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Current IssueEditorial BoardOnline First ArticlesArchive

  • Submitted23-07-2025|

  • Accepted25-10-2025|

  • First Online 08-11-2025|

  • doi 10.18805/LRF-890

ABSTRACT

Background: Soil moisture affects alfalfa biomass, nutritive value and physiological processes. Implementing precision agriculture for moisture management during alfalfa cultivation can help sustain high-quality forage production. This study aimed to assess limited irrigation effects on biomass, growth characteristics, nutritive value and hyperspectral wavelength in alfalfa (Medicago sativa L.).

Methods: The experiment was conducted in a greenhouse at Kansas State University from May to November 2024. Irrigation was applied based on field capacity (FC) at four levels namely 55% (FC55), 70% (FC70), 85% (FC85) and 100% (FC100).

Result: The findings indicated that above- and below-ground biomass and growth characteristics, including growth stage, leaf area index, number of nodules, crown size and taproot diameter as well as normalized difference vegetation index (NDVI) improved with increasing FC. FC85 appeared to be the optimal growth condition related to roots and nodules. The leaf to stem ratio was highest in FC55, which showed the same trend as nutritive values, including crude protein (CP), acid detergent fiber (ADF) and relative feed value (RFV). The hyperspectral reflectance was high in FC55, indicating drought stress. The optimal field capacity for balanced above- and below-ground growth in alfalfa appeared to be 85% while showing signs of water stress in FC55.

INTRODUCTION

Alfalfa (Medicago sativa L.) is a perennial forage legume its high biomass and superior nutritive value (Putnam et al., 2007). In 2024, Kansas ranked 14th in U.S. hay production, with 1.5 million tons of alfalfa from 580,000 acres and over 84% of this was rainfed (USDA-NASS, 2024, 2025). However, rising temperatures and declining summer precipitation have increased drought frequency in Kansas (NOAA, 2022).
       
Drought is a major constraint to plant survival and production, often reducing  yield up to 70% (Farooq et al., 2012; Baral et al., 2022). Under the drought, alfalfa allocates more resources to root development while reducing leaf size and area, stem number and length with delaying maturity (Diatta et al., 2021). These shifts lower photo-synthesis and biomass, but may enhance nutritive vale by increasing the leaf to stem ratio and reducing fiber content, which in followed by improving alfalfa quality (Diatta et al., 2021).
       
The Ogallala Aquifer, spanning several Great Plains states including Kansas, is under threat of depletion by 2100 (Haacker et al., 2016). As its availability declines, precise water management strategies based on soil moisture content will be critical for sustaining high alfalfa production.
       
Precision agricultural technologies offer solution to maximize both forage biomass and quality (Dey et al., 2024, 2025). The normalized difference vegetation index (NDVI) is widely used to detect moisture stress (Zhang et al., 2019) and biomass (Ehlert, 2002), though responses vary by species (Hatfield et al., 2008). Soil moisture-based irrigation scheduling is important to optimize water use (Dey et al., 2024). Thus, assessing optimal water supply thresholds based on soil moisture levels is crucial for alfalfa cultivation. Hyperspectral imaging offers potential to monitoring biomass (Feng et al., 2020), cutting time (Cevoli et al., 2022), morphology and biochemical composition (Garriga et al., 2020) and nutritive value (Gámez  et al., 2024; Dey et al., 2025). While commonly applied in crops like corn and wheat under drought (Okyere et al., 2024), its application in alfalfa remains limited. Previous studies have focused mainly on morphology or forage quality, there is a need to integrate physiological measures with hyperspectral imaging to more precisely identify water-stress thresholds in alfalfa.
       
Most greenhouse studies on alfalfa have focused on factors such as drought influences on root and leaf morphology (Pembleton et al., 2009; Prince et al., 2022) and forage quality (Halim et al., 1989). There is a lack of research on how alfalfa biomass and growth characteristics respond to real-time soil moisture monitoring.
       
It is hypothesized that monitoring drought stress in alfalfa can be used to determine the soil moisture threshold that achieves an optimal balance between production and forage quality. This study aimed to evaluate the effect of water limitation on alfalfa biomass, growth characteristics, nutritive value and spectral responses under controlled greenhouse environment and identify critical water stress thresholds using hyperspectral image.

