# Evaluation of Baby Leaf Products Using Hyperspectral Imaging Techniques
## 1 Introduction  
Growing buyer interest in the environmental impact and misuse of non-renewable resources has increased research on the introduction of means to optimize the use ofthese resources and product quality. The escalating public interest in the environmental ramifications and the unsustainable exploitation of non-renewable resources has stimulated research aimed at developing strategies to optimize their use and concurrently enhance product quality [1]. The complex interaction between water resources and agri-food production is driven by the concepts of food security and environmental sustainability [2]. Global population growth coupled with rapid economic development in various regions exerts significant pressure on the demand for food and agricultural products in general. The combined effects of global population expansion and accelerated economic development in numerous regions lead to a significant increase in the demand for food and agricultural products [3]. According to Food and Agriculture Organization (FAO) projections for 2050, the combined increase in these factors could lead to a growth in global food demand of more than 70 %, with peaks of more than 100%, in some developing nations [4]. The goal is to meet growing needs through the development of sustainable agronomic practices that balance technical and economic considerations with environmental impacts and social benefits [5]. To understand the influence of climate change on plant growth and water use, it is necessary to appreciate how the water use efficiency (WUE) can be affected. Understanding the influence of climate change on plant growth and water use is essential for appreciating its impact on water use efficiency (WUE). Maximizing WUE is one way to mitigate the effects of a changing climate, and exploring mechanisms to increase WUE in agricultural systems is key to exploiting limited water resources. Addressing climate change requires that the physical and biological factors that interact to create high WUE be understood and is essential to ensure agricultural productivity and the resilience of cropping systems in a context of increasing climate change-induced water scarcity and variability [6]. Furthermore, maximizing WUE in agriculture is crucial due to the increasing competition for finite water resources between agriculture, industry, and civil use, where several technologies, like decenter centrifuge, were developed for the dewatering of sludge. Given the intensifying competition for finite water resources across agricultural, industrial, and civil applications, enhancing water use efficiency (WUE) in agriculture has become critically important [7]. This is even more intensified by population growth and increasing affluence, in a context where the development of new water sources is economically and ecologically limited. Agriculture, being the largest consumer of water globally and often perceived as inefficient, becomes a prime target for efficiency improvement in a scenario of increasing global water scarcity that may soon limit food production [8]. To maximize the WUE in crops, it is essential to accurately determine the water consumption of plants [9]. Nowadays, there are several techniques for optimizing water use in agriculture, the efficiency of which varies depending on the irrigation method, which can be optimized with certain measures. A range of techniques is currently employed to optimize water use in agricultural systems. The inherent efficiency of these techniques exhibits considerable variability, largely contingent upon the specific irrigation method utilized. Consequently, achieving maximal water-use efficiency necessitates the application of tailored optimization measures, strategically adapted to the characteristics of each irrigation approach [10]. Furthermore, there is a development trend towards more innovative and advanced technologies such as satellite sensors, drones, GPS, and telemetry systems by means of which farmers can accurately monitor soil conditions and crop water requirements in real time [11].