutrient management decisions can be made.

7. Implementation of Sap Analysis in CEA

7.1. Real-Time Assessment of Plant Nutrient Concentrations

Implementing sap analysis in CEA requires establishing a structured protocol for crop monitoring and integrating sap testing into regular decision-making methodologies. It involves not only performing sap tests, but also determining the frequency of testing, interpreting the results in real-time, and modifying cultivation techniques accordingly. In CEA, where nutrient uptake and conditions change quickly, traditional tissue analysis, which reflects cumulative nutrient accumulation over past weeks, may lag the plant’s current physiological status. In contrast, sap analysis provides a snapshot of the soluble nutrients actively circulating in the vascular system (both xylem and phloem), revealing the current status of nutrient uptake and availability in plants [14,18]. Regular extraction of sap from selected plants enables growers to obtain immediate results for essential nutrients such as NPK. As detailed in Section 5.2, handheld meters and test strips are now available to measure certain nutrients, such as N and K, in sap, which provide results in minutes [36,37,42,68]. However, the rapid results must be balanced with considerations of accuracy, including proper calibration before use, and periodic validation against lab methods. By continuously monitoring and adjusting, plants are kept in an optimal nutritional condition, which helps to avoid the stress caused by nutrient imbalances.

7.2. Rapid Identification of Nutritional Imbalance and Deficiencies

Sap analysis can be used for the early detection of nutritional imbalances, deficiencies, or excesses, often before visible symptoms or yield losses occur. Early detection is valuable in CEA, where deficiencies may develop within days due to rapid growth rates and controlled environments. To support early detection, defined thresholds and sampling intervals (e.g., weekly or biweekly) should be developed. When comparing sap from different leaves, sap analysis could be useful in distinguishing between immobile nutrients that appear in new leaves and mobile nutrients, which often show in older leaves [17,82]. For example, a nutrient is mobile and is being translocated to new growth from older tissues if the concentration of the nutrient in the sap of older leaves is noticeably greater than that of younger leaves. Conversely, comparable levels may suggest that an immobile nutrient, such as Ca, is inadequate at the site of new tissue formation [28,63]. This ability underscores the importance of nutrient mobility and facilitates the diagnosis of early-stage imbalances, making sap analysis a crucial tool for optimizing real-time nutrient management in CEA systems.

7.3. Precise Fertilizer Application to Enhance Crop Quality and Production

Sap analysis enables precision fertilization by providing real-time data on the movement of nutrients inside plant tissues. It is essentially the practice of delivering nutrients at the optimal rate, time, and location to precisely match plant needs. In CEA, nutrient delivery is often through automated fertigation systems, where concentrated nutrient stock solutions are mixed into irrigation water. Sap analysis provides feedback on how well the current fertilization strategy is meeting plant needs, because instead of applying a standard nutrient concentration throughout a crop cycle, a grower might increase K and Ca dosing during fruit development upon seeing sap K and Ca drop as fruits set (an indication that fruits are drawing heavily on these nutrients). The K status of the plants was considered adequate, as the average leaf tissue of K concentrations fell within the established sufficiency range of K (1.0%–1.25%), and P levels were also sufficient, with leaf tissue P concentrations within or slightly below the recommended range (0.16–0.18%) for cranberries (Vaccinium macrocarpon) [83]. This suggests that the plants received precisely what they required at the appropriate times, with minimal surplus and adjusted fertilizer regimes. For example, suppose that the sap analysis consistently indicates deficiencies in micronutrients such as Zn or Mn, despite the use of a standard Hoagland solution [82]. In that case, it may be necessary to reformulate the nutrient blend to make it more consistent with the specific crop requirements. Unlike standard leaf tissue analysis, which indicates historical nutrient accumulation, sap analysis provides the immediate adjustment of nutrient imbalances, offering a dynamic and realistic approach that can significantly enhance crop quality and yield in CEA systems. Maintaining optimal nutrient levels through sap analysis can indirectly, yet powerfully, contribute to improved crop quality and yield in CEA systems. Quality parameters such as fruit size, taste, and nutrient content, leaf color, and shelf life are all influenced by nutrition. For example, consistent Ca levels in sap are tied to a lower incidence of disorders like blossom end rot in tomatoes, directly improving the marketable quality of the produce [84]. However, this makes sap analysis not just a diagnostic tool, but also a proactive strategy for creating crop productivity and quality in CEA.