MATERIALS AND METHODS

This experiment was conducted in a greenhouse at Kansas State University, Manhattan, Kansas, from May to November 2024 for seven months. The alfalfa variety used was L442RR. The seeds were planted in the North Agronomy Farm at Manhattan, KS on April 17, 2024. Later, at the early vegetative growth stage four alfalfa plants were transplanted into pots.
       
A loam textured soil was used for pH of 7.95, phosphorus (P) of 31 ppm and potassium (K) of 182 ppm. The pots were made up of PVC pipes with a length of 50 cm and diameter of 20 cm. The temperature was set at 24/18oC in the day/night cycle and the lights were continuously turned on. To ensure uniform growth before treatment, all plants were cutted at 10% bloom. Subsequent cuttings were performed at approximately 30 days interval. Alfalfa samples and data were collected on July 23, August 22, September 26 and October 29.
       
The experiment followed a randomized complete block design (RCBD) with five replications. Four irrigation treatments were applied based on soil field capacity (FC) 55% (FC55), 70% (FC70), 85% (FC85) and 100% (FC100), with average daily water application rates of 176, 248, 307 and 386 mm, respectively. Soil moisture levels were continuously monitored using a soil moisture sensor (TDR-315H, Acclima, USA).
       
Aboveground biomass was calculated by multiplying the dry matter (DM) percentage by fresh weight, with DM determined after drying samples at 65oC for 72 hours. Belowground biomass was measured after the fourth cut by weighing the roots, using the same method as aboveground biomass. Dried samples used for nutritive value analysis were grounded with a Wiley mill to pass through a 1 mm mesh.
       
Growth stages were assessed following Fick and Mueller (1989). Plant height was measured from the soil surface to the top of the plant. The leaf to stem ratio was determined by manually separating leaves and stems calculating its respective dry weights. Leaf area was measured using an LI-3100C area meter (LI-COR, USA) and leaf area index (LAI) was calculated by multiplying leaf area by the number of leaves and dividing by the pot area. Taproot diameter was measured at a 5 cm depth below the soil surface. Nodules were counted by activating it on the roots and crown size was measured by determining the crown diameter. The root/shoot ratio was calculated by comparing below-and above-ground biomass after the fourth cut.
       
Forage nutritive value was analyzed using a near-infrared reflectance spectroscopy (NIRS) following Marten et al., (1985), including crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrients (TDN), in vitro dry matter digestibility (IVDMD), lignin, relative feed value (RFV) and relative forage quality (RFQ).
       
Chlorophyll content was measured using a SPAD-502 Plus meter (Konica Minolta, Japan). NDVI was assessed using a green seeker sensor (Trimble, USA). Hyperspectral reflectance was recorded using an ASD FieldSpec 3 spectroradiometer (ASD Inc., USA) within a wavelength range of 350-2,000 nm. Hyperspectral reflectance was calibrated and processed with RS3 and ViewSpec Pro software (ASD Inc., USA).
               
Data analysis was analyzed using SPSS 24 (IBM Inc., 2019). The significance of treatments on the above-and below-ground biomass, growth characteristics, nutritive value and sensing data were tested using analysis of variance (ANOVA). Mean differences among treatments were compared using the least significant difference (LSD) test at a 5% significance level.

RESULTS AND DISCUSSION

Above-and below-ground biomass
 
Aboveground biomass significantly increased with higher FC levels (P<0.05, Fig 1a). Compared to FC100, above-ground biomass in FC55, 70 and 85 were decreased by 77.7, 51.9 and 32.2%, respectively. Total aboveground biomass followed a similar trend in 8.6, 18.6, 28.1 and 38.6 g pot-1 with FC55, 70, 85 and 100, respectively (P<0.05, Fig 1b). Belowground biomass of FC55, 70, 85 and 100 was 6.2, 9.1, 13.1 and 12.6 g pot-1, respectively, with significantly higher values in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 1c).

Fig 1: Aboveground (a), total aboveground (b) and belowground (c) biomass of alfalfa by water-limiting treatments.


       
Reduced aboveground biomass under drought through delaying the alfalfa growth is consistent with previous studies (Farooq et al., 2012; Diatta et al., 2021). Also, alfalfa appeared to have a more pronounced decrease in aboveground biomass than in belowground biomass during drought consistent with findings by Li et al., (2011).
 
Growth characteristics
 
Plant height increased significantly with higher FC levels (P<0.05, Table 1). Growth stage was significantly greater in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 2a), with FC55 showing the youngest maturity. As stem height increases, alfalfa tends to mature, leading to an increase in stem weight (Ray et al., 1999). In water stress, delayed growth led to lower alfalfa maturity, as reported by Diatta et al., (2021).

Table 1: Above- and below-ground morphology and sensing data of alfalfa by water-limiting treatments.



Fig 2: Growth stage (a), leaf to stem ratio (b), leaf area index (c) and root/shoot ratio (d) of alfalfa by water-limiting treatments.


       
Taproot diameter was the highest in FC85 (P<0.05, Table 1), while crown size and nodule number were significantly higher in FC85 and 100 (P<0.05). Previous study has also reported that drought reduces nodule formation in alfalfa (Diatta et al., 2021). In FC55, the reduced nodule count suggests that it is not an optimal condition.
 
Morphological chanage
 
Leaf to stem ratio was significantly higher in FC55 than in other treatments (P<0.05, Fig 2b). Drought increased leaf to stem ratio by 20% due to reduced stem development (Petit et al., 1992), which enhanced forage quality especially CP content as increasing leaf ratio (Avci et al., 2018; Diatta et al., 2021).
       
Leaf area of alfalfa increased with higher FC levels (P<0.05, Table 1). Similarly, LAI was significantly higher in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 2c). LAI of FC55 was reduced by 82.4% compared to FC100. The root/shoot ratio was significantly higher in FC55 than in other treatments (P<0.05, Fig 2d).
       
These are indicating a shift toward root development under stress. This aligns with Carter and Sheaffer (1983), who observed a 39% reduction in leaf size under drought. Alfalfa reduces leaf expansion and enhances root growth to conserve water (Aranjuelo et al., 2011; Erice et al., 2010). Smaller leaves under stress improve drought tolerance by reducing transpiration (De Micco and Aronne, 2007). Based on these results, FC85 appeared to be the optimal threshold for alfalfa growth.
 
Nutritive value
 
CP content with FC55 was significantly higher than FC100 (P<0.05, Table 2, while ADF showed the opposite trend (P<0.05). Notably, CP content decreased by 11.5% from FC100 compared to FC55. RFV was significantly higher in FC55 at 266.3 compared to FC100 at 209.9 (P<0.05, Table 2). There were no significant differences these from FC50 to FC85 treatments (P>0.05, Table 2). Other nutritive contents did not differ by the treatments (P>0.05, Table 2).

Table 2: Nutritive value of alfalfa by water-limiting treatments.


       
Drought conditions typically raise CP and lower fiber content due to increased leaf proportion (Fiasconaro et al., 2012). Although Staniak and Harasim (2018) found no difference in CP between FC70 and FC40 in pots, other studies reported improved quality under stress (Abid et al., 2016; Holman et al., 2016). Delayed growth under drought conditions enhanced the nutritive value of alfalfa (Diatta et al., 2021; Fiasconaro et al., 2012; Karayilanli and Ayhan, 2016; Marković et al., 2022). FC55 appeared to produce high quality alfalfa and its nutritive value was not different from that of the FC85 treatment.
 
NDVI, chlorophyll content and hyperspectral reflectance
 
NDVI values of FC55, 70, 85 and 100 were 0.43, 0.52, 0.63 and 0.64, which were significantly higher in FC85 and 100 than in FC55 and 70 (P<0.05, Table 1). These values were lower than field values (0.55-0.80; Masialeti et al., 2010), likely due to lower plant density, which was four plants per pot compared to 20 alfalfa plants ft² recommended in the field (Mueller et al., 2007). NDVI was lowest in FC55, reflecting greater stress and unhealthy. NDVI values in FC85 and 100 were similar, possibly due to saturation in biomass and LAI (Del Pozo et al., 2023), suggesting growth was optimized at FC85. The SPAD values did not significantly differ among treatments (P>0.05, Table 1).
       