8. Variability, Limitations, Lack of Standard Protocol, Economic Factors and Cost-Efficiency, Knowledge Gap and Future Directions for Sap Analysis in CEA

8.1. Variability and Limitations of Sap Analysis in CEA

Sap analysis in CEA serves as a valuable tool for real-time nutrient management. However, several limitations impact its large-scale scalability and applicability. One major challenge is that the inherent variability in sap composition is a significant challenge, influenced by diurnal cycles, environmental factors, and plant physiological processes. Plants are living organisms, and the amount of nutrients in their sap can differ by a variety of factors. Nutrient levels fluctuate throughout the day due to diurnal cycles. For instance, in tomatoes, sap NO₃⁻ may be higher in the morning due to nighttime accumulation and present lower sap NO₃⁻ levels by afternoon, as it is metabolized for growth [60]. Environmental factors, such as temperature, humidity, and light intensity, have been shown to influence transpiration rates and nutrient transport, which in turn affect sap nutrient concentration in all production systems, especially in CEA, due to the precise control and subtle nutrient changes [7,8]. To minimize diurnal variability concerns, it is recommended to collect sap samples between 8 and 10 AM, when nutrient levels are more stable in the vascular system and are less influenced by diurnal fluctuations, and a significant amount of changes in nutrient levels within vascular tissue correlate with variations in leaf water potential [61]. Another limitation is the temporal and spatial bias in tissue selection. Sap analysis often prioritizes new growing tissues, perhaps neglecting the accumulation or depletion of nutrients in older tissues. For example, if petioles are regularly taken from the top part of the plant (new growth), sap analysis could fail to identify a decline in N accumulation later in the crop cycle [14]. The sap analysis in CEA is limited by technological challenges. Measurement errors can affect nutrient readings, often caused by issues such as contamination of ion-selective membranes in electrode-based meters [61]. The accuracy of these devices may decline over time due to contamination or deterioration. To mitigate this, routine calibration before or during regular use, as well as daily or weekly cleaning, is recommended. Technological limitations can impede effective nutrition management in CEA, where precision is essential. Alternative technologies, such as portable ICP- or lab-based methods, may offer higher accuracy, but require more extensive infrastructure and higher costs.

Table 4. Challenges and proposed solutions for implementing plant sap analysis.

Challenges	Cause	Possible Solution	References
Variability in sap composition	Environmental fluctuations	Standardized sampling protocols	[60]
Lack of standard method	Different labs use different methods	Proper standard method	[17]
Economic barriers	High setup cost	Low-cost rapid test	[28]
Technological limitations	Instrument contamination	Careful handling	[61]
Complexity of real-time data interpretation	Large datasets	AI-powered data analysis tools	[76]

describes the primary challenges of sap analysis in CEA, along with proposed solutions to enhance its reliability and affordability.

8.2. Lack of Standardized Protocols and Cost-Efficiency Concerns for Sap Analysis

The absence of standardized sampling and extraction protocols also limits the current application of sap analysis. This creates substantial challenges for both the research and practical implementation in CEA. To ensure reliability and consistency, standardization is needed for sampling methodology (e.g., the specific plant part to sample, tissue age, time of day, and the quantity of leaves or petioles), extraction techniques, and analytical methods (e.g., the instruments or test kits utilized and the calibration procedures) [17]. While some labs may use the leaf blade midrib for sap testing [58], other uses the petiole from the most recent fully expanded leaves [44], which can also be considered in relation to variability concerns. As a result, inconsistent sampling and analysis techniques make it more difficult to establish reliable reference levels and compare results across CEA systems.

The lack of information about the methodologies and sufficiency levels used by private laboratories is also an issue. Although certain studies have established sufficiency ranges and the interpretation of results for some crops, most commercial labs do not disclose the source of their reference values or methodological details, complicating the validation and comparison of results for growers and researchers [17]. The lack of transparency reduces the reliability of sap results across different labs and limits their broader implementation in CEA. To address this, standardizing protocols and promoting openness in methodologies are crucial for improving the reliability and comparability of sap analysis results and publishing best practice guidelines.

Economic factors play a significant role in the adoption of sap analysis in CEA systems, particularly for small-scale operations or those with lower profit margins. Currently, sap analysis can be more expensive than traditional tissue analysis due to specialized techniques and equipment (sap press, ion-selective probes, or advanced analytical instruments) and higher labor demand for timely sample handling and analysis. The labor intensity and time sensitivity of sap sampling further add operational costs. Additionally, sap analysis is now accessible by a small number of laboratories, which may limit the availability of this service to certain growers [28]. Despite these considerations, no studies to date have demonstrated comprehensive cost comparisons between traditional tissue nutrient analysis and sap analysis [85]. Future work should assess capital investment, operational costs, and return on investment across various crops and production scales to support informed decision-making.

8.3. Knowledge Gaps and Areas for More Research

Knowledge gaps persist for sap analysis, and research largely remains limited. One major limitation is the absence of crop-specific calibration and reference ranges for NSRs of various CEA crops, including lettuce, herbs, and ornamentals. Although some progress has been made for fruiting crops like tomatoes and peppers, limited data exist on optimal sap nutrient profiles for crops grown in diverse systems, such as nutrient film technique (NFT), deep water culture (DWC), and vertical farm systems. Establishing crop and system-specific NSRs is essential for the efficient use of nutrients and the accurate interpretation of data.

The interactions of nutrients within sap analysis remain unclear because of the complex dynamic relationships within plant tissues, where nutrients interact antagonistically and synergistically. Understanding nutritional antagonisms or synergisms enables the improvement of fertilization strategies and the prevention of nutrient imbalance. Studying nutrient combinations and their interactions in various crops is essential for improving nutrient management techniques. The long-term effects of sap-based nutrient management remain uncertain and not well-documented. Long-term studies are crucial to evaluate whether sap-based fertigation leads to sustainable yield and has effects on fruit quality traits (e.g., flavor) and secondary metabolite production (e.g., antioxidants, flavonoids), or even gene expression related to nutrient stress responses.

8.4. Future Directions

The application of sap analysis in CEA is still evolving, and we anticipate several developments that will make it more effective, accessible, and practically integrated into crop management. This will make sap analysis more powerful, user-friendly, and integrated into daily management and validation across CEA systems. Automated systems capable of periodically sampling plant sap and analyzing it without human intervention would be extremely beneficial in reducing costs and increasing efficiency.

Another promising development is the advancement of real-time site sensors. Integration with AI and climate control is also a likely future advancement. Future CEA systems will likely use AI not just to interpret data, but also to control systems. We predict integrated “nutrient algorithms” that take sap data, nutrient solution data, and growth models to maintain optimal conditions. Another critical step is the standardization of sap analysis protocols. A global or regional consensus on tissue type (leaf, petiole), sampling time of day, extraction methods, and calibration standards will enhance cross-study comparability, facilitate dataset development, and improve diagnostic reliability. Expanded databases for interpretation will further strengthen sap analysis. Future cloud-based, crop-specific databases may include not only sufficiency ranges, but also typical nutrient profiles across conditions and multivariate diagnostic patterns (e.g., what low Mn combined with high Fe might indicate). Sustainability and nutrient recycling are additional future applications. Sap analysis can help manage nutrient delivery with high precision, reduce runoff, and enhance closed-loop systems. Finally, broader education and adoption will be essential. Greater grower awareness, cost reduction, and proof of return on investment will accelerate uptake. Training programs, extension activities, webinars, and even professional certifications ensure that users know how to interpret sap analysis results correctly.

9. Conclusions

This review indicates that plant sap analysis is an effective approach for enhancing nutrient management in CEA. Sap analysis provides real-time data on nutrient availability, allowing for the early identification of nutrient deficiencies and excesses. This approach enables more accurate fertilization strategies than traditional tissue testing. Therefore, sap-based management enhances crop yield, quality, and resource efficiency, concurrently minimizing environmental impact. The broader adoption of sap analysis is hampered by several challenges, including the lack of standardized sampling and extraction protocols, limited crop, growth, and stage-specific NSRs, and uncertainties regarding economic feasibility. The variability in sap composition across cultivars and environmental conditions presents challenges for the consistent interpretation of data.

To address these barriers, further directions should prioritize the development and validation of standardized methodologies across major CEA crops, generating multi-year datasets to refine NSRs that account for crop types, growth stages, and environmental conditions. Additionally, efforts should focus on calibrating sap nutrient data with plant performance outcomes, such as growth rate, yield, and plant tissue content, to ensure accuracy, while also assessing economic viability through cost analysis and the integration of sap analysis into fertigation controllers, crop management software, and environmental monitoring systems. Further advances should include the use of real-time technologies, such as AI, IoT, and ML, for automation. Providing stakeholder-specific guidance, such as staff training programs, equipment specifications, and adoption roadmaps, will support widespread implementation. Addressing these constraints will enable sap analysis to serve as an essential component of precision nutrient management, thus significantly improving sustainable food production in CEA systems.