Alfalfa exhibits a typical hyperspectral reflectance pattern, in which strong chlorophyll absorption in the blue (450-500 nm) and red (600-700 nm) bands results in lower reflectance, while higher reflectance in the near-infrared (NIR; 800-900 nm) band is caused by scattering in the spongy mesophyll (Feng et al., 2020). FC55, which was the highest reflectance, showed reduced chlorophyll absorption and lower leaf pigment concentration, as indicated by its higher overall reflectance values (Okyere et al., 2024). Notably, this study observed higher NIR reflectance in FC55, which was the youngest growth stage, compared to the other treatments, which were at older growth stages, consistent with Zhao et al., (2023).  Furthermore, FC55 exhibited a smaller decline in reflectance at the water absorption bands of 1450 and 1950 nm compared to other treatments, indicating severe drought stress. In contrast, FC70 to FC100 displayed similar absorption features at these wavelengths [Fig 3 (a); (b)], indicating adequate water content. Consequently, hyperspectral wavelength suggests that FC55 experienced significant drought stress, potentially representing the water-stress as the drought threshold for alfalfa. Using hyperspectral reflectance as a real-time forecasting tool could enhance alfalfa production and maintaining FC85 would optimize biomass, growth charateristics and forage quality simultaneously.

Fig 3: Hyperspectral reflectance curve by water-limiting treatments.

CONCLUSION

This study examined the effects of water-limited conditions on alfalfa biomass, growth characteristics and nutritive value, while also using hyperspectral reflectance to identify the threshold of water stress. Both aboveground biomass and growth characteristics increased with higher FC, whereas belowground biomass and growth improved at FC85. FC55 showed higher leaf-to-stem and root/shoot ratios, along with improved nutritive values, which partially offset its reduced biomass. Hyperspectral reflectance was the higested at FC55, indicating that this treatment experienced the most severe water stress. Overall, FC85 represented the optimal balance, supporting both above- and below- ground biomass while maintaining forage quality comparable to FC55. Since this experiment was conducted as a one-year greenhouse trial, further multi-year studies on cropland are necessary to validate these findings, including the production and economic benefits of alfalfa.

ACKNOWLEDGEMENT

The present study was supported by the USDA National Institute of Food and Agriculture, Alfalfa Seed and Alfalfa Forage System Program (ASAFS) (Grant no: 2023-70005-41080).
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
This research did not involve any animal experiments.

CONFLICT OF INTEREST

 The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish or preparation of the manuscript.

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    • Submitted23-07-2025|

    • Accepted25-10-2025|

    • First Online 08-11-2025|

    • doi 10.18805/LRF-890

    ABSTRACT

    Background: Soil moisture affects alfalfa biomass, nutritive value and physiological processes. Implementing precision agriculture for moisture management during alfalfa cultivation can help sustain high-quality forage production. This study aimed to assess limited irrigation effects on biomass, growth characteristics, nutritive value and hyperspectral wavelength in alfalfa (Medicago sativa L.).

    Methods: The experiment was conducted in a greenhouse at Kansas State University from May to November 2024. Irrigation was applied based on field capacity (FC) at four levels namely 55% (FC55), 70% (FC70), 85% (FC85) and 100% (FC100).

    Result: The findings indicated that above- and below-ground biomass and growth characteristics, including growth stage, leaf area index, number of nodules, crown size and taproot diameter as well as normalized difference vegetation index (NDVI) improved with increasing FC. FC85 appeared to be the optimal growth condition related to roots and nodules. The leaf to stem ratio was highest in FC55, which showed the same trend as nutritive values, including crude protein (CP), acid detergent fiber (ADF) and relative feed value (RFV). The hyperspectral reflectance was high in FC55, indicating drought stress. The optimal field capacity for balanced above- and below-ground growth in alfalfa appeared to be 85% while showing signs of water stress in FC55.

    INTRODUCTION

    Alfalfa (Medicago sativa L.) is a perennial forage legume its high biomass and superior nutritive value (Putnam et al., 2007). In 2024, Kansas ranked 14th in U.S. hay production, with 1.5 million tons of alfalfa from 580,000 acres and over 84% of this was rainfed (USDA-NASS, 2024, 2025). However, rising temperatures and declining summer precipitation have increased drought frequency in Kansas (NOAA, 2022).
           
    Drought is a major constraint to plant survival and production, often reducing  yield up to 70% (Farooq et al., 2012; Baral et al., 2022). Under the drought, alfalfa allocates more resources to root development while reducing leaf size and area, stem number and length with delaying maturity (Diatta et al., 2021). These shifts lower photo-synthesis and biomass, but may enhance nutritive vale by increasing the leaf to stem ratio and reducing fiber content, which in followed by improving alfalfa quality (Diatta et al., 2021).
           
    The Ogallala Aquifer, spanning several Great Plains states including Kansas, is under threat of depletion by 2100 (Haacker et al., 2016). As its availability declines, precise water management strategies based on soil moisture content will be critical for sustaining high alfalfa production.
           
    Precision agricultural technologies offer solution to maximize both forage biomass and quality (Dey et al., 2024, 2025). The normalized difference vegetation index (NDVI) is widely used to detect moisture stress (Zhang et al., 2019) and biomass (Ehlert, 2002), though responses vary by species (Hatfield et al., 2008). Soil moisture-based irrigation scheduling is important to optimize water use (Dey et al., 2024). Thus, assessing optimal water supply thresholds based on soil moisture levels is crucial for alfalfa cultivation. Hyperspectral imaging offers potential to monitoring biomass (Feng et al., 2020), cutting time (Cevoli et al., 2022), morphology and biochemical composition (Garriga et al., 2020) and nutritive value (Gámez  et al., 2024; Dey et al., 2025). While commonly applied in crops like corn and wheat under drought (Okyere et al., 2024), its application in alfalfa remains limited. Previous studies have focused mainly on morphology or forage quality, there is a need to integrate physiological measures with hyperspectral imaging to more precisely identify water-stress thresholds in alfalfa.
           
    Most greenhouse studies on alfalfa have focused on factors such as drought influences on root and leaf morphology (Pembleton et al., 2009; Prince et al., 2022) and forage quality (Halim et al., 1989). There is a lack of research on how alfalfa biomass and growth characteristics respond to real-time soil moisture monitoring.
           
    It is hypothesized that monitoring drought stress in alfalfa can be used to determine the soil moisture threshold that achieves an optimal balance between production and forage quality. This study aimed to evaluate the effect of water limitation on alfalfa biomass, growth characteristics, nutritive value and spectral responses under controlled greenhouse environment and identify critical water stress thresholds using hyperspectral image.

    MATERIALS AND METHODS

    This experiment was conducted in a greenhouse at Kansas State University, Manhattan, Kansas, from May to November 2024 for seven months. The alfalfa variety used was L442RR. The seeds were planted in the North Agronomy Farm at Manhattan, KS on April 17, 2024. Later, at the early vegetative growth stage four alfalfa plants were transplanted into pots.
           
    A loam textured soil was used for pH of 7.95, phosphorus (P) of 31 ppm and potassium (K) of 182 ppm. The pots were made up of PVC pipes with a length of 50 cm and diameter of 20 cm. The temperature was set at 24/18oC in the day/night cycle and the lights were continuously turned on. To ensure uniform growth before treatment, all plants were cutted at 10% bloom. Subsequent cuttings were performed at approximately 30 days interval. Alfalfa samples and data were collected on July 23, August 22, September 26 and October 29.
           
    The experiment followed a randomized complete block design (RCBD) with five replications. Four irrigation treatments were applied based on soil field capacity (FC) 55% (FC55), 70% (FC70), 85% (FC85) and 100% (FC100), with average daily water application rates of 176, 248, 307 and 386 mm, respectively. Soil moisture levels were continuously monitored using a soil moisture sensor (TDR-315H, Acclima, USA).
           
    Aboveground biomass was calculated by multiplying the dry matter (DM) percentage by fresh weight, with DM determined after drying samples at 65oC for 72 hours. Belowground biomass was measured after the fourth cut by weighing the roots, using the same method as aboveground biomass. Dried samples used for nutritive value analysis were grounded with a Wiley mill to pass through a 1 mm mesh.
           
    Growth stages were assessed following Fick and Mueller (1989). Plant height was measured from the soil surface to the top of the plant. The leaf to stem ratio was determined by manually separating leaves and stems calculating its respective dry weights. Leaf area was measured using an LI-3100C area meter (LI-COR, USA) and leaf area index (LAI) was calculated by multiplying leaf area by the number of leaves and dividing by the pot area. Taproot diameter was measured at a 5 cm depth below the soil surface. Nodules were counted by activating it on the roots and crown size was measured by determining the crown diameter. The root/shoot ratio was calculated by comparing below-and above-ground biomass after the fourth cut.
           
    Forage nutritive value was analyzed using a near-infrared reflectance spectroscopy (NIRS) following Marten et al., (1985), including crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrients (TDN), in vitro dry matter digestibility (IVDMD), lignin, relative feed value (RFV) and relative forage quality (RFQ).
           
    Chlorophyll content was measured using a SPAD-502 Plus meter (Konica Minolta, Japan). NDVI was assessed using a green seeker sensor (Trimble, USA). Hyperspectral reflectance was recorded using an ASD FieldSpec 3 spectroradiometer (ASD Inc., USA) within a wavelength range of 350-2,000 nm. Hyperspectral reflectance was calibrated and processed with RS3 and ViewSpec Pro software (ASD Inc., USA).
                   
    Data analysis was analyzed using SPSS 24 (IBM Inc., 2019). The significance of treatments on the above-and below-ground biomass, growth characteristics, nutritive value and sensing data were tested using analysis of variance (ANOVA). Mean differences among treatments were compared using the least significant difference (LSD) test at a 5% significance level.

    RESULTS AND DISCUSSION

    Above-and below-ground biomass
     
    Aboveground biomass significantly increased with higher FC levels (P<0.05, Fig 1a). Compared to FC100, above-ground biomass in FC55, 70 and 85 were decreased by 77.7, 51.9 and 32.2%, respectively. Total aboveground biomass followed a similar trend in 8.6, 18.6, 28.1 and 38.6 g pot-1 with FC55, 70, 85 and 100, respectively (P<0.05, Fig 1b). Belowground biomass of FC55, 70, 85 and 100 was 6.2, 9.1, 13.1 and 12.6 g pot-1, respectively, with significantly higher values in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 1c).

    Fig 1: Aboveground (a), total aboveground (b) and belowground (c) biomass of alfalfa by water-limiting treatments.


           
    Reduced aboveground biomass under drought through delaying the alfalfa growth is consistent with previous studies (Farooq et al., 2012; Diatta et al., 2021). Also, alfalfa appeared to have a more pronounced decrease in aboveground biomass than in belowground biomass during drought consistent with findings by Li et al., (2011).
     
    Growth characteristics
     
    Plant height increased significantly with higher FC levels (P<0.05, Table 1). Growth stage was significantly greater in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 2a), with FC55 showing the youngest maturity. As stem height increases, alfalfa tends to mature, leading to an increase in stem weight (Ray et al., 1999). In water stress, delayed growth led to lower alfalfa maturity, as reported by Diatta et al., (2021).

    Table 1: Above- and below-ground morphology and sensing data of alfalfa by water-limiting treatments.



    Fig 2: Growth stage (a), leaf to stem ratio (b), leaf area index (c) and root/shoot ratio (d) of alfalfa by water-limiting treatments.


           
    Taproot diameter was the highest in FC85 (P<0.05, Table 1), while crown size and nodule number were significantly higher in FC85 and 100 (P<0.05). Previous study has also reported that drought reduces nodule formation in alfalfa (Diatta et al., 2021). In FC55, the reduced nodule count suggests that it is not an optimal condition.
     
    Morphological chanage
     
    Leaf to stem ratio was significantly higher in FC55 than in other treatments (P<0.05, Fig 2b). Drought increased leaf to stem ratio by 20% due to reduced stem development (Petit et al., 1992), which enhanced forage quality especially CP content as increasing leaf ratio (Avci et al., 2018; Diatta et al., 2021).
           
    Leaf area of alfalfa increased with higher FC levels (P<0.05, Table 1). Similarly, LAI was significantly higher in FC85 and 100 than in FC55 and 70 (P<0.05, Fig 2c). LAI of FC55 was reduced by 82.4% compared to FC100. The root/shoot ratio was significantly higher in FC55 than in other treatments (P<0.05, Fig 2d).
           
    These are indicating a shift toward root development under stress. This aligns with Carter and Sheaffer (1983), who observed a 39% reduction in leaf size under drought. Alfalfa reduces leaf expansion and enhances root growth to conserve water (Aranjuelo et al., 2011; Erice et al., 2010). Smaller leaves under stress improve drought tolerance by reducing transpiration (De Micco and Aronne, 2007). Based on these results, FC85 appeared to be the optimal threshold for alfalfa growth.
     
    Nutritive value
     
    CP content with FC55 was significantly higher than FC100 (P<0.05, Table 2, while ADF showed the opposite trend (P<0.05). Notably, CP content decreased by 11.5% from FC100 compared to FC55. RFV was significantly higher in FC55 at 266.3 compared to FC100 at 209.9 (P<0.05, Table 2). There were no significant differences these from FC50 to FC85 treatments (P>0.05, Table 2). Other nutritive contents did not differ by the treatments (P>0.05, Table 2).

    Table 2: Nutritive value of alfalfa by water-limiting treatments.


           
    Drought conditions typically raise CP and lower fiber content due to increased leaf proportion (Fiasconaro et al., 2012). Although Staniak and Harasim (2018) found no difference in CP between FC70 and FC40 in pots, other studies reported improved quality under stress (Abid et al., 2016; Holman et al., 2016). Delayed growth under drought conditions enhanced the nutritive value of alfalfa (Diatta et al., 2021; Fiasconaro et al., 2012; Karayilanli and Ayhan, 2016; Marković et al., 2022). FC55 appeared to produce high quality alfalfa and its nutritive value was not different from that of the FC85 treatment.
     
    NDVI, chlorophyll content and hyperspectral reflectance
     
    NDVI values of FC55, 70, 85 and 100 were 0.43, 0.52, 0.63 and 0.64, which were significantly higher in FC85 and 100 than in FC55 and 70 (P<0.05, Table 1). These values were lower than field values (0.55-0.80; Masialeti et al., 2010), likely due to lower plant density, which was four plants per pot compared to 20 alfalfa plants ft² recommended in the field (Mueller et al., 2007). NDVI was lowest in FC55, reflecting greater stress and unhealthy. NDVI values in FC85 and 100 were similar, possibly due to saturation in biomass and LAI (Del Pozo et al., 2023), suggesting growth was optimized at FC85. The SPAD values did not significantly differ among treatments (P>0.05, Table 1).
           
    Alfalfa exhibits a typical hyperspectral reflectance pattern, in which strong chlorophyll absorption in the blue (450-500 nm) and red (600-700 nm) bands results in lower reflectance, while higher reflectance in the near-infrared (NIR; 800-900 nm) band is caused by scattering in the spongy mesophyll (Feng et al., 2020). FC55, which was the highest reflectance, showed reduced chlorophyll absorption and lower leaf pigment concentration, as indicated by its higher overall reflectance values (Okyere et al., 2024). Notably, this study observed higher NIR reflectance in FC55, which was the youngest growth stage, compared to the other treatments, which were at older growth stages, consistent with Zhao et al., (2023).  Furthermore, FC55 exhibited a smaller decline in reflectance at the water absorption bands of 1450 and 1950 nm compared to other treatments, indicating severe drought stress. In contrast, FC70 to FC100 displayed similar absorption features at these wavelengths [Fig 3 (a); (b)], indicating adequate water content. Consequently, hyperspectral wavelength suggests that FC55 experienced significant drought stress, potentially representing the water-stress as the drought threshold for alfalfa. Using hyperspectral reflectance as a real-time forecasting tool could enhance alfalfa production and maintaining FC85 would optimize biomass, growth charateristics and forage quality simultaneously.

    Fig 3: Hyperspectral reflectance curve by water-limiting treatments.

    CONCLUSION

    This study examined the effects of water-limited conditions on alfalfa biomass, growth characteristics and nutritive value, while also using hyperspectral reflectance to identify the threshold of water stress. Both aboveground biomass and growth characteristics increased with higher FC, whereas belowground biomass and growth improved at FC85. FC55 showed higher leaf-to-stem and root/shoot ratios, along with improved nutritive values, which partially offset its reduced biomass. Hyperspectral reflectance was the higested at FC55, indicating that this treatment experienced the most severe water stress. Overall, FC85 represented the optimal balance, supporting both above- and below- ground biomass while maintaining forage quality comparable to FC55. Since this experiment was conducted as a one-year greenhouse trial, further multi-year studies on cropland are necessary to validate these findings, including the production and economic benefits of alfalfa.

    ACKNOWLEDGEMENT

    The present study was supported by the USDA National Institute of Food and Agriculture, Alfalfa Seed and Alfalfa Forage System Program (ASAFS) (Grant no: 2023-70005-41080).
     
    Disclaimers
     
    The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
     
    Informed consent
     
    This research did not involve any animal experiments.

    CONFLICT OF INTEREST

     The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish or preparation of the manuscript.

